2024 State of Reliability
June 2024

2024 SOR Infographic
2024 SOR Overview
2024 SOR Video

Technical Assessment of2023 Bulk Power System
PerformanceTable of Contents
Preface ........................................................................................................................................................................... iii
About This Technical Assessment ................................................................................................................................... 4
Introduction ................................................................................................................................................................. 4
Purpose of the SOR ...................................................................................................................................................... 4: Major Occurrences and Report Releases for 2023 ....................................................................................... 6
Québec Wildfires ......................................................................................................................................................... 7
Utah Solar Photovoltaic (PV) Performance Improvement .......................................................................................... 8
Winter Storm Elliott Report......................................................................................................................................... 9
CAISO Battery Energy Storage System (BESS) Disturbance Report ........................................................................... 11: Severe Risks, Impact, and Resilience ........................................................................................................... 12
Severity Risk Index ..................................................................................................................................................... 12
Major Weather Events .............................................................................................................................................. 15
Impact of Extreme Event Days .................................................................................................................................. 16
Analysis of Transmission System Resilience .............................................................................................................. 19
Transmission System Resilience Statistics by Associated Weather Type: 2019–2023.............................................. 25: Grid Transformation .................................................................................................................................... 29
Resource Adequacy ................................................................................................................................................... 29
Critical Infrastructure Interdependencies ................................................................................................................. 36
Increasing Complexity of Protection and Control Systems ....................................................................................... 39
Protection System Failures Leading to Transmission Outages.................................................................................. 43
Loss of Situational Awareness ................................................................................................................................... 44
Human Performance ................................................................................................................................................. 48
Energy Emergency Alerts........................................................................................................................................... 51: Grid Performance ........................................................................................................................................ 53
Reliability Metrics ...................................................................................................................................................... 53
Frequency Response Performance ............................................................................................................................ 54
Interconnection Reliability Operating Limit Exceedances ......................................................................................... 56
Generation Performance and Availability ................................................................................................................. 57
Transmission Performance and Unavailability .......................................................................................................... 61
Appendix A: Supplemental Analysis at Interconnection Level ..................................................................................... 67
Severity Risk Index by Interconnection ..................................................................................................................... 67
Extreme Day Analysis by Interconnection ................................................................................................................. 72
Appendix B: Acknowledgements .................................................................................................................................. 76

NERC | State of Reliability | 2024
ii

Preface
Electricity is a key component of the fabric of modern society and the Electric Reliability Organization (ERO) Enterpriseserves to strengthen that fabric. The vision for the ERO Enterprise, which is comprised of NERC and the six Regional
Entities, is a highly reliable and secure North American bulk power system (BPS). Our mission is to assure the effective
and efficient reduction of risks to the reliability and security of the grid.
Reliability | Resilience | Security
Because nearly 400 million citizens in North America are counting on us
The North American BPS is made up of six Regional Entities as shown on the map and in the corresponding tablebelow. The multicolored area denotes overlap as some load-serving entities participate in one Regional Entity whileassociated Transmission Owners/Transmission Operators participate in another.

MRO

Midwest Reliability Organization

NPCC

Northeast Power Coordinating Council

RF

ReliabilityFirst

SERC

SERC Reliability Corporation

Texas RE

Texas Reliability Entity

WECC

WECC

NERC | State of Reliability | 2024
iii

About This Technical Assessment
Introduction

The State of Reliability (SOR) report seeks to inform regulators, policymakers, and industry leaders on the mostsignificant reliability risks facing the BPS and describe the actions that the ERO Enterprise has taken and will take toaddress them. This year’s SOR report is comprised of two publications: this 2024 SOR Technical Assessment, which
provides NERC’s comprehensive annual technical review of BPS reliability for the 2023 operating (calendar) year, andthe 2024 SOR Overview, 1 which is a high-level summary of the Technical Assessment, summarized by important
findings.
•

The 2024 SOR Overview replaces the key findings previously found in the Technical Assessment.

•This 2024 SOR Technical Assessment provides key occurrences and highlights major reports released in 2023,
along with in-depth analysis of risks and resilience, grid transformation and performance, and related
performance metrics.

Purpose of the SOR

Both the Overview and the Technical Assessment provide objective and concise information for policymakers,
industry leaders, and regulators on issues that affect the reliability and resilience of the North American BPS.
Specifically, the SOR report does the following:•

Analyzes performance trends and emerging reliability risks based on past performance•

Reports on the relative health of the interconnected system•

Measures the success of mitigation activities deployed

NERC, as the ERO, works to assure the effective and efficient reduction of reliability and security risks to the North
American BPS. Annual and seasonal risk assessments look to the future, and special reports on emergent risks serve
to identify and mitigate potential risks. This assessment document identifies performance trends and provides strong
technical support for those interested in the underlying data and detailed analytics.
NERC defines the reliability 2 of the interconnected BPS in terms of the following two basic and functional aspects:•

Adequacy•

Operating Reliability

The 2024 SOR report focuses on BPS 3 performance during the prior calendar year as measured by an established setof performance metrics, other reliability indicators, and more detailed analysis performed by ERO staff and technicalcommittee participants. Data used in the analysis comes from the Transmission Availability Data System (TADS), theGenerating Availability Data System (GADS), the Misoperation Information Data Analysis System (MIDAS), voluntary
reporting into the Event Analysis Management System (TEAMS), Bulk Power System Awareness monitoring andprocesses, and the Institute of Electrical and Electronics Engineers (IEEE) Distribution Reliability Working Group. ERO
staff developed this independent assessment with support from the Performance Analysis Subcommittee (PAS).
1 https://www.nerc.com/pa/RAPA/PA/Performance%20Analysis%20DL/NERC_SOR_2024_Overview.pdf

2 Learn About NERC provides background information about NERC, the definition of reliability, and the electric grid.

3 The term BPS is defined in Section 215 of the Federal Power Act as facilities and control systems necessary for operating an interconnected

electric energy transmission network (or any portion thereof); and electric energy from generating facilities needed to maintain transmission
system reliability. The term does not include facilities used in the local distribution of electric energy. 16 U.S.C. § 824o(a)(1). Bulk Electric
System (BES) is a subset of the BPS and is a defined term under the NERC Glossary as approved by the Federal Energy Regulatory Commission(FERC). As the Electric Reliability Organization, NERC is responsible for developing and enforcing Reliability Standards to ensure an adequatelevel of reliability of the BPS and assessing reliability of the BPS. NERC’s regulatory model is designed to ensure that entities capable of affecting
the reliability of the BPS are registered and subject to Reliability Standards. North Am. Elec. Reliability Corp., 187 FERC ¶ 61,196, P 53 (2024).
NERC | State of Reliability | 2024
4

About This Technical Assessment

NERC also produces the following regular assessments to evaluate BPS security as well as present and future BPS
reliability:•

Long-Term Reliability Assessment (LTRA)•

Summer and Winter Assessments•

Electricity Information Sharing and Analysis Center (E-ISAC) End-of-Year Report 4

Considerations•

Data in the SOR report represents the performance for the January–December 2023 operating year unlessotherwise noted.

•

Analysis in this report is based on data from 2019–2023 that was available in Spring 2024, and it provides abasis to evaluate 2023 performance relative to performance over the last five years. All dates and times
shown are in Coordinated Universal Time (UTC).

•To properly demonstrate key trending information, this year’s report evaluates generation data dating backto 2014.

•The SOR report is a review of industry-wide trends and not the performance of individual entities.

•

When analysis is presented by Interconnection, the Québec Interconnection is combined with the EasternInterconnection unless specific analysis for the Québec Interconnection is shown.

4 2023 E-ISAC End-of-Year Report

NERC | State of Reliability | 2024
5

: Major Occurrences and Report Releases for 2023
This chapter highlights major occurrences and reports that were issued in 2023. These occurrences and reports did
not constitute a key finding but had a notable impact on the BPS.
Figure 1.1 highlights important numbers and facts about the North American BPS. Table 1.1 shows the five-year trendof these numbers.

Figure 1.1: 2023 BPS Inventory and Performance Statistics
Table 1.1: Five-Year BPS Inventory and Performance Statistics
Rank
2019
2020
2021
2022
Actual Energy (GWh)
Summer Peak Capacity (MW)
Total Transmission Circuit Miles >100 kV miles
Number of Conventional Generating
Units > 20 MW
Portion of hours in the year with nooperator-initiated firm load shedding
associated with EEA Level 3
Category 3, 4, 5 Events (non-weather
related)Amount of unserved energy
associated with EEA Level 3 (GWh)
Number of hours with operatorinitiated load shed

2023

4,639,653
N/A

4,588,062
1,048,944

4,585,939
1,056,980

4,674,290
1,057,455

4,687,894
1,071,370

492,463503,551

511,099522,665

527,698

6,064

6,009

5,966

5,910

5,915

99.9%

99.7%

99.2%

99.4%

100%

0

0

0

1

0

5.85

828.1

1,015.5

96.2

0

>1

22

71

56.5

0

NERC | State of Reliability | 2024
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Chapter 1: Major Occurrences and Report Releases for 2023

Québec Wildfires

In Québec, the 2023 wildfire season began in May when La Société de Protection des Forêts Contre le Feu (SOPFEU), 5
a nonprofit responsible for forest fire prevention in Québec, provided the provincial power grid operator, HydroQuébec, with its first notification of a critical situation from the threat from increased wildfire activity. This wildfire
season escalated to become the worst such season in Québec’s history, quickly breaking records set during the 1923
wildfire season. 6 According to SOPFEU, 4,318,538.6 hectares (ha), the equivalent of 16,673.97 square miles, wereburned by active fires across the province (see Figure 1.2). 7 The size of the impacted area is approximately equal tothe cumulative area in the province that burned over the previous 20 years combined (equal to the area of
Massachusetts and New Hampshire). The smoke from the Québec wildfires reached New York City during Summer
2023, briefly causing hazy skies and hazardous air quality.

Figure 1.2: Map from Natural Resources Canada, June 20, 2023 8
Hydro-Québec is a public corporation utility owned by the government of Québec that manages the generation,transmission, and distribution of electricity across the province. Hydro-Québec coordinates power exchanges throughinterconnections with three Canadian provinces (Newfoundland and Labrador, New Brunswick, and Ontario) andportions of the United States, including New York and the New England states. As a direct result of the dense smoke
caused by increased wildfire activity throughout the province, Hydro-Québec experienced multiple transmission
power line outages from the operation of protection systems. To address the situation, specific operating strategies
were used to manage these challenging system conditions. During a period of increased intensity and proximity towildfires in the northern portion of the province, Hydro-Québec staff and personnel had to be evacuated from criticalgenerating and transmission facilities. The two most significant events during this period were the load-shedding
5 SOPFEU | Organization

6 The 2023 wildfire season in Québec: an overview of extreme conditions, impacts, lessons learned and considerations for the future(biorxiv.org)
7 SOPFEU | 2023 Season Review | A record-breaking season for SOPFEU
8 Natural Resources Canada, June 20, 2023

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Chapter 1: Major Occurrences and Report Releases for 2023

actions by the remedial action scheme (RAS) that operated to ensure system stability, shedding approximately 600
and 1,200 MW, respectively. 9 However, the outages were short-lived, with an average customer outage duration ofless than an hour. The wildfires also impacted high-voltage direct current (HVdc) facilities and equipment exporting
power from the province to the New England power grid operator, Independent System Operator New England, Inc.
(ISO-NE); this subsequently caused a temporary capacity deficiency event for the ISO-NE footprint. 10
Through enhanced coordination and real-time communication among neighboring Reliability Coordinators (RC),including New York Independent System Operator (NYISO), ISO-NE, Independent Electricity System Operator (IESO),
and New Brunswick Power System Operator (NBP-SO) along with the NPCC situation awareness team, the grid acrossnortheastern North America remained stable throughout the 2023 Québec wildfires. This collaborative effort
maintained the reliability of the Québec Interconnection and the entire region.
This year’s severity risk index (SRI), extreme days for transmission, and transmission outage severity (TOS) analyses
all indicated that these wildfires had a disproportionately high impact on the BPS. The fires rose in prominence due
to somewhat frequent and brief outages on very high-voltage transmission lines. These analyses highlighted a
deficiency with the current definition of a formula that sums up transmission capacity affected by the outages started
on a given day without consideration for their durations or whether repeat outages occur on the same equipment.
This leads to a systematic overestimation of the contribution of much shorter outages while conversely
underestimating the contribution of longer outages. The PAS is evaluating the calculations to incorporate andadequately account for outage duration.

Utah Solar Photovoltaic (PV) Performance Improvement

On April 10, 2023, at 08:51 Pacific, a single-line-to-ground fault occurred on a 345 kV transmission circuit in thesouthern Nevada/southwest Utah area (see Figure 1.3). The fault was normally cleared in 58 ms. While noconventional generation tripped because of the transmission line outage, supervisory control and data acquisition(SCADA) data for the area showed that aggregate solar PV output dropped significantly. The abnormal active power
reduction for each facility was due to inverters tripping for a variety of causes, including loss of synchronization, ac
overvoltage, and ac overcurrent.
Fifteen solar sites were connected to the system with the majority on 138 kV transmission lines. The total solar loss
was approximately 929 MW, ranging anywhere from 3 MW to 234 MW per site. Most of the generation was
automatically restored within 1–11 minutes and the remainder was manually restored within 120 minutes. A joint
NERC, WECC, and BA investigative team recommended that the plant owners work with their inverter manufacturers
to apply known improvements to ride-through settings.

9 Remedial action schemes are designed to detect abnormal or predetermined system conditions and take corrective actions other than and/orin addition to the isolation of faulted components to maintain system reliability. These schemes are independent of firm load shed reported
through an energy emergency alert.
10 2023 Summer Quarterly Markets Report (iso-ne.com)
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Chapter 1: Major Occurrences and Report Releases for 2023

Figure 1.3: Map of Fault Location and Affected Solar PV Facilities, April 10, 2023, Event
On September 29, 2023, at 14:32:40 Pacific, a trip with no reclosing occurred on another 345 kV transmission circuitin southern Utah due to a line-to-line fault that lasted approximately 66 ms and was cleared as intended. At the sametime, roughly 537 MW of solar generation (about 90% of which was from the same facilities involved in the April 10,
2023, event) experienced a sudden cessation of generation output while remaining connected to the grid. All but 5.3
MW of generation were restored within seven minutes.
After the April 10, 2023, event, the Generator Owners (GOs) of some of the larger facilities worked with their inverter
manufacturers to set the inverters to not trip on the same behaviors seen during that event. These changes allowed
their IBR generation to reduce active power injection but not trip, resulting in significantly improved recovery timesof two to three minutes. GOs also provided updated models to the Transmission Planner for all but two of the sites.
Although these IBR facilities exhibited improved performance, recovery time still has room to improve. The
investigative team is working with the inverter manufacturers and the GOs to identify the settings that need to bealtered to optimize performance.

Winter Storm Elliott Report

In November 2023, FERC and the ERO Enterprise released a 167-page report on Winter Storm Elliott, 11 the late
December 2022 storm that contributed to power outages for millions of electricity customers in the eastern half of
the United States. During this extreme cold weather event, over 90,000 MW of coincident unplanned generation
outages occurred that rendered 18% of the U.S. portion of anticipated resources in the Eastern Interconnection
unavailable along with generation already on outage at that time. 12 As temperatures rapidly decreased across theevent area and electricity demand correspondingly increased, balancing area operators in SERC-East and SERCCentral were faced with energy deficiencies that required 5,400 MW of firm load shed to maintain system balance,
the largest controlled firm load shed recorded in the history of the Eastern Interconnection (see Figure 1.4). 13

11 Winter Storm Elliott Report: Inquiry into Bulk-Power System Operations During December 2022
12 FERC/NERC/RE WS Elliott Report at 18.
13 FERC/NERC/RE WS Elliott Report at 6.

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Chapter 1: Major Occurrences and Report Releases for 2023

Figure 1.4: Bulk Electric System Map of Entities in the U.S. Eastern Interconnection Affectedby Winter Storm Elliott
During the 2022 event, domestic U.S.
natural gas production experienced its
greatest decline since 2021’s WinterStorm Uri. In the Marcellus and Utica
shale regions, production dropped by
23–54%. Wellhead freeze-offs, thefreezing of other natural gas supply chain
equipment, and weather-related poorroad conditions
that
prevented
necessary maintenance were reported
as the top causes. 14 The combination of
reduced natural gas production andrecord consumption 15 forced somepipelines in the event area to declare
force majeure and curtail deliveries evento firm gas transportation customers.
While natural gas availability anddelivery issues accounted for 20% of
unplanned generating unit MW outages,
mechanical/electrical issues comprised
41% and freezing issues comprised
31% 16 (see Figure 1.5). 17

Figure 1.5: Incremental Unplanned Generating Unit MW
Outages, Derates, and Failures to Start; Winter Storm
Elliott Event Area by Cause

14 FERC/NERC/RE WS Elliott Report at 19.

15 FERC/NERC/RE WS Elliott Report at 112.

16

“Natural Gas Fuel Issues include the combined effects of decreased natural gas production; cold weather impacts and mechanical problems
at production, gathering, processing and pipeline facilities resulting in gas quality issues and low pipeline pressure; supply and transportationinterruptions; curtailments and failure to comply with contractual obligations. Additionally, it includes shippers’ inability to procure natural gas
due to tight supply, prohibitive, scarcity-induced market prices, or mismatches between the timing of the natural gas and energy markets.”(Footnote 58 of FERC/NERC/RE WS Elliott Report)
17 FERC/NERC/RE WS Elliott Report Fig 7.
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Chapter 1: Major Occurrences and Report Releases for 2023

CAISO Battery Energy Storage System (BESS) Disturbance Report 18
On March 9 (Figure 1.6) and April 6, 2022
(Figure 1.7), the Southern California area
experienced normally cleared transmission
faults of less than 5 cycles, resulting in solar
PV and BESS generation losses. The March 9
fault was due to a circuit breaker failure on a
694 MW natural gas unit; it cleared in 4.5
cycles and led to 1,102 MW of generation
loss: a 694 MW natural gas unit, initiating theloss of 124 MW BESS and 284 MW of other
IBRs. The second fault cleared in about 4cycles on April 6 and led to about 500 MW ofgeneration loss and all IBRs.

The March 9 event is unique in that it
occurred after sunset with no solar resources
on-line. It was noted that, in this event, “mostof the affected BESS facilities were located in
the vicinity of solar PV facilities.” Of the 1,102
MW of generation lost in this event, 124 MW
was attributed to BESS and the remainder tosynchronous generation.

Figure 1.6: Map of the Fault Location and Affected
IBR Facilities, March 9, 2022

A single phase-to-ground fault on a 220 kV bus
caused the April 6 event at 15:06 Pacific. In
this event, 498 MW of IBRs were lost. Becauseof poor or no metering at the BESS facilities,
the report was not able to indicate the exact
MW impact of the BESS lost. None of the
facilities involved in these two events met
CAISO’s 10 ms data resolution requirement,
making it difficult or impossible to verify the
behavior of the plants during the disturbance.

Figure 1.7: Map of the Fault Location and Affected
IBR Facilities, April 6, 2022

The causes and problems that have been traditionally seen in IBR events within the Western Interconnection wereseen in these events as well. Key observations and recommendations from the report are as follows:•

BESS may have the same system performance problems as solar PV resources.

•

BESS ride-through performance is not adequately assessed during the interconnection process.

•Poor commissioning practices are a significant contributor to the unreliable performance of IBRs.

•

NERC will be conducting a model quality assessment of this event and subsequently issue an alert as needed.

•

Inadequate monitoring hinders performance and event analysis.

Based on the analysis of the events, including a finding that the affected entities did not meet the performancerequirements of the Generator Interconnection Agreement, CAISO worked with affected GOs to develop andimplement mitigation plans to eliminate the unexpected causes of tripping and make changes to recording
capabilities to meet the Interconnection agreement requirements.
18 2022 California Battery Energy Storage System Disturbances

NERC | State of Reliability | 2024
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: Severe Risks, Impact, and Resilience
This chapter identifies and examines the highest-stress days on the BPS in 2023 using established measures.

Severity Risk Index 19

The SRI provides a quantitative measure that assesses the relative severity of the combined impact of load,
generation, and transmission loss on the BPS daily and offers a comprehensive picture of the performance of the BPS,
allowing NERC to assess year-on-year reliability trends. For 2023, load-loss data voluntarily reported to the IEEE
Distribution Reliability Working Group was used to estimate the daily load-loss component; generation andtransmission components are calculated from data collected by NERC.
By comparing the daily SRI scores in descending order for each of the past five years, the overall performance of the
BPS can be evaluated (see Figure 2.1). The inset chart in the upper right of Figure 2.1 provides a detailed comparisonof the top 10 SRI days for each year. The annual cumulative SRI shown in Table 2.1 sums each day’s SRI for the year
by component. Three of these cumulative measures for 2023 were the lowest in the past five years (Cumulative
Weighted Load Loss, Annual Cumulative SRI, and Average Daily SRI) and Cumulative Weighted Generation was thesecond lowest.
The cumulative performance of the BPS is calculated by summing each day’s SRI for the year. Table 2.1 and Figure
2.1 show the annual cumulative SRI for the five-year period of 2019–2023.

Figure 2.1: NERC Descending SRI by Day of the Year
19 Severity Risk Index

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Chapter 2: Severe Risks, Impact, and Resilience

Year
2019
2020
2021
2022
2023

Table 2.1: Annual Cumulative SRI
Cumulative Cumulative Cumulative
AnnualAverage
Weighted
Weighted
Weighted Cumulative
Daily
Generation Transmission Load Loss
SRI
SRI
368.9
67.4
57.0
493.3
1.35
339.0
67.7
72.5
479.2
1.31
375.8
65.3
152.1
593.2
1.63
404.2
61.1
55.2
520.4
1.43
356.8
65.9
53.2
475.9
1.30

Figure 2.2 plots the daily SRI scores for 2023 against control limits that were calculated by using 2019–2022 seasonal
daily performance and identifies the 10 highest SRI days. A general normal range of performance is represented by
the gray-colored band, showing the daily seasonal 90% control limits. 20 Days that extend above the seasonal control
limit indicate irregularities for the season but may not have a high enough SRI to rank in the top 10.

Figure 2.2: 2023 Daily SRI with Top 10 Days Labeled, 90% Confidence Interval
Table 2.2 details the scores for the top 10 SRI days during 2023. The table identifies where atypical weather conditions
were ongoing during the day and the general location by Regional Entity. Four of the top 10 SRI days in 2023 were
driven by relatively short high-voltage transmission outages resulting from the wildfires in Québec. As noted in otherareas of this report, although the wildfires did have some impact on reliability, they have disproportionately increasedtransmission indicators. Five of the six remaining top days were coincident with major thunderstorms, leading tohigher load loss than usual. Due to the relatively calm weather in 2023, the final remaining day was a result of several
coincident large fossil generator outages.

20 The shaded area reflects the 90% confidence interval (CI) of the historic values between the 5th and 95th percentiles.

NERC | State of Reliability | 2024
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Chapter 2: Severe Risks, Impact, and Resilience

Table 2.2: 2023 Top 10 SRI Days
SRI and Weighted Components 2023
Atypical Weather
Weighted
Weighted
Weighted
Conditions
SRI
Generation Transmission Load Loss
Widespread storms and
4.32
1.10
0.45
2.77
tornadoes

MRO, RF,
SERC

Regional
Entities

Rank

Date

1

1-Apr

2

22-Jun

3.71

1.39

2.18

0.14 Québec Wildfires

NPCC

3

13-Jul

3.47

1.01

2.18

0.28 Québec Wildfires

NPCC

4

21-Jun

3.40

1.36

1.80

0.24 Québec Wildfires

NPCC

5

3-Mar

3.05

1.40

0.57

1.08 Severe Storms

RF, SERC,
Texas RE

6

1-Jun

2.74

1.78

0.77

0.19 Québec Wildfires

NPCC

7

25-Mar

2.46

0.71

0.30

1.46 Widespread storms

RF, SERC

8

18-Dec

2.45

1.26

0.15

9

1-Jul

2.31

1.68

0.51

10

3-Feb

2.28

2.00

0.14

East Coast thunderstorms
1.04 and coincident generation
outagesThree high-voltage lines
0.12 out < 30 minutes due tolightning
Coincident large coal and
0.15
gas generator outages

NPCC,
SERC
NPCC
N/A

SRI Performance Trends
To put the severity of days in 2023 into context with historic BPS performance, the top 10 days over the five-year
period are updated annually. Table 2.3 identifies the top 10 SRI days occurring for 2019–2023 with the contributionof the generation, transmission, and load-loss components to the SRI for each day; contributing event information;and the Regional Entities impacted by the event. Only April 1, 2023, was severe enough to be added to the top 10 SRI
days of the past five years.
Table 2.3: 2019–2023 Top 10 SRI Days
SRI and Weighted Components
Weighted
Weighted
Weighted
SRI
Generation Transmission Load Loss

Rank

Date

1

February 15, 2021

61.35

5.54

0.79

55.02

2

February 16, 2021

18.34

5.02

0.54

12.78

3

February 17, 2021

12.04

2.49

0.29

9.26

4

December 23, 2022

11.28

8.17

0.86

2.26

5

December 24, 2022

7.46

6.44

0.97

0.05

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14

Atypical
Weather
Conditions
Cold Weather
Event
Cold Weather
Event
Cold Weather
Event
Winter Storm
Elliott
Winter Storm
Elliott

Regional
EntityMRO, RF,
SERC, TRE
MRO, RF,
SERC, TRE
MRO, RF,
SERC, TRE
All
All

Chapter 2: Severe Risks, Impact, and Resilience

Table 2.3: 2019–2023 Top 10 SRI Days
SRI and Weighted Components
Weighted
Weighted
Weighted
SRI
Generation Transmission Load Loss

Rank

Date

6

February 18, 2021

5.83

2.20

0.33

3.30

7

February 14, 2021

4.59

1.91

0.86

1.83

8

June 14, 2022

4.47

1.52

0.39

2.57

9

April 1, 2023

4.32

1.10

0.45

2.77

10

August 27, 2020

4.06

1.52

0.94

1.60

Atypical
Weather
Conditions
Cold Weather
Event
Cold Weather
Event
High
Temperatures
and Derecho
Hurricane
Florence
Winter Storm
Riley

Major Weather Events

Regional
EntityMRO, RF,
SERC, TRE
MRO, RF,
SERC, TRE
MRO,
NPCC, RF,
SERC, TRE
SERC
NPCC

The typical major weather systems that have been analyzed for 2023, such as severe thunderstorms, hurricanes,
tornadoes, and winter storms, had less of an impact on the BPS than seen in the past. Six of the 28 events highlighted
in Figure 2.3 21 were identified as large transmission events in the resilience analysis. By far the largest natural disasterevent that impacted the BPS transmission metrics was the Québec wildfires; however, the impact of this event does
not align with the metrics (see Major Occurrences, Resilience Curves, and TADS Reliability Indicators sections).

Figure 2.3: 2023 U.S. Billion-Dollar Weather and Climate Disasters 22
21

NOAA National Centers for Environmental Information (NCEI) U.S. Billion-Dollar Weather and Climate Disasters(2023). https://https://www.ncei.noaa.gov/access/billions/, DOI: 10.25921/stkw-7w73
22
NOAA National Centers for Environmental Information (NCEI) U.S. Billion-Dollar Weather and Climate Disasters(2023). https://https://www.ncei.noaa.gov/access/billions/, DOI: 10.25921/stkw-7w73
NERC | State of Reliability | 2024
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Chapter 2: Severe Risks, Impact, and Resilience

Impact of Extreme Event Days
Extreme Event Days
Extreme event days are identified as event days above the 95th percentile upper bound relative to the past four
years’ severity measures for any season within North America or a specified Interconnection. This analysis expandson the transmission and generation components that contribute to the SRI reported in the previous SRI Performance
Trends section to explore the causes of the extreme days.
The impacts of extreme days on BPS resources are characterized by the amount of transmission or generation
reporting immediate forced outages or derates starting on a given day. By analyzing the impact and causes of extreme
event days, it is possible to identify which conditions pose the highest risk to the BPS. While this analysis does notaddress every potential scenario, learning from performance during extreme events helps provide insight into how
the system may respond to a range of conditions and events.
Extreme-day outages for transmission and generation by Interconnection are presented in Appendix A, Supplemental
Analysis by Interconnection. 23 The analysis provided in the following subsections is reported separately fortransmission and generation. The total estimated MVA transfer capacity 24 reported in TADS or net maximum capacity
reported to GADS for all Regional Entities or by Interconnection is shown at the top of each figure in this chapter.

Transm ission I m pacted

In 2023, 22 days met the criteria of extreme transmission days for the BPS as compared to 11 in 2022. Of the 22
extreme days in 2023, 14 were associated with the Québec wildfires. The most extreme transmission-impacting day
was June 22, primarily due to the Québec wildfires (see Figure 2.4), followed closely by July 13, also due to the Québec
wildfires. On these days, the potential MVA capacity impacted due to automatic transmission outages was 10.4 times
as high as the associated season’s average.

Figure 2.4: 2023 Transmission Outages during Extreme Days
23 For extreme day Interconnection-level analysis, the Québec Interconnection is included in the analysis labeled as Eastern Interconnection–

Québec Interconnection.

24 Severity Risk Index

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Chapter 2: Severe Risks, Impact, and Resilience

The top causes reported for outages that occurred on extreme days are shown in rank order for North America andeach Interconnection (Table 2.4).
Table 2.4: Top Transmission Initiating Outage Causes on Extreme Days
Ranked by MVA Capacity
Area
Cause #1
Cause #2
Cause #3
Cause #4
Cause #5
Fire

Weather(Excluding
Lightning)

Lightning

Failed AC Circuit
Equipment

Unknown(568,311)(112,908)(59,365)(32,329)(31,075)

Fire

Weather(Excluding
Lightning)

Lightning

Failed AC Circuit
Equipment

FailedProtection
SystemEquipment(568,392)(91,274)(49,745)(31,732)(29,606)

Weather(Excluding
Lightning)

Lightning

Failed AC Circuit
Equipment

Unknown

Other(55,125)(27,487)(18,963)(6,895)(5,952)

Weather(Excluding
Lightning)

Unknown

Power System
Condition

Lightning

Human Error(24,675)(16,615)(8,739)(8,475)(6,668)All NERC
Regional Entities

Eastern–Québec
Interconnections

Texas
Interconnection

Western
Interconnection

Conventional Generation I m pacted

Based on analysis of GADS data, a total of 14 days in 2023 qualified as extreme for North America’s BPS (see Figure2.5) compared to 22 in 2022. The two highest-impact days for generation loss were July 27 (severe storms) andFebruary 3 (winter storm). On these days, conventional generating units experienced outages that were 1.8–1.9 times
as severe as the associated season’s average. Two of the extreme generation loss days coincided with extreme days
identified for transmission (early February winter storms and June 1). The days on which generation outages wereslightly above the seasonal bounds (red line) do not have a specific cause listed and have been investigated; theyeither coincided with severe thunderstorms (i.e., May 8, June 1, June 12, and July 27) or saw many coincident outages
that were not a result of adverse weather conditions.

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Chapter 2: Severe Risks, Impact, and Resilience

Figure 2.5: 2023 Generation Impacted during Extreme Days
The top causes reported for outages that occurred on extreme days are shown in rank order for North America andeach Interconnection (Table 2.5).

Area

Table 2.5: Top Generation Outage Causes on Extreme Days
Ranked by Unavailable Net Maximum Capacity
Cause #1
Cause #2
Cause #3
Cause #4
Electrical

Fuel, Ignition,
and Combustion
Systems

Auxiliary
Systems

Boiler Tube
Leaks

Controls(17,851)(14,130)(13,876)(13,008)(11,341)

Fuel, Ignition,
and Combustion
Systems

Boiler Tube
Leaks

Electrical

Auxiliary
Systems

Lack of Fuel
(Hydro, gas,coal)

(11,086)(10,758)(9,073)(7,126)(6,746)

Electrical

Controls

Boiler Tube
Leaks

Fuel, Ignition,
and Combustion
Systems

Boiler Piping
System(5,784)(4,933)(4,868)(4,471)(4,444)

Feedwater
SystemElectrical

Fuel, Ignition,
and Combustion
Systems

Controls

Condensing
System(2,136)(1,579)(1,470)(1,397)(1,373)

All Regional
Entities

Eastern–Québec
Interconnections

Texas
Interconnection

Western
Interconnection

Cause #5

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Chapter 2: Severe Risks, Impact, and Resilience

Analysis of Transmission System Resilience

The analysis of large transmission events evaluates transmission outages related to severe weather events thatinvolve 20 or more automatic outages. Outage and restoration processes for transmission elements are analyzed, notthe disruption and restoration of distribution customer load. Restoration of the transmission system to serve
customer load is always the priority.
The analysis of the 2023 transmission outages identified 11 large transmission events that were caused by weather
and quantified the resilience and restoration statistics for them. The resilience statistics enable the measurement
and tracking of some abilities of the transmission system to withstand, adapt, protect against, and recover during
and after major weather events. 25
This section provides a detailed description of the March 31 winter storm and tornado event as the largest outage
event on the transmission system in 2023 and the Québec wildfires as a composite event due to the impact on othertransmission metrics. Multiyear statistics by associated weather type and changes in the severity and duration ofthese events as measured by the number of transmission outages reported for each cause are compared for two fiveyear periods: 2018–2022 and 2019–2023.
TADS Outage Grouping and 2023 Large Weather Events
The outage grouping algorithm 26 considers automatic outages reported in TADS based on Interconnection andassociated start and end times. The resulting transmission outage events are determined to be weather-related if at
least one outage in the event is initiated or sustained by one of the following TADS cause codes: Weather (excluding
lighting), Lightning, Fire, or Environmental. The procedure produces groupings of outages that are further reviewed
and compared with the weather information from external sources to confirm or refine the events. The TADS data
was supplemented by Velocity Suite as a source to identify utility company footprints, and weather sources like
National Oceanic and Atmosphere Administration (NOAA) and Ventusky were used to visualize the weather events.
Matching the data from these sources provides a much clearer picture of outages within the event. This combinationof automatic and manual procedures results in a set of transmission events that can cross boundaries of different
utilities and Regional Entities to capture significant events caused by major weather occurrences, such as hurricanes
and severe winter storms.
Table 2.6 lists these events in chronological order and shows the severe weather type for each event with statistics
that quantify the impact of the event on the transmission system. In 2023, the largest event was the Québec wildfire
composite event with 180 outages between June 20 and July 16, which consisted of 101 small non-overlapping eventsand as such was not captured by the algorithm as one single event. The combination of all events affected 600,635
of MVA capacity. This composite event is shown in blue in Table 2.6.
The second largest event, the March 31 winter storm/tornado event (with 119 transmission outages reported),
occurred in the Eastern Interconnection, shown in red in Table 2.6. In terms of impact to the overall system, theFebruary 1 ERCOT winter storm event had the highest transmission capacity affected (48,761 MVA out) for any single
event in 2023. The two events taking place on June 25 were reported as two separate events due to the large time
gap and geographical distance between them.

Resilience Framework, Methods, and Metrics for the Electricity Sector | IEEE Power & Energy Society Resource Center (ieeepes.org)
26
Impact of Extreme Weather on North American Transmission System Outages | IEEE Conference Publication | IEEE Xplore
25

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Chapter 2: Severe Risks, Impact, and Resilience

Table 2.6: 2023 Large Transmission Weather-Related Events

All Automatic

Sustained Automatic

Momentary Auto.

Interconnection

Extreme/Severe
Weather Event

Transmission Capacity
Affected(MVA)

Miles Affected

Final Restoration
Duration (Days)

Element-Days 27 Lost

Most Simultaneous
Unavailable Capacity (MVA)

Event Outage
Count

February 1

66

61

5 TexasWinter Storm, Ice

48,105

1,270

61.5

115

35,593

March 388

75

13 Eastern

Severe / HighWinds

39,100

2,609

5.6

50

13,676

March 25

29

23

6 Eastern

Thunderstorm

16,401

920

2.3

15

4,706

March 31

119

99

20 Eastern

47,097

3,091

22.8

164

16,788June 158572

13 Eastern

26,747

2,034

11.3

127

14,388June 1832

29

3 Eastern

9,406

859

9

60

6,620

June 20July 14

180

143

37 Québec

600,635

25,710N/A

917,482June 2522

19

3 Eastern

5,038

587

6.9

29

3,121

June 25

21

19

2 Eastern

6,472

503

2.2

10

3,686

June 2958

50

8 Eastern

23,781

1,520

11.7

51

10,983

July 2052

42

10 Eastern

18,147

1,365

4.9

33

7,055

August 30

58

56

2 Eastern

15,170

1,439

9.2

106

11,132

Event Start

Winter Storm,
TornadoesThunderstorm,
TornadoesThunderstorm,
Tornadoes
Wildfires(composite event)South Central
Thunderstorm,
TornadoesThunderstorms
Derecho,Thunderstorms
Thunderstorm,
High Winds
Hurricane Idalia

27The definition for element-days is provided in Appendix B of the NERC 2022 SOR.

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Chapter 2: Severe Risks, Impact, and Resilience

Outage, R estore, and Perform ance Curves

Table 2.6 illustrates the variability in event sizes andduration. However, these statistics do not completely
explain what happened during the events; theoutage, restore, and performance curves of theevents provide more details on how he events
unfolded. 28 Figure 2.6 serves as an example todescribe transmission outages during an event.
These curves track the number of elements out or the
MVA transmission capacity impact on the verticalaxis versus time on the horizontal axis.
The outage curve is the cumulative number of
elements or cumulative equivalent MVA capacity
impact at the time shown on the horizontal axis.
The restore curve is the cumulative number of
elements restored or cumulative equivalent MVA
restored at the time shown on the horizontal axis.

Figure 2.6: Example of Outage, Restore, andPerformance Curves for a Large Transmission
Outage Event

Lastly, the performance curve is the number of
elements or equivalent MVA capacity impact out simultaneously at the time shown on the horizontal axis. The value
is equal to elements or MVA capacity restored minus the elements or MVA capacity (i.e., the performance curve isthe restore curve minus the outage curve). The performance curve combines information on degradation andrecovery during the event.
The curves enable the calculation of several resilience metrics. 29 These metrics help quantify the abilities of a resilient
power system to effectively absorb, withstand, adapt, protect against major weather events (event size, outage
process duration and outage rate, time to first restore, the most degraded state in the event, the total element-daysand MVA capacity-days lost), and recover from and reduce the durations and impacts of major weather events (event
duration, time to first restore, time to substantial restoration, instantaneous restore rate).
Resilience Curves and Statistics for Two Largest Transmission Events in 2023

Québec W ildfires (June 20–July 14, 2023)

The Québec wildfire outages were combined into one composite event that consisted of 101 non-overlapping small
outage events that are grouped together to better assess the overall impact between June 20 and July 26, 2023.
These small events together contained 180 automatic outages. It should be noted that the creation of this composite
event is only possible due to the specificity of the “Fire” cause code. With current data, it would be impossible toperform a similar, accurate methodology for other types of weather, making for limited comparability.
Out of the 180 outages, 37 were momentary (< 1 minute) and the remaining were sustained. The event included 11
dc circuit outages and 169 ac circuit outages. A total of 180 automatic outages occurred on 2 distinct dc circuits and
26 distinct ac circuits. The affected dc circuits were from the 400–499 kV voltage class and the ac circuits from the
300–399 kV and 600–799 kV voltage classes. Because of the high voltages and large estimated MVA capacity of thedc and ac circuits and because the wildfires were considered as one composite event, the total affected transmission
capacity summed up to 600,635 MVA. Outage durations were short (1.2 hours on average) and generally notoverlapping, reducing the simultaneous stress on the transmission system. The total duration analyzed from the first
outage to final restoration was 26.1 days. The element- and MVA-based performance curves for the Québec wildfires
28 S. Ekisheva, I. Dobson, R. Rieder, and J. Norris, “Assessing transmission resilience during extreme weather with outage and restore

processes,” 2022 17th International Conference on Probabilistic Methods Applied to Power Systems

29 Resilience statistics are defined in Appendix B in the 2022 SOR.

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Chapter 2: Severe Risks, Impact, and Resilience

composite event are shown in Figure 2.7 and Figure 2.8, respectively. The outage and restore curves for thecomposite event are not shown because they do not provide valuable information since regular resilience statistics
cannot be properly applied.

Figure 2.7: Transmission Element-Based Performance Curve for Québec Wildfire Event, June
20–July 14, 2023

Figure 2.8: Transmission Capacity (MVA-Based) Performance Curve for Québec Wildfire
Event, June 20–July 14, 2023

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Chapter 2: Severe Risks, Impact, and Resilience

The maximum simultaneous loss of potential transmission capacity was greater than that of the EasternInterconnection winter storm and tornado event, 17,482 MVA vs. 16,788 MVA, respectively. The elements’ highvoltages resulted in a significant total loss of 29,492 MVA-days compared to only nine element-days lost. This ratio
of 3,276:1 is roughly nine times the average ratio of 363:1, clearly demonstrating how these outages
disproportionately impact transmission calculations that do not account for duration.

W inter Storm and Tornado Event (M arch 31–April 23, 2023)

Table 2.6 indicates that the events with a combination of weather types significantly impacted the transmission
system in 2023. The largest non-composite transmission outage event in 2023 was the winter storm and tornado
event that started in the Eastern Interconnection on March 31, 2023, in terms of the number of element outages.
This weather event was also recorded by NOAA as one of the billion-dollar weather disasters of 2023 (see Figure 2.3).
It involved a series of strong storms containing high winds, heavy rain, and multiple tornadoes across the Mississippi,
Tennessee, and Ohio Valleys and into the Mid-Atlantic and Northeast on Friday and Saturday, March 31, and April 1.
At the storm’s peak, EAGLE-I 30 indicated approximately 1.1 million distribution outages between Arkansas and New
York; 268,000 in Pennsylvania; 237,000 in Ohio; and 99,000 in Tennessee.
The event caused 119 automatic transmission outages reported by 36 Transmission Owners; 20 out of the 119
outages were momentary (< 1 minute), and the remaining were sustained. The event included five transformer
outages and 114 ac circuit outages with more than 3,090 ac circuit miles affected, totaling 47,097 MVA capacity. The
event had a duration of 22.8 days, second only to the ERCOT winter transmission outage event that lasted 61.5 days.
The element- and MVA-based curves for the winter storm are shown in Figure 2.9 and Figure 2.10, respectively. The
curves are condensed with the gray area representing the time between April 11, 2023, 15:55 UTC and April 22, 2023,
0:00 UTC.

Figure 2.9: Transmission Element Outage, Restore, and Performance Curves for WinterStorm/Tornado Event, March 31–April 23, 2023

30 EAGLE-I is an interactive geographic information system (GIS) that allows users to view and map the nation's energy infrastructure and obtainnear real-time informational updates concerning the electricity, petroleum, and natural gas sectors within one visualization platform.
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Chapter 2: Severe Risks, Impact, and Resilience

Figure 2.10: Transmission Capacity (MVA-Based) Outage, Restore, and Performance Curves
for Winter Storm/Tornado Event, March 31–April 23, 2023
The large transmission outage event started with a series of ac circuit momentary outages due to galloping causedby the winter storm. During this transmission event, four distinct ac circuits followed the same scenario: a line had
several momentary outages in close succession due to galloping followed by a sustained outage with a multiday
duration. Due to the multiple outages of the same ac circuit, a total of 119 automatic outages occurred on 111 distinct
transmission elements. The orange outage curves in Figure 2.9 and Figure 2.10 show that an outage process lasted
35 hours with the outages accumulating at the average rate of 3.4 outages per hour (1,359 MVA capacity per hour).
The restore process, shown in Figure 2.9 and Figure 2.10 by green curves, started immediately due to a momentary
outage with the earliest sustained restore occurring in 10 minutes. It then followed the usual pattern for most large
events. 31 The maximum number of elements (55) and MVA capacity (16,788) simultaneously out, shown by the nadirof the respective blue performance curves, was reached approximately 28 hours into the event, and the systemremained in this most degraded state for six minutes. Unlike the outage process, the restore process did not occur at
a constant rate, rather its rate decreased over the event duration. Using a log-normal fitted curve for the restore
process, 32 the maximum instantaneous restore rate was 1.8 restores per hour, which was reached 13.7 hours into
the event. At the time point when half of sustained outages were restored, the rate was 1.3 restores per hour, and it
was only 0.07 restores per hour at the 95% element restoration level. The substantial restoration level when 95% of
outages were restored was reached in 167.5 hours, or 31% of the event duration. The substantial restoration fortransmission capacity (MVA) happened faster, 148.1 hours, or 27% of the event duration. The total loss for the event,calculated as the area between a blue performance curve and the time axis, was 164 element-days lost (Figure 2.9)
and 62,675 MVA-days lost (Figure 2.10).
31 S. Ekisheva, I. Dobson, R. Rieder, and J. Norris, “Assessing transmission resilience during extreme weather with outage and restore

processes,” 2022 17th International Conference on Probabilistic Methods Applied to Power Systems.

32 S. Ekisheva, D. K. Pratt, M. Kachadurian, W. G. Martin, J. Norris, and I. Dobson, “Grid Restoration after Extreme Weather Events,” 2023 IEEEPES Innovative Smart Grid Technologies Europe (ISGT) Conference.

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Chapter 2: Severe Risks, Impact, and Resilience

The last unrestored outage in the event was 22.4 days, likely due to extensive damage of the 300–399 kV ac circuit.
This is typical for large transmission events when few remaining elements are out either due to the inaccessibility ofa portion of the line or a damaged structure or equipment. In some cases, this is attributable to a utility postponing
the restoration of a single remaining element (or a few elements) after all other outages in the large event are
restored because this outaged element is considered not critical for grid reliability. 33

Transmission System Resilience Statistics by Associated Weather Type:2019–2023
W eather Types

The outage grouping procedure identified 59 largetransmission events in the years 2019–2023, only one ofwhich was not weather-related (a 2023 contamination
event). 34 The 58 large weather-related events were causedby the weather types listed in Figure 2.11. If several weather
factors were observed together (e.g., hurricane, tornado,
and wind), the dominant cause of transmission outages wasdetermined to be the weather type. Multiple sources (i.e.,
NERC’s daily BPS awareness reports, Velocity Suite, NOAA,
Ventusky, public media reports) were used to determine if aweather event was associated with each large transmission
event.
Figure 2.12 shows selected resilience statistics for the 2019–2023 events by weather type. Hurricanes caused the largest
transmission events with an average size of 154 outages
while other groups had average sizes that ranged from 40–
59 outages. The maximum number of elements
simultaneously out (the most degraded state in an event as
indicated by the nadir of the performance curve) equals 60%of the event size on average.

Figure 2.11: Weather Types of Large
Transmission Events, 2019–2023

33 S. Ekisheva, I. Dobson, R. Rieder, and J. Norris, “Assessing transmission resilience during extreme weather with outage and restore

processes,” 2022 17th International Conference on Probabilistic Methods Applied to Power Systems.

34 A 2023 large event in SERC with 30 outages caused by bird contamination; the event duration was 2.5 days.

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Chapter 2: Severe Risks, Impact, and Resilience

Figure 2.12: Resilience Statistics for 2019–2023 Large Weather-Related Events
Figure 2.13 compares the average event duration with the average substantial restoration duration (the time torestore 95% of outages and 95% of MVA capacity) and shows the time to first restore. The one fire event (2020 WECC
wildfires) had a duration of 87 days, thus having a greater impact on this statistic due to the small group size. For
other groups, the event duration is positively correlated with the event size. For all weather types, the time to restore
95% of outages (the substantial restoration level) is much shorter than the total event duration (on average, from
35% of the event duration for hurricanes to 52% of the event duration for tornadoes and thunderstorm, wind). The
time to reach a restoration level of 95% MVA ranges from 29% of an event’s duration for hurricanes to 63% fortornadoes. The first restore typically occurs inside one hour from the event start; hurricane events have the shortest
average time to the first restore (34 minutes) among all groups. This indicates effective advanced preparation by
utilities for these forecasted events. This is down two minutes from the 2017–2022 statistic calculated in the 2022
SOR report, indicating that fast response to hurricanes is consistent.

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Chapter 2: Severe Risks, Impact, and Resilience

Figure 2.13: Average Event Duration vs. Average Sustained Restoration Duration
Event duration is a straightforward metric but is too highly variable to be a reliable estimate. Moreover, it depends
strongly on the last few restores, making the event duration relate poorly to transmission performance because theselast restores may be unimportant for customers or may be excessively delayed by factors out of the utility’s control,
such as the difficulty of repairing transmission lines in the mountains in the winter or structural damage caused byhurricane or tornado. 35 The substantial restoration duration is a preferable metric to measure and track the ability ofthe transmission system to recover from outage events caused by major weather systems.

Changes in R esilience Statistics: 2019–2023 Events vs. 2018–2022 Events

To draw conclusions about improving, stable, or declining transmission resilience against weather, the analysis
focuses on capturing changes in the several metrics that quantify resilience over years. The resilience statistics arecalculated for large weather-related events for the years 2018–2022 and 2019–2023, and changes in the metrics byweather types were analyzed. The five-year period is selected due to the small annual number of events in somegroups (e.g., Fire).
The bubble chart in Figure 2.14 shows the groups of large weather-related transmission events by weather type; thefive patterned bubbles correspond to the groups for combined 2018–2022 data, and the five solid-colored bubbles
show the same groups for combined 2019–2023 data. The size of a bubble represents the group size. The X-axis of abubble center shows the average time to restore 95% of outages for the events in this group; the Y-axis shows theaverage number of outages for the events. The bubble color indicates the average MVA-day loss for each group:
below 30,000 MVA-days is shown in blue, between 30,000 and 100,000 MVA-days is shown in yellow, and above
100,000 MVA-days is shown in orange.
Change in size or position of a bubble for the same weather type in Figure 2.14 indicates changes in the impact ofthat weather resulting from a combination of the weather frequency and severity and improved or declined resilience
performance. There was a decrease in the number of events in all categories as reflected by the bubble sizes in Figure
2.14. The average MVA-day loss increased for all weather types due to some of the smaller events falling off from2018, which is highlighted by the change of color for Fire and Winter Weather. The average event size of Hurricanes

How Long is a Resilience Event in a Transmission System?: Metrics and Models Driven by Utility Data | IEEE Journals &Magazine | IEEE Xplore
35

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Chapter 2: Severe Risks, Impact, and Resilience

increased due to the removal of several small hurricanes from 2018. The average MVA-day loss for the Fire category
increased when a short 2018 fire (with approximately 6,000 MVA-day loss) dropped off.
The time to substantial restoration for all extreme weather types combined in 2023 decreased compared with theprevious five years (from 5.3 to 4.3 days for element recovery and from 4.9 to 4.5 days for MVA recovery). Possible
explanations could be improvements in transmission resilience and less severe weather events. Additional years of
the outage data as well as incorporation in the analysis of more detailed weather data are needed for more reliable
inferences.

Figure 2.14: Statistics for Large Transmission Events by Weather Type for 2018–2022 vs.
2019–2023

NERC | State of Reliability | 202428

: Grid Transformation
Resource Adequacy

For this report, two measures of resource adequacy are examined for the Energy Emergency Alerts (EEA) section.
Planning Reserve Margins present a forward-looking perspective on whether sufficient resources are expected to beavailable to meet demand. The EEAs provide details of actual energy emergencies within an Interconnection.
2023 Planning Reserve Margins
Planning Reserve Margins are a long-term resource adequacy indicator. Anticipated Reserve Margin (ARM) expresses
the level of additional resource capacity that an area has above its peak summer (June–September) and winter(December–February) seasonal demand. 36 It is calculated as the difference in anticipated resources and net internal
demand divided by net internal demand and shown as a percentage. 37 Each assessment area’s ARM is comparedagainst its Reference Margin Level (RML)—the threshold margin established by the state, provincial authority,
ISO/regional transmission organization (RTO), or other regulatory body to provide the level of resources needed tomeet reliability criteria (e.g., maintain loss-of-load expectation below 1-day-in-10 years).
In 2023, all assessment areas had adequate ARMs compared to their RMLs (see Figure 3.1; assessment areas aregrouped together based on their peak demand season). This indicates that sufficient resource capacity was plannedfor 2023 to meet established resource adequacy targets. However, risks of electricity supply shortfalls arising fromextreme weather, insufficient generator fuel supplies, or other energy limitations in the resource mix are notgenerally addressed by this traditional resource adequacy criteria.

Figure 3.1: 2023 Peak Season Planning Reserve Margins and Reference Margin Levels 38

36 The peak demand season for an assessment area generally occurs when peak demand is highest or when planning reserves are lowest. For

example, if an assessment area is summer peaking, that area experiences its highest demand levels during the summer months.

37 Anticipated resources include all generating capacity and firm capacity transfers for the assessed summer and winter season. See the 2023

Long-Term Reliability Assessment (LTRA) pp. 126–132 for complete definitions.
38 M-1, Reserve Margin

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Chapter 3: Grid Transformation

2023 Seasonal Energy and Capacity Risk Analysis
The ERO assesses the risk of electricity supply shortfall in seasonal reliability assessments by considering Planning
Reserve Margins, seasonal risk scenarios, and probability-based risk assessments. The expected impact of generator
outages and extreme operating conditions on electricity supply and demand are also considered in NERC’s seasonalreliability assessments. NERC evaluates the availability of supplies to meet normal seasonal peak demand as well as
higher demand that may occur only once per decade, referred to as an extreme or 90/10 demand scenario. Increased
demand, which can be caused by extreme temperatures, higher-than-anticipated generator forced outages, andderates, can create conditions that lead system operators to take emergency operating actions. The maps in Figure
3.2 and Figure 3.3 highlight the assessment areas that NERC identified ahead of the Summer 2023 39 and Winter2023–2024 40 seasons as at risk for resource deficiencies.

Figure 3.2: 2023 Summer Reliability Assessment Risk Area Map

Figure 3.3: 2023–2024 Winter Reliability Assessment Risk Area Map
39 NERC 2023 Summer Reliability Assessment

40 NERC 2023/2024 Winter Reliability Assessment

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Chapter 3: Grid Transformation

2023 Capacity and Energy Performance
Actual operating conditions in 2023 stressed energy supplies to meet demand. In summer, high temperatures,
wildfires, and weather conditions challenged electric grid operators in many parts of North America to maintain areliable supply of electricity. It is noteworthy that, after a summer of soaring temperatures, extended heat waves,and new electricity demand records, few high-level EEAs were issued, and no disruptions occurred because of
inadequate resources. Nonetheless, operators at BAs, TOPs, and RCs faced significant challenges and drew upon
procedures and protocols to obtain all available resources, manage system demand, and ensure the flow ofelectricity over the transmission network. Additionally, load-serving entities and state and local officials in many
parts of North America used mechanisms and public appeals to lower customer demand during periods of strained
supplies. Table 3.1 and the following section describe actual demand and resource levels in comparison with NERC’s
2023 SRA and summarize 2023 resource adequacy events.
Eastern Interconnection–Canada and Québec Interconnection
Systems in parts of Canada experienced challenging conditions early in the summer from high electricity demand
and wildfires over large areas. Electricity transfers from Québec to the neighboring Maritimes and New England werecurtailed or disrupted during periods in May and June, when wildfires affected transmission facilities. Peak electricity
demand in Ontario occurred in early September at a level near the 90/10 demand forecast. Additional imports helped
the area meet the extreme demand.
Manitoba Hydro and SaskPower both experienced peak electricity demand in excess of 90/10 summer forecasts.
Manitoba Hydro’s peak occurred at the start of summer in June. Operators had sufficient reserves and were able toexport supplies during the peak period to neighboring areas.
SaskPower peak electricity demand occurred in late July. A forced outage at a large thermal generator early in thesummer contributed to operating challenges over much of the summer period. At the time of peak demand, forced
outages were significantly higher than typical for summer peak periods.
Eastern Interconnection–United States
In Southwest Power Pool (SPP), summer electricity demand peaked in August and exceeded 90/10 forecasts. At thehour of peak demand, SPP experienced normal levels of forced thermal generation outages. Wind resource
performance at the time of peak demand exceeded seasonal peak forecasts, helping to alleviate the strain on
supplies. However, during periods in June and July, operators at SPP issued resource advisories during periods offorecasted high demand and low or uncertain wind resource output.
Midcontinent Independent System Operator (MISO) also experienced peak electricity demand during the same
period in August; however, demand was between the normal and 90/10 summer peak forecast levels. Wind andsolar resource output at the time of peak demand were below expectations for summer on-peak contributions.
However, forced outages of thermal units were lower than expected. A Level 2 EEA was issued in August due to highforecasted loads and wind uncertainty. MISO used operating procedures to ensure that sufficient reserves weremaintained during periods of high electricity demand and high forced generator outages at times throughout thesummer.
PJM experienced peak electricity demand in late July at a level between normal summer peak and the 90/10 forecast.
Wind and solar resource output were below seasonal peak expectations while low thermal generator outages werereported.
Peak electricity demand at NYISO and ISO-NE occurred in early September and fell below average summer peak
forecasts.
Systems in the U.S. Southeast experienced peak demand above the 90/10 forecasts in mid to late August. Solar
resource output exceeded the expected contributions for the peak demand period. Electricity imports into resourceconstrained areas helped BAs maintain reserves during high-demand periods.
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Chapter 3: Grid Transformation

ERCOT
Extended heat waves led to record-setting system electricity demand in the ERCOT system throughout Summer
2023. Peak electricity demand occurred in mid-August at a level exceeding the 90/10 demand forecast. Simultaneouswith peak demand, wind and solar generation were slightly below expected levels for peak demand periods, andthermal generator outages were also slightly higher than normal for peak periods. Nonetheless, operators were able
to maintain sufficient reserves. At various times throughout the summer, ERCOT issued public appeals forconservation to help manage high-demand periods and periods when output from the solar resources is diminished(e.g., evenings). On September 6, ERCOT declared a Level 2 EEA to address a low-frequency condition on the system
during a period of unusually high demand, declining solar output, and low wind output. Transmission systemconstraints led to the curtailment of some generation from wind resources in southern parts of the system. No load
was shed during the event.
Western Interconnection–Canada
At the start of summer, the province of Alberta was in a state of emergency because of active wildfires and the threatof spreading from hot and dry conditions. A period of high demand from heat and humidity that coincided withgenerator forced outages and low wind conditions triggered an EEA. Alberta’s system peak demand occurred in late
July at a level above normal summer peak demand forecasts but below the 90/10 level. Wind and solar resource
outputs were above seasonal forecast levels for peak demand periods. High temperatures in late August led to highdemand at a time of planned transmission system maintenance. A Level 3 EEA was triggered when low windconditions and insufficient imports resulted in reserve shortage.
The BC-Hydro system also experienced peak electricity demand in early August at a level near the 90/10 summer
peak forecast.
Western Interconnection–United States
The California-Mexico assessment area, which consists of the CAISO, Northern California, and CENACE BAs,
experienced system peak electricity demand in mid-August between the average summer peak demand forecast andthe 90/10 peak demand forecast. Public appeals to shift electricity use to off-peak hours were used during somehigh-demand periods. The Mexico portion of the assessment area faced reserve shortages during periods in July andAugust because of high demand, generator outages, and unavailability of imports.
System peak electricity demand in the U.S. Northwest also occurred in mid-August and was below normal summer
peak demand forecasts.
The U.S. Southwest experienced extended heat conditions and demand levels that exceeded normal summer peakdemand forecasts. Wind and solar output also exceeded the expected levels for peak demand periods.
Table 3.1: 2023 Summer Demand and Generation Summary at Peak Demand
Assessment
Area
MISO
MROManitoba
Hydro
MROSaskPowerMRO-SPPActualPeak
Demand1(MW)

SRA PeakWind –
Wind –
Solar –
Solar –
Demand1
3
1
ActualExpected
ActualExpected3
Scenario2
(MW)
(MW)
(MW)
(MW)
(MW)
116,825
120,781
8,598
5,488
2,096
3,750
123,871
3,060
3,529
83
47
3,390
3,669
56,0483,489
3,633
52,62655,126

381

203

15

8,278

4,500

130

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32

ForcedOutages
Summer4
(MW)
6,638
95
737

378

6,533

Chapter 3: Grid Transformation

Table 3.1: 2023 Summer Demand and Generation Summary at Peak Demand
Assessment
Area
NPCCMaritimes
NPCC-NewEngland
NPCC-NewYork
NPCCOntario
NPCCQuébec

ActualPeak
Demand1(MW)
3,544
23,47530,20623,713
22,531

PJM

147,605

SERC-C44,011

SERC-E

43,307

SERC-FP

54,139SERC-SE45,558

TRE-ERCOT

85,432

WECC-AB

11,522

WECC-BC

9,157

WECCCA/MX

54,130

WECC-NW

57,417

WECC-SW

31,689SRA PeakWind –
Wind –
Solar –
Solar –
Demand1
3
1
ActualExpected Actual
Expected3
Scenario2
(MW)
(MW)
(MW)
(MW)
(MW)
3,284
131
255
40
3,625
24,664
186
186
145
1,163
26,47930,823223
331
84
32,65721,752
786
771
200
126
23,731
22,859496
822,859141,771
1,278
1,688
1,826
2,984
162,666
40,313
15
564
673
511
42,96742,8813,032
1,473
45,60649,297
4,590
4,534
52,416
44,1172,781
4,647
44,83478,927
9,557
10,293
10,431
12,50982,316
11,206
906
309
894
763
11,596
8,636
373
137
0
1
9,234
55,494
1,074
1,111
6,930
14,48967,34465,328
2,137
593
3,821
1,411
71,956
25,612
835
3,968
1,731
5,062
27,992ForcedOutages
Summer4(MW)
1,690*
1,969
9,716
3,419*
12,287*
8,020
1,225
2,129
1,610
2,334
6,699
2,444
4,855
2,507

Table Notes:
1
Actual demand, wind, and solar values for the hour of peak demand in U.S. areas were obtained fromEnergy Information Agency (EIA) Form 930 data. For areas in Canada, this data was provided to NERC bysystem operators and utilities.
2
See NERC 2024 SRA demand scenarios for each assessment area (pp. 14–33). Values represent thenormal summer peak demand forecast and an extreme peak demand forecast that represents a 90/10,
or once-per-decade, peak demand. Some areas use other basis for extreme peak demand.
3
Expected values of wind and solar resources from the 2023 SRA.
4
Values from NERC Generator Availability Data System or provided by NERC entities for the 2023
summer hour of peak demand in each assessment area. Values marked with * include both planned andforced outages.

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Chapter 3: Grid Transformation

Operators issued Level 3 EEAs over five periods during the summer months because of projected reserve deficiencies
from insufficient electricity supplies to meet forecasted demand. Table 3.2 provides an overview of resource andenergy adequacy EEAs. This count of EEAs excludes events that resulted from transmission outages or storm damage
to transmission.
Table 3.2: 2023 Resource and Energy EEA-3 Summary
Date (2023)

June 7 and 12

July 26
July 31–August 4,
and August 14

Regional
EntityMRO
WECC(CanadaAssessment
Areas)WECC(MexicoArea)
MRO(Canadian
Assessment
Area)

August 16

WECC(MexicoArea)

August 28–29

WECC(CanadaAssessment
Area)

EEA Description
Heat and humidity contributed to high demand andthermal generator outages and derates. Low windconditions caused wind resource output to be below
seasonal norms. Some interruptible load was affected,
but no firm load was shed.
High electricity demand, generator outages within thearea, and transmission system congestion resulted ina reserve shortage. No load shed.
Thermal generator outages and low wind conditions
resulted in insufficient reserves during forecasted
peak demand; periods of interruptible load shed wererequired to maintain reserves. No firm load was shed.
The Mexico assessment area experienced reserve
deficiency when all BA resources were committed andimports from neighboring areas were curtailed during
early evening hours. No firm load was shed.
High temperatures caused high demand during
periods when planned maintenance on a majortransmission line reduced imports. Low windconditions reduced wind generator output. No firm
load was shed.

NERC Seasonal
Assessment
Indication
Low RiskElevated Risk

Low RiskElevated Risk

Low Risk

Changes in the Peak Resource Mix over the Past 10 Years
The generation resource mix is changing as older nuclear and fossil-fired generators retire and natural-gas-fired
generators and wind and solar PV resources are built (see Table 3.3). Over the past 10 years, the BPS has reduced its
on-peak capacity of coal-fired generation by over 122 GW and reduced its capacity of nuclear generation by 9 GW.
During this time, the BPS added on-peak generation capacity: 73 GW of natural gas, 21 GW of wind, and 57 GW ofsolar PV. 41
Table 3.3: Generation Resource Capacity by Fuel Type2013 On-Peak2023 On-PeakGeneration
Fuel Type
GW
Percent
GW
Percent
Coal
318.0
30.1%
195.3
18.4%
Natural Gas
412.0
39.0%
485.3
45.8%
Hydro
138.9
13.2%
124.5
11.7%
Nuclear
115.2
10.9%
106.2
10.0%
Oil
48.9
4.6%
32.1
3.0%
Wind
11.6
1.1%
32.8
3.1%
Solar PV
2.0
0.2%
59.7
5.6%
Other
8.5
0.8%
24.4
2.3%
Total:
1055.0100.0%
1,060.2
100.0%
41 Data obtained from NERC long-term reliability assessments

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Chapter 3: Grid Transformation

The resource mix and the pace at which it is changing varies considerably across different parts of the North American
BPS. Figure 3.4 provides an Interconnection-level view of the generation resource mix since 2013.

Figure 3.4: 2013 and 2023 Capacity Resource Mix by Interconnection
NERC’s LTRA reports on both the current generation resource mix and projections for the next 10 years for each of
the 20 assessment areas within the four Interconnections that encompass the North American BPS. NERC’s 2023
LTRA shows that wind, solar PV, and hybrid (battery storage combined with another type of generator) resources
are projected to be the primary additions to the resource mix over the 10-year assessment period; this leads thecontinued energy transition as older thermal generators continue to retire. Maintaining a reliable BPS throughout
the transition requires unwavering attention to ensure that the resource mix satisfies capacity, energy, and essential
reliability service (ERS) needs under designed conditions. It will also require significant planning and development of
the interconnected transmission system to have a deliverable electricity supply from new resources to changing
types of loads and the ability to withstand system contingencies.

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Chapter 3: Grid Transformation

Critical Infrastructure Interdependencies

In addition to an increased reliance on weather-dependent fuels, such as wind and solar, today’s generation resource
mix includes more natural gas-fueled generation than ever before. Figure 3.5, 42 prepared by the Energy Information
Agency (EIA), shows the average natural gas generation by dispatch hour for the years 2021–2023.

Figure 3.5: Lower 48 States Annual Average Natural Gas Generation by Hour of Dispatch
The supply and delivery of natural gas to power plants depends on the reliable operation of natural gas production,gathering, processing, and delivery facilities that in turn often rely on electricity as a prime mover. The same is trueof the water supply, whether it will be used to directly generate electricity or to cool another generator, it is often
managed and controlled by third-party infrastructure powered by electricity. Figure 3.6 and Figure 3.7 show
generation outages over the past five years that have been attributed to a lack of natural gas fuel or water supply
availability issues.

MW Lost200,000
150,000
100,000
50,000
0

2019

2020

2021

2022

2023

Figure 3.6: Natural-Gas-Fired Outages Due to Lack of Fuel

42 U.S. natural gas-fired electricity generation consistently increased in 2022 and 2023 - U.S. Energy Information Administration (EIA)

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Chapter 3: Grid Transformation

Figure 3.7: Cumulative MW–Water Supply Issues by YearAs natural gas continues to fuel more base and intermediate loaded generation, extreme weather events havehighlighted the risks of the natural gas and electric industries’ mutual reliance. The risk is particularly acute in winterwhen natural gas demand for home and commercial space heating coincides with high electricity demand. This risk
was realized in February 2021 when extreme cold weather descended upon the U.S. central southwest. The resulting
gas production declines, pipeline force majeures, and generator outages led to electrical energy deficiencies andload shedding, which in turn exacerbated gas unavailability issues. Since that time, efforts to maintain gas production
and pipeline availability during cold weather, notably in Texas, as well as NERC and industry actions to improve cold
weather generator availability, have been developed and many have been implemented. 43,44,45,46
In October 2023, FERC and the ERO Enterprise published the official report on Winter Storm Elliott. Previously
identified electric–gas interdependencies were less of a contributing factor to the electrical energy deficiencies thanwhat occurred during the February 2021 winter storm. Energy-deficient balancing areas shed much less load than in
February 2021, and gas production facilities were not impacted. The report identifies the degree to which facilities
essential to the production and delivery of natural gas have still not been identified to balancing area operators ascritical electrical loads, which remains a risk for future cold weather events. 47 Risks emanating from theinterconnected electric–gas energy delivery system were also highlighted. 48

43 Fuel Assurance and Fuel-Related Reliability Risk Analysis Guideline
44 Considerations for Performing an Energy Reliability Assessment

45 Project 2022-03 Energy Assurance with Energy-Constrained Resources

46 Project 2023-07 Transmission System Planning Performance Requirements for Extreme Weather
47 WS Elliott Report Recommendation 4(c) addresses this risk.
48 See, generally, WS Elliott Report, pp 76-88.

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Chapter 3: Grid Transformation

Figure 3.8: The Interconnected Gas and Electric Energy Delivery System 49,50
Utilizing data from the EIA’s 2023 Annual Energy Outlook, Figure 3.8 shows the annual generation by fuel type andnatural gas consumption by end-use sector percentages. Industrial, commercial, and residential end users accountfor 51% of all natural gas use in the United States. Power generators use 30% of all natural gas to produce electricity,representing 37% of all electrical energy delivered. Extreme cold weather can significantly increase demand fornatural gas by power generators and residential/commercial end-use customers well above these annual averages.
For example, during the December 2022 event, the U.S. Northeast/Midwest/Southeast regions’ natural gas
consumption51 by electric generators temporarily increased by roughly 15% while consumption of natural gas byresidential and commercial end-use gas customers increased by nearly 50% (shown in Table 3.4). 52
Table 3.4: Overall and Relative Increase in Natural Gas Consumption for the
Northeast, Midwest, and Southeast Regions during Winter Storm Elliott
Billion Cubic Feet per Day (Bcf/day) 53
Dec. 21–26, 2022
Dec. 15–20, 2022
Percent Change
Average
Average
Northeast/Midwest/Southeast
82.3
100.5
22.1%
Natural Gas DemandPower Burn
21.2
24.6
15.8%
Residential/Commercial

31.4

46.0

46.5%

Industrial

15.3

16.5

7.9%

LNG Feedgas

10.6

8.5

-19.8%

Pipe Loss

3.9

5.0

29.2%

49 Annual gas consumption percentages EIA 2023 Annual Energy Outlook
50 Annual electric energy from fuel type EIA 2023

51 Consumption does not include demand unmet due to fuel unavailability.
52 WS Elliott Report, Fig. 92.
53 WS Elliott Report, Fig. 92

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Chapter 3: Grid Transformation

This increased consumption, in combination with natural gas supply interruptions during extreme cold weather
periods, challenges both grid operators and gas controllers to maintain energy deliveries to end-use customers whenconditions can be life threatening. While the gas industry has long relied upon natural gas storage to manage spikes
in consumption and mitigate the risk of supply interruption, electric generators typically do not store natural gas,and electric energy storage at utility scale is not currently available to overcome this risk.
Winter Storm Elliott Report Recommendation 5 addresses situational awareness issues by urging grid operators andgas controllers from across the interconnected natural gas–electric production and energy delivery system to quickly
develop and formalize protocols to communicate operational issues leading up to and during extreme weather
events. 54 Longer term, Recommendation 4 of the Winter Storm Elliott report calls for the creation of a natural gas
reliability organization to develop rules that would require natural gas wellhead, gathering, processing, andtransportation infrastructure cold weather preparations to maintain natural gas availability and energy deliveries to
end-use customers when needed most. 55
6 GHz Frequency Communications
In April 2020, the Federal Communications Commission (FCC) opened usage of the 6 GHz 56 spectrum to new users
to promote spectrum sharing. Sharing this spectrum will likely impact the energy industry (specifically criticalinfrastructure) and BPS reliability. The industry and incumbent users continue to conduct testing on potential
harmful interference for BPS communications.
In support of industry awareness and strengthening reliability, the 6 GHz Task Force published its 6 GHz Microwave
Link Interference Preparedness 57 white paper in December 2023. This white paper provides valuable backgroundinformation on the current state of the FCC processes, current spectrum usage, and recommendations for theindustry to assist with baseline understanding, the identification of potential harmful interference, and mitigation
options to offset impacts from harmful interference. Additionally, the 6 GHz Task Force plans to conduct anawareness webinar in the second quarter of 2024.

Increasing Complexity of Protection and Control Systems

Together with the progression of interconnected power generation, transmission, and distribution assets, thelandscape of automated tools and systems has transformed. This evolution spans an array of digital information
platforms and microprocessor-driven devices, fostering a technologically diverse environment wherein operators
can wield unprecedented control from virtually any location at a fraction of the historical cost. When meticulously
designed and executed, these automated tools offer a means to enhance the reliable and secure use of thetechnologies and concepts in the BPS. However, the proliferation of these systems introduces an increasing web ofrules, algorithms, and interdependencies that amplify the intricacy of operation. The swift decision-making
capabilities of modern relays, tripping circuits, or initiating alternative actions within milliseconds epitomize theaccelerated pace at which these systems must navigate intricate operational scenarios. The increasing integration of
IBRs also expands this complexity, requiring the deployment of additional automated tools and systems. Navigating
this expanding labyrinth demands not only vigilant maintenance, prudent asset replacement, and strategic upgrades,
but also a nuanced understanding of the dynamic interplay between diverse system components. As the scope andscale of these challenges continue to proliferate, it is imperative to cultivate agile, adaptive solutions.
Protection System Misoperation Trends
Figure 3.9 presents the annual misoperation rates across all Regional Entities and separately for each Regional Entity
over the last five years. The comparison of the misoperation rate of the first four years to the most recent year showsa statistically significant decreasing trend for Texas RE. No statistically significant trend is observed for any otherRegional Entity, nor within the overall MIDAS data. The overall count of misoperations in 2023 was the lowest overthe past five years (see Table 3.5).
54 WS Elliott Report, p. 143.
55 WS Elliott Report, p. 137.

56 6 GHz Communication Penetration in the Electric Industry, April 23, 2024
57 6 GHz Microwave Link Interference Preparedness

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Chapter 3: Grid Transformation

Figure 3.9: Changes and Trends in the Annual Misoperations Rate by Regional Entity 58

Table 3.5: Five-Year Protection System Operations and Misoperations Counts
2019–2023
Protection System Operations
Misoperations
Area
2019
2020
2021
2022
2023
2019
2020
2021
2022

2023

North
America

19,28318,306

17,46018,012

17,821

13,44

1,172

1,187

1,163

1,131

MRO
NPCC
RF
SERC
Texas RE
WECC

3,734
1,658
2,146
4,736
2,640
4,369

3,054
1,774
1,888
5,267
2,000
4,323

2,617
1,365
1,867
4,622
2,599
4,390

3,299
1,811
2,061
4,775
1,991
4,075

2,999
1,744
1,865
4,894
2,182
4,137

272
131
245
283
168
245

257
132
205
254
119
205

230
164
161
270
135
227

281
130
142
254
148
208

247
143
157
287
100
197

Leading Causes of Misoperations
Figure 3.10 shows the distribution of misoperation causes over the past five years. Incorrect settings and relay
failures/malfunctions remain the most common causes of misoperations. There was minimal change in the relative
frequency of causes from 2022 to 2023.

58 M-9, Protection System Misoperations Rate

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Chapter 3: Grid TransformationYear
Misoperation Count

2019
1,344

2020
1,172

2021
1,187

2022
1,163

2023
1,131

Figure 3.10: Percentage of Misoperations by Cause Code (2019–2023)
Misoperation Impact Score
The misoperation impact score provides an estimated impact of each misoperation on the BPS. This is done bysumming weighted values for the facility voltage class, equipment type, cause, and category (shown in the equation
and Table 3.6 below). Note that this calculation can be scaled down to an individual misoperation. In this report, theresults are aggregated and then plotted in a box and whisker plot to identify potential trends.
[𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀 𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼 𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆]= [ 𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉 𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶 𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹] ∗ 0.3 + [𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸 𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇 𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹] ∗ 0.2 + [𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶 𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹] ∗ 0.1+ [𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶 𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹] ∗ 0.4
Table 3.6: Generation Resource Capacity by Fuel Type Misoperation Impact Factors
Field
Value
Factor0–99 kV
0.4
100–199 kV
0.5
Voltage Class
200–299 kV
0.65
300–499 kV
0.85
500–765 kV1
BES UFLS, BES UVLS
0.333
Equipment Type Shunt Capacitor, Shunt Reactor/Inductor
0.5
HVdc, Line, Series Capacitor, Series Reactor/Inductor, Transformer, Breaker 0.667
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Chapter 3: Grid Transformation

Table 3.6: Generation Resource Capacity by Fuel Type Misoperation Impact Factors
Field
Value
FactorBus, Other
0.833
Dynamic VAR Systems, Generator
1
Equipment Errors (and Other)
0.5
Cause
Human Errors
0.85
Unknown1
Slow Trip–Other than Fault
0.167
Unnecessary Trip–Other than Fault
0.333
Category
Failure to Trip–Other than Fault, Unnecessary Trip–During Fault
0.667
Failure to Trip–During Fault, Slow Trip–During Fault
1
The median and inner quartiles of all misoperations’ impact scores (see Figure 3.11) have remained largely
unchanged over the past five years, while the number of outliers has decreased. The Duncan’s grouping test 59
confirms that the mean impact score for 2023 was statistically similar to 2021 and 2022 but statistically lower thanin 2019 and 2020. These factors (in combination with the slowly decreasing but statistically stable misoperation rate,
number of misoperations, and cause distribution) indicate that work being done to reduce misoperations iscontinuing. The ERO and industry should continue to monitor and coordinate to identify any common issues tofurther drive down misoperations and their severity.

Figure 3.11: Misoperations Impact Score Distribution (2019–2023)
Year
2019
2020
2021
2022
2023
Total Impact Score
808.98706.88709.91
693.41671.5059 Duncan, David B. “Multiple Range and Multiple F Tests.” Biometrics 11, No. 1 (1955): 1–42. https://doi.org/10.2307/3001478.

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Chapter 3: Grid Transformation

Protection System Failures Leading to Transmission Outages

AC circuits and transformers saw a decrease in the number of outages per element in 2023, resulting in the numberof outages per ac circuit being statistically significantly lower than the prior four years (see Figure 3.12).

Figure 3.12: Failed Protection System Equipment Outages 60
Event-Related Misoperations
An analysis of qualified events reported through the ERO Event Analysis Process (EAP) found that there were 72transmission-related qualified events in 2023, 36 of which (50%) involved misoperations (see Figure 3.13). In
comparison, 2019 saw 76 transmission-related qualified events, of which 41 (54%) had associated misoperations.
This reduction is attributed to the ERO and industry stakeholder efforts to reduce protection system misoperations
through initiatives such as various task forces, workshops, and more granular root-cause analysis.

60 M-12, Automatic AC Transmission Outages Initiated by Failed Protection System Equipment

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Chapter 3: Grid Transformation

Figure 3.13: Events with Misoperations

Loss of Situational Awareness

The BPS operates in a dynamic environment with physical properties that are constantly changing. Situationalawareness is necessary to maintain reliability, anticipate events, and respond appropriately when or before eventsoccur. To maintain the reliability of the BPS, entities use various situational awareness tools, including energy
management systems (EMS), transmission outage planning, load forecasting, geomagnetic disturbance/weather
forecasting, data from neighboring entities’ operations, and interpersonal communication within their own
companies and with neighboring systems.
Without the appropriate tools and up-to-date data, system operators may have degraded situational awareness that
impacts their ability to make informed decisions regarding BPS reliability. Unexpected outages of systems needed
for communications or monitoring and control of equipment, as well as planned outages without appropriate
coordination or oversight, can leave system operators with reduced visibility. For system operators, the EMS is a
critical component of situational awareness.
At the same time, security risks have implications for industry that require a broadened perspective from what wastraditionally addressed in conventional engineering practices, such as planning, design, and operations. The 2023
ERO Reliability Risk Priorities Report 61 continued to highlight security risks as one of the four top risks for theelectricity sector with cyber security risks identified as the most likely to impact the industry.
Impacts from the Loss of EMS
An EMS is a computer-aided set of tools used by system operators as a primary means to monitor, control, andoptimize the performance of the generation and/or transmission system. The EMS allows system operators tomonitor and control frequency, the status (open or closed) of switching devices plus real and reactive power flows
61 2023 ERO Risk Priorities Report, August 2023

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Chapter 3: Grid Transformation

on BPS tie-lines and transmission facilities within the respective control area, and the status of critical applicable
EMS applications (e.g., state estimator (SE), real-time contingency analysis (RTCA), automatic generation control,
alarm management).
There were 32 categorized events associated with an EMS in 2023; there were no reported EMS-related events thatcaused loss of generation, transmission lines, or customer load. Figure 3.14 shows a trend of the reported EMS eventsby loss of EMS functions over the 2019–2023 period.

Figure 3.14: Number of EMS-Related Events (2019–2023)
There are two main reasons for the declining trend of the loss of SE/RTCA and Inter-Control Center Protocol (ICCP)
events since 2019:•

Changes to Work Environment
The industry has made major efforts to enhance EMS reliability and resilience. For example, many entities
built a 24x7 onsite team that works with system operators and provides dedicated support to SE and RTCA.
This action has reduced the outage duration, resulting in many SE/RTCA issues not being reportable.

•

Changes to Reporting
Partial loss events (i.e., loss of SE/RTCA, loss of ICCP, loss of remote terminal units (RTU), and loss of
automatic generation control) are no longer captured as part of EOP-004-4 62 mandatory reporting (effective
April 1, 2019). However, the ERO encourages partial-loss EMS reporting through the ERO EAP for trendingof potential reliability risks/impacts to the BPS as some entities continue to do.

There were 25 complete loss of monitoring 63 or control 64 capability events in 2023. The following two major
contributors to the events were observed:
62 Emergency Operating Procedure, Event Reporting, EOP-004-4

63 The ability to accurately receive relevant information about the BPS in real time and evaluate system conditions using real-time data toassess existing (pre-contingency) and potential (post-contingency) operating conditions to maintain reliability of the BPS.

64 The ability to take and/or direct actions to maintain the reliability of the BPS in real time via entity actions or by issuing operating instructions.

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Chapter 3: Grid Transformation•

Network Communications Configuration
EMS-related communications networks are moving from point-to-point serial communication infrastructures
to packet-based networks. The main advantage of a packet-based network is to transmit data from one nodeto another node while avoiding a communications system failure caused by the breakdown of a single (orfew) intermediate link(s). Consequently, the correct configuration is critical to ensure that thecommunications network functions as designed.

•

Power Supply
Stable and secure power supplies are critical to control rooms, data centers, and substations. It is essentialthat routines be established for monthly testing and maintenance of the backup generator, uninterruptible
power supply, and associated power switches.

Database and system configuration/settings were improved in 2023, contributing to the decrease in the complete
loss of monitoring or control capability events.
•

Settings
Periodic review of system parameters and settings with vendor support has been shown to reduce settingserrors. Different flags and weighting levels may need to be adjusted as models are expanded or system
conditions change.

•

Skill Development
More skilled in-house personnel who can troubleshoot and correct these issues can lead to shorter outage
durations, including additional knowledge transfer from the vendor to the in-house staff.

Over the five-year period (2019–2023), the average partial or full function EMS outage time (see Figure 3.15) was 73
minutes, making the calculated EMS availability 99.994% during the term.

Figure 3.15: Average EMS Outage Time (2019–2023)

Largest Contributor to Loss of EM S

Reported EMS events can be grouped by the following attributes:•

Software: Software defects, modeling issues, database corruption, memory issues, etc.

•

Communications: Device issues, less-than-adequate system interactions, etc.

•

Facility: Loss of power to the control center or data center, fire alarm, ac failure, etc.

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Chapter 3: Grid Transformation•

Maintenance: System upgrades, job scoping, change management, software configuration, settings failure,etc.

Figure 3.16 shows that, over the evaluation period of 2019–2023, outages associated with software challenges werethe leading contributors to EMS outages followed by outages associated with communications and maintenancechallenges.
Software failure was usually caused by bugs, either in a vendor
application or in an in-house implementation. A software testingprocess is always recommended to meet requirements. Systems
and software assurance require a process model for formal
testing based on the development framework the software wascreated with. The scope of the test should provide an assurance
case for operation of the software under test for both known
and unknown operating conditions with the inclusion of a data
integrity check of the module. In general, the process is
considered to have four components:••

Test Scope: Define the requirements and setup of thetest environment, features and functions that need to betested, documentation to refer to and produce as output,
approval workflows, etc.

Figure 3.16: Contributors to Loss of EMS
Test Design: Design the test cases that are necessary toFunctions (2019–2023)
validate the system, functions, and features being built
compared to its design requirements. Typically, regression testing, and incremental testing are necessary.

•

Test Execution: Execute tests in many different ways.

•

Test Closure: Consider the exit criteria for signaling completion of the test cycle and readiness for release.

Communications failure means that data exchange was degraded between substations and control rooms or
between the entity and its RC/neighboring entities. Internal network configuration error and hardware failure are
two major contributors to this cause. Entities should maintain network devices on a schedule in accordance with thelatest vendor information, security bulletins, technical bulletins, and other recommended updates. Entities must also
consider redesigning communications systems such that the most critical BPS substations communicate
simultaneously over entirely separate physical paths to control centers.
Maintenance failure usually occurs when system configuration/settings are not updated according to changes in thelatest system operation. These EMS system configuration/settings are often uniquely programmed for the entity tomeet the individual needs based on the entity’s configuration, topology, contingencies, and external model. Whenthe entity expands or modifies its model, the configuration/settings need to be tuned or calibrated based on
subsequent topology changes. Periodic reviews of the settings and configuration with the vendor’s help may benecessary to ensure that the EMS functions continue to converge and produce a quality solution. The frequency ofthese reviews will vary, but consideration of reviewing the settings and configuration following model changes,
generation retirements, software upgrades, and any other significant changes made to the EMS system or model isnecessary.
A review of ERO EAP data shows that a total of 5.7%, or 15 out of the 263 reportable loss of EMS events between
2019 and 2023 that were greater than 30 minutes, were related to external communication provider issues. External
communication provider related issues are not currently influencing EMS outages in a major way.

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Chapter 3: Grid Transformation

Human Performance

As human error can adversely impact the performance of BPS equipment, it is important to establish and adhere torobust processes to minimize the risks. In-depth analysis often identifies that primary human error causal factors area result of latent errors as well as organizational and programmatic weaknesses. As the 2023 ERO Reliability Risk
Reliabilities Priority Report 65 states, “The BPS is becoming more complex, and the industry will have difficulty staffing
and maintaining necessary skilled workers as it faces turnover in technical expertise.”Transmission Outages
NERC’s TADS collects transmission outage data, including on human error; human error as a cause of transmission
outage is defined in the TADS Data Reporting Instructions. 66 Weaknesses in human performance hamper anorganization’s ability to identify and address precursor conditions that degrade effective mitigation and behavior
management. Effective human performance will help mitigate the active and latent errors that negatively affectreliability.
Statistical significance testing compared the average outage rate of 2023 to that of the prior four years. For ac
circuits, all forced outages caused by human error saw a statistically significant decrease in frequency (see Figure3.17). Transformers saw a statistically significant decrease in operational outages and an apparent increase inautomatic outages caused by human error; however, this was not statistically significant (see Figure 3.18).

Figure 3.17: AC Circuit Outages per Circuit Initiated by Human Error 67

65 2023 ERO Reliability Risk Reliabilities Priority Report

66 Human Error: relative human factor performance including any incorrect action traceable to employees and/or contractors of companies

operating, maintaining, and/or assisting the Transmission Owner.
67 M-13, Automatic AC Transmission Outages Initiated by Human Error

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Chapter 3: Grid Transformation

Figure 3.18: Transformer Outages per Element Initiated by Human Error 68
Generation Outages
NERC’s GADS collects generation availability data, including on outages associated with human error. While NERC
continues tracking these outages, they have historically represented approximately 1% of all forced-outage events,
and no systemic increase warranting presentation was observed in 2023.
Trends of Event Root Causes
In the ERO EAP, the cause sets of individual human performance and management/organization identify events orconditions that caused or contributed to the reported event. In 2023, organization/human performance was
identified as the root cause for 20 processed events (see Figure 3.19). This may not fully project the final number asjust more than half of the 2023 events have been assigned a final root cause. For the same period, the top fivedetailed root causes, listed in priority order below, are members of the management and organization performance
categories or the design and engineering category:
1. Design output scope less than adequate
2. Job scoping did not identify special circumstances and/or conditions
3. Management policy guidance or expectations are not well-defined, understood, or enforced
4. Corrective action responses to a known or repetitive problem were untimely
5. System interactions not considered or identified

68 M-13, Automatic AC Transmission Outages Initiated by Human Error

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Chapter 3: Grid Transformation

Figure 3.19: ERO EAP Organization/Human Performance Root Cause Identification by Year
Events processed between 2019 and 2023 saw three of the same top five root causes identified in the 2018–2022
time period. The causes “Design Output Scope Not Correct” and “Previous Industry or In-House Experience Was not
Effectively Used To Prevent Recurrence” were replaced with “Management Policy Guidance or Expectations Are not
Well-Defined, Understood, or Enforced” and “System Interactions not Considered or Identified,” respectively.
An opportunity exists for industry to improve BPS reliability through increased focus in the areas of management
and organization performance and engineering and design. Management and organization performance includes
subcategories in which methods, actions, and/or practices are less than adequate. The Engineering and Design
category includes ensuring that the engineering group employs a robust peer-review process to identify procedural
errors and all considerations a design needs to be accountable. One way to improve human and organization
performance would be to establish robust internal control mechanisms to ensure that processes and procedures arein place to ensure that project leaders consider the potential impacts and dependencies that may exist elsewhereon the system.
Protection System Misoperations
Human performance-related misoperations remain common, representing 41% of misoperations in 2023; consistingof 10% As-Left Personnel Error, 5% Design Errors, 22% Incorrect Settings, and 4% Logic Errors (see Figure 3.10). Figure
3.20 shows the number of misoperations related to human error by Regional Entity for the past five years. The fiveyear trends for all Regional Entities, except SERC, are either improving or remaining consistent.
To improve the frequency of misoperations potentially due to human error, SERC formed a task force last year todevelop sub-cause categories to better identify what areas to target for improvement. Starting in 2024, the SERC
Protection and Control Working Group (PCWG) has documented these subcategories to develop mitigation
strategies. It is also focusing on reducing incorrect settings by having members summarize their relay settingsprocesses to identify improvement opportunities and incorporate them into stakeholder setting processes.

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Chapter 3: Grid Transformation

Figure 3.20: MIDAS Protection System Misoperations Due to Human Error by Regional Entity

Energy Emergency Alerts 69

The purpose of an EEA is to provide real-time
indication of potential and actual energy
emergencies within an Interconnection. An EEA3 is reported when firm load interruption isimminent or in progress. EEA trends may provide
an indication of BPS capacity, energy, andtransmission insufficiency. Figure 3.21 shows that
16 EEA-3s were declared in 2023, a decrease of
10 EEA-3 declarations over 2022. None of the
EEA-3 declarations in 2023 included shedding offirm load (92.6 GWh in 2022 vs 0 GWh in 2023.)
All EEA-3 declarations in 2023 were associatedwith periods of reduced generation or import
capability combined with a heavy load day. Whilenone of these days would be considered extreme
weather days, 11 of the EEA-3 reports did
indicate that higher temperatures or loads wereinvolved.

Figure 3.21: EEA-3 by Year and Interconnection

Figure 3.22 shows the number of hours when operator-initiated firm load shed was deployed during each of the past
five years. In 2023, zero hours occurred, while in 2022, 21 hours occurred in June during excessive heat and 35.5
hours occurred during Winter Storm Elliott, for a total of 56.5 hours.

69 M-11, Energy Emergency Alerts

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Chapter 3: Grid Transformation

70

Number of Hours

60
50
40
30
20
10
0

2019

2020

2021

2022

2023

Winter Storm Elliot (35.52 Hours)
June Heatwave (21.01 Hours)
February Cold Weather Event (70.5 Hours)
California Wildfires (4.1 Hours)
Hurricane Laura (10.9 Hours)
California Heatwave (7.4 Hours)
WI: Generator Trip, Subsequent Failure of Dispatched Units (0.8 Hours)
Figure 3.22: Hours with Operator-Initiated Firm Load Shed (Hours/Year)

NERC | State of Reliability | 202452

: Grid Performance
Grid performance is evaluated through established reliability metrics and more in-depth analysis of specific aspectsof the BPS:•

Reliability Metrics•

Frequency Response Performance•

Generation Performance and Availability•

Transmission Performance and Unavailability

Reliability Metrics

By calculating 2023 reliability metrics 70 and comparing the results to the previous years as well as the five-year
average values, the reliability metrics discussed in this chapter can be categorized as either Improving, Stable,
Monitor, or Actionable. Measuring and trending the relative state of the BPS in this manner supports NERC’s
obligation to assess the capability of the BPS. Table 4.1 shows the status of the reliability metrics and includes areference to the specific metric.
Table 4.1: Reliability Indicators
Metric Name
Metric Performance Status
M-1: Reserve Margin
ActionableM-2: Transmission-Related Events Resulting in Loss of
Improving
Load (Excluding Weather)M-3: System Voltage Performance
Retired
Improving:
Stable: Eastern
Monitor: Québec
M-4: Interconnection Frequency Response
Texas
and WesternInterconnection
Interconnection Interconnections
Improving:
Stable: Eastern
Monitor: Québec
M-4.1: Inertia and Rate-of-Change-of-Frequency
Texas
and WesternInterconnection
Interconnection Interconnections
M-5: Activation of Under Frequency Load Shedding
RetiredM-6: Disturbance Control Standard Failures
Metric is Under Review
M-7: Disturbance Control Events Greater than Most
Metric is Under Review
Severe Single Contingency
Improving:
Monitor: Eastern
M-8: Interconnection Reliability Operating Limit
Texas andand Québec
Western(IROL) ExceedanceInterconnections
Interconnections
M-9: Protection System Misoperations Rate
StableM-10: Transmission Constraint Mitigation
RetiredM-11: Energy Emergency Alerts
ImprovingM-12: Automatic AC Transmission Outages InitiatedImprovingby Failed Protection System Equipment
M-13: Automatic AC Transmission Outages InitiatedImprovingby Human Error
M-14: Automatic AC Transmission Outages InitiatedImprovingby Failed AC Substation Equipment

70 Current Approved Reliability Metrics; Metrics M-3, M-5, and M-10 are retired.

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Chapter 4: Grid Performance

Table 4.1: Reliability Indicators
Metric Name
Metric Performance Status
M-15: Automatic AC Transmission Outages InitiatedImprovingby Failed AC Circuit Equipment
M-16: Transmission Element Availability Percentage
Stableand Unavailability Percentage
M-17: Transmission Outage Severity
StableFrequency Response PerformanceFrequency response arrests and stabilizes
frequency during system disturbances. NERC
closely monitors the frequency response of eachof the four Interconnections and measures themargin at which under-frequency load shedding(UFLS) would be activated. UFLS provides a vital
safety net for preserving Interconnection
reliability. Measuring the margin allows NERC
and the industry to ensure that there is adequate
frequency response on the system.

During the arresting period, the goal is to arrest
the frequency decline for credible contingencies
before the activation of UFLS. The calculation forInterconnection frequency response obligation(IFRO) under BAL-003 is based on arresting the
Point C nadir before the first step of UFLS for
resource contingencies at or above the resource
Figure 4.1: Frequency Response Methodology
loss protection criteria (RLPC) 71 for theInterconnection. Measuring and tracking themargin between the first-step UFLS set point and the Point C nadir is an important indicator of risk for each
Interconnection. Figure 4.1 indicates the measurement periods used for analysis of the arresting period of events bylooking at the frequency response between Value A and Point C as well as at the margin between Point C and thefirst-step UFLS set point.
During the stabilizing period, the goal is to stabilize system frequency following a disturbance primarily due togenerator governor action. Figure 4.2 indicates the measurement periods used for analysis of the stabilizing periodof events by looking at the frequency response between Value A and Value B.
2023 Interconnection Frequency Response2023 performance and trends frequency response analysis indicate an adequate level of reliability.
•

For the stabilizing period, the Interconnection frequency response, 72 the Eastern Interconnection, theQuébec Interconnection, and the Western Interconnection showed no statistically significant changes from2019 through 2023. The Texas Interconnection showed a statistically significant improvement for thestabilizing period from 2019 through 2023.

•

For the arresting period, the inertia and rate-of-change-of-frequency (ROCOF), 73 the Eastern and WesternInterconnections showed no statistically significant changes from 2019 through 2023. The Texas

71 BAL-003-2 specifies that the RLPC be based on the two largest potential resource losses in an Interconnection or the largest resource loss

due to an N-2 RAS. This value is updated annually through the BAL-003-2 data collection process.

72 Interconnection Frequency Response, M-4

73 Inertia and Rate-of-Change-of-Frequency, M-4.1

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Chapter 4: Grid Performance

Interconnection showed a statistically significant improvement. The Québec Interconnection showed astatistically significant decreasing trend.
Of note in 2023, as shown in Table 4.2, the Western Interconnection had two events within the five-year period inwhich the measured frequency response was less than the IFRO. Both events had a starting frequency well above
60.00 Hz and had a confirmed MW loss under 500 MW. These two factors combined alleviate concerns that theWestern Interconnection frequency response is insufficient. Also, of note in 2023 was the decreasing trend in theinertia and ROCOF for the Québec Interconnection. The Québec Interconnection confirmed an overrepresentation ofsummer events in 2023 compared to other years (2019–2022). Twenty percent of all events in the past five years
occurred between May and October 2023 (months that typically have lower inertia), in part due to the wildfire eventsin the region. The Eastern Interconnection, Québec Interconnection, and Texas Interconnection did not have any
events within the five-year period in which the measured frequency response was less than the IFRO for therespective Interconnection.
Table 4.2: 5-Year Statistical Trend

Interconnection
Eastern
Texas
QuébecWestern

M-4
Interconnection
Frequency
Responseneither decreasing
nor increasing
increasing
neither decreasing
nor increasing
neither decreasing
nor increasing

M4.1
Inertia and Rate-ofChange-of-Frequency

Margin-C-UFLS

Comment

neither decreasing
nor increasing

neither decreasing
nor increasing

increasing

increasing

No M4 events with
FR below IFRONo M4 events with
FR below IFRONo M4 events with
FR below IFRO
Two M4 eventswith FR below IFRO

decreasing
neither decreasing
nor increasing

neither decreasing
nor increasing
neither decreasing
nor increasing

Of note, the Western Interconnection has had the least number of valid events since frequency response evaluation
started. This trend in reduction of valid frequency response events is suspected to be due to the retirement of large
generating facilities in the Interconnection over the evaluation period and is a positive indicator when considering
impacts to Interconnection reliability.
Frequency response for all Interconnections indicates stable and improving performance for the stabilizing period
and arresting period as shown in Table 4.3 and Table 4.4. 74
Table 4.3: 2023 Frequency Response Performance Statistics for Stabilizing Period2023 Operating Year Stabilizing Period Performance
Mean
Number of
Number of
Frequency
MedianMinimum
Maximum
events with FR
EventsResponse
below the IFRO
Eastern
47
2,685
2,459
1,138
5,176
0
Texas
38
1,410
1,241
682
2,788
0
Québec
65
762
693
260
1,682
0
Western
28
2,049
1,682
912
5,050
2

74 Frequency Response Performance Statistics

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Chapter 4: Grid Performance

Table 4.4: 2023 Frequency Response Performance Statistics for Arresting Period
Operating Year (OY)
Mean
Mean
MedianMin.
Number of
Frequency
Median Minimum Maximum
UFLS
UFLS
UFLS
EventsResponse
MarginMargin Margin
Eastern
47
2,151
1,969
1,059
3,550
0.454
0.453
0.441
Texas
38
727
738
283
1,604
0.611
0.606
0.579
Québec
65
124
120
48
233
1.022
1.065
0.118
Western
28
868
829
544
1,554
0.415
0.421
0.332
Figure 4.2 represents an analysis of the arresting period of frequency response events. The Y-axis shows the percent
UFLS margin from 100% (60 Hz) to 0% (first UFLS set point for the Interconnection). The X-axis represents the MW
loss for the event, expressed as a percentage of the RLPC for the Interconnection. The Québec Interconnection had
two events at or greater than 100% of the RLPC and maintained sufficient UFLS margin. The largest events for the
Eastern Interconnection and Texas Interconnection were 45% and 50%, respectively, as measured by percentage of
RLPC.

Figure 4.2: Operating Year 2019–2023 Qualified Frequency Disturbances and Remaining
UFLS Margin

Interconnection Reliability Operating Limit Exceedances
2023 Performance and Trends
Each RC has a different methodology for determining Interconnection reliability operating limits (IROL) 75 based on
the makeup of their area and what constitutes an operating condition that is less than desirable. The following
discussion of performance on an Interconnection basis is for clarity, not comparison:

75 M-8, IROL Exceedance

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Chapter 4: Grid Performance•

Eastern–Québec Interconnections: In 2023, there were eight exceedances that lasted more than 10 minutes,
less than the five-year average of 19.4 exceedances as shown in Figure 4.3. The 10- to 20-minute range
continued to decline from its all-time peak in 2019 with zero exceedances greater than 20 minutes.

•

Western Interconnection: The trend has been stable with no IROL exceedances reported in 2023.

•

Texas Interconnection: The trend has been stable with no IROL exceedances reported in 2023.

Figure 4.3: IROL Exceedance Counts 76

Generation Performance and Availability

GADS contains information that can be used to compute reliability measures, such as WEFOR. GADS collects andstores unit operating information by pooling individual unit information, overall generating unit availability,
performance, and calculated metrics.
Conventional Generation WEFOR
The horizontal lines in Figure 4.4 show the annual WEFOR compared to the monthly WEFOR columns; the solid
horizontal bar shows the WEFOR for all years in the analysis period of 7.4%. While noticeably lower than the two
preceding years, the annual WEFOR of 7.8% for 2023 is the third highest since NERC began digitally collecting GADS
data in 2013, despite no major outlying winter weather event.

76 M-8, IROL Exceedance

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Chapter 4: Grid Performance

Figure 4.4: Monthly, Annual, and Five-Year WEFOR
To better illustrate 2023’s high WEFOR relative to historical norms, Figure 4.5 shows the annual WEFOR by fuel type
for the past 10 years. This extended analysis period is presented to illustrate how the abnormally high WEFORs in
2021 and 2022 caused by extreme cold weather conditions obfuscate long-term trends.

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Chapter 4: Grid Performance

Figure 4.5: 10-Year Annual WEFOR by Fuel Type and 2023 Resource Mix by Net Maximum
Capacity
Although coal-fired generation experienced a large decrease in WEFOR in 2023 (12.0% in 2023 versus 13.9% in 2022),
it remains above pre-2021 rates. Due to year-over-year variability, coal generation is the primary driver of change inthe overall WEFOR despite more energy being produced by both natural gas and nuclear power in 2023 (see Figure4.6). Further investigation into baseload coal generation indicates that a unit’s WEFOR negatively correlates moststrongly to capacity factor. 77 Notably, once capacity factor falls below approximately 60%, unweighted average EFORsof units begin increasing more rapidly than those between 60% and 100%. Although forced-outage hours are adefinite contributor to lower capacity factor units’ increased WEFOR, the disproportionate change appears to be
driven more by maintenance/planned outage hours and decreased service hours. This aligns with industry statements
indicating that reduced investment in maintenance and abnormal cycling that are being adopted primarily inresponse to rapid changes in the resource mix are negatively impacting baseload coal unit performance.
Hydro units also experienced an unusually high annual WEFOR (6.9%) for the second time following one in 2021
(7.6%). However, these two relatively high years were both still lower than the associated years’ overall WEFOR and
do not indicate a trend at this point but warrant continued awareness.

77 The correlation factor between capacity factor and WEFOR for baseload coal in 2023 was -0.41. While not mathematically indicative of astrong correlation (generally +/-0.7), it is notably stronger than any other aspect that is not a direct component of the WEFOR with the next
highest being age (0.18) and planned outage hours (-0.16) given the relatively small sample size and amount of variation between coal units.
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Chapter 4: Grid Performance

Figure 4.6: 10-Year Annual Conventional Net Actual Generation (GWh) by Fuel TypeWind Generation Weighted Resource Forced-Outage Rate
NERC began collecting wind performance data with a phased-in approach based on plant size starting with a total
installed capacity of 200 MW or greater in 2018 followed by plants with a total installed capacity of 100–199 MW in2019 and plants with a total installed capacity of 75–99 MW in 2020 (see Figure 4.7). By the end of 2023, data from137,737 MW of installed capacity, representing 703 wind plants across North America and 13% of nameplate
generation, was reported to NERC. Data will continue to be reported separately for the reporting phase groups until
sufficient history is available to analyze trends for a five-year rolling period across all wind plants comparable to theanalysis for conventional generation. Specific event data collection for wind and solar began in 2024 and will allow
for further analysis.

Figure 4.7: Monthly Capacity and Annual Average WRFOR Wind Plant Reporting GroupNERC | State of Reliability | 2024
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Chapter 4: Grid Performance

Transmission Performance and Unavailability

When evaluating transmission reliability, an important concept is that transmission line outages have different
impacts on BPS reliability. Some impacts can be very severe, such as those that affect other transmission lines andload loss. Additionally, some outages are longer than others, leaving the transmission system at risk for extended
periods of time. Reliability indicators for the transmission system are measured by using qualified event analysis
reporting not related to weather and outages reported to TADS. The number of qualified events that include
transmission outages that resulted in firm load loss not related to weather is provided in the following subsection.
Transmission-Related Events Resulting in Loss of Load
In 2023, a total of nine distinct non-weather-related transmission events resulted in a loss of firm load that met the
ERO EAP reporting criteria (see Figure 4.8). The median firm load loss over the past five years was 97 MW, which is adecrease from 2018–2022’s 101 MW. Although, notably, the median load loss was 113 MW in 2023, which is above
the five-year median value, no discernible trend in the number of events or amount of loss is identifiable.

Figure 4.8: Transmission-Related Events Resulting in Loss of Firm Load and Median Amountof Firm Load Loss Excluding Weather-Related Events 78
TADS Reliability Indicators
A TADS event is an unplanned transmission incident that results in the automatic outage (sustained or momentary)of one or more elements. TADS event information was analyzed for the following indicators in this section:•

Transmission Outage Severity•

Automatic AC Transmission Outages•

Transmission Element Unavailability

Transm ission Outage Severity

The impact of a TADS event on BPS reliability is called the TOS of the event, which is defined by the number of outages
in the event and by the type and voltage class of transmission elements involved in the event. TADS events are
categorized by initiating cause codes (ICC). These ICCs facilitate the study of cause-effect relationships between each
event’s ICC and event severity.
78 M-2, BPS Transmission Related Events Resulting in Loss of Load (Excluding Weather)

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Chapter 4: Grid Performance

By examining the average TOS, duration, and frequency of occurrence for events with different ICCs (see Figure 4.9),
it is possible to determine which ICCs contribute most to reliability performance for the considered period. The
average TOS for events with a specific ICC is displayed on the Y-axis. A higher TOS for an ICC indicates that more
outages or higher voltage elements were involved in an event. The average duration for events with a specific ICC isdisplayed on the X-axis; generally, events with a longer duration pose a greater risk to the BPS. The number of ICC
occurrences is represented by the bubble size; larger bubbles indicate that an ICC occurs more often. Change in sizeor position of a bubble with the same number (identifying ICC) may indicate improved or declined performance.
Lastly, the bubble colors indicate a statistical significance of a difference in the average TOS of this group and theevents from other groups. The number of events per hour, average event duration, and average TOS for each ICC
group are shown in Table 4.5.

Figure 4.9: TOS vs. Expected TADS Event Duration

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Chapter 4: Grid Performance

Table 4.5: TOS vs. Expected TADS Event Duration
TADS Event

Events per Hour

Power System Condition
Fire
Combined Smaller ICC Groups
Misoperation
Failed AC Substation Equipment
Other
Unknown
Lightning
Human Error
Failed AC Circuit Equipment
Weather, Excluding Lightning
Foreign Interference
Vegetation

Average TOS

.012
.014
.019
.046
.068
.015
.085
.067
.026
.098
.153
.061
.045

.056
.049
.038
.043
.034
.028
.027
.029
.029
.023
.024
.023
.014

Average Event
Duration
17.9
54.2
37.4
18.8
99.4
21.2
10.0
9.5
12.2
47.3
40.0
25.2
23.2

An analysis of the total TOS by year indicates that 2023 was an outlier from the statistically improving trend identified
over the previous five years. Figure 4.10 shows the annual TOS, which is the third highest over the last five years; theshaded area shows the effect of the Québec wildfires on the 2023 TOS.

Figure 4.10: TOS of TADS Sustained Events of 100 kV+ AC Circuits and Transformers byYear 79

Autom atic AC Transm ission Outages

The average number of outages per circuit due to failed ac substation equipment has continued to improveconsistently over the last four years, showing a statistically significant decrease in 2023 compared to 2019–2022 (seeFigure 4.11 The number of sustained outages due to failed ac circuit equipment per 100 miles saw a decrease in 2023
(see Figure 4.12).
79 M-17, Transmission Outage Severity

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Chapter 4: Grid Performance

Figure 4.11: Number of Outages per AC Circuit Due to Failed AC Substation Equipment 80

Figure 4.12: Number of Outages per 100 Miles Due to Failed AC Circuit Equipment 81

80 M-14, Automatic AC Transmission Outages Initiated by Failed AC Substation Equipment
81 M-15, Automatic AC Transmission Outages Initiated by Failed AC Circuit Equipment

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Chapter 4: Grid Performance

Autom atic AC Transform er Outages

In 2023, the number of automatic ac transformer outages per element caused by failed ac substation equipment was
statistically equal to 2019–2022 (see Figure 4.13); the overall average remains stable.

Figure 4.13: Number of Outages per Transformer Due to Failed AC Substation Equipment 82

Transm ission Elem ent Unavailability

In 2023, ac circuits over 200 kV across North America had an unavailability rate of 0.24%, meaning that there is a
0.24% chance that a specific transmission circuit is unavailable due to sustained automatic and operational outages
at any given time. Transformers had an unavailability rate of 0.25% in 2023. Figure 4.14 shows that 2023 was thelowest year for ac circuit unavailability of the five-year analysis period. Figure 4.15 shows that 2023 was the secondhighest year for transformer unavailability of the five-year analysis period.

82 M-14, Automatic AC Transmission Outages Initiated by Failed AC Substation Equipment

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Chapter 4: Grid Performance

Figure 4.14: AC Circuit Unavailability > 200 kV 83

Figure 4.15: Transformer Unavailability 84

83 M-16, Element Availability Percentage (APC) & Unavailability Percentage
84 Ibid.

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Appendix A: Supplemental Analysis at Interconnection Level
Severity Risk Index by Interconnection
Eastern and Québec Interconnections
The cumulative SRI for the Eastern and Québec Interconnections in Table A.1 shows a 5% decrease compared to theaverage of the four-year period of 2019–2022.
Table A.1: Annual Cumulative SRI Eastern and Québec
Interconnections
Cumulative Cumulative Cumulative
AnnualAverageYear Weighted
Weighted
Weighted Cumulative
Daily SRI
Generation Transmission Load Loss
SRI
2019
2020
2021
2022
2023

345.9
315.3
346.2
385.3
324.7

59.3
58.4
54.5
53.0
65.4

51.3
67.4
64.1
53.0
48.5

456.4
441.0
464.8
491.2
438.6

1.25
1.21
1.27
1.35
1.20

The top 10 SRI days of the Eastern and Québec Interconnections were distributed throughout the year as shown in
Figure A.1 (numbered circles). A total of 8 of the top 10 days that occurred in the Eastern and Québec
Interconnections align with the top 10 SRI days reported for North America.

Figure A.1: 2023 Eastern and Québec Interconnections Daily SRI with Top 10 Days Labeled,
90% Confidence Interval
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Appendix A: Supplemental Analysis at Interconnection Level

Figure A.2: Eastern and Québec Interconnections Top Annual Daily SRI Days, Sorted
Descending
Table A.2 provides details on each component’s contribution to the top 10 SRI days for the Eastern and Québec
Interconnections.

Rank

1
2
3
4
5
6
7
8
9

Table A.2: 2023 Top 10 SRI Days Eastern and Québec Interconnections
Regional
SRI and Weighted Components 2022
AtypicalEntities within
Date
Weather
Weighted
Weighted
Weightedthe
SRI
Conditions
Generation Transmission Load Loss
Interconnection
Widespread
1-Apr
5.85
0.74
0.64
4.46 Storms and
MRO, RF, SERC
Tornadoes
Québec22-Jun
4.47
1.34
2.99
0.14
NPCC
Wildfires
Québec13-Jul
4.44
0.89
3.19
0.36
NPCC
Wildfires
Québec21-Jun
3.98
1.15
2.60
0.23
NPCC
Wildfires
Widespread
25-Mar
3.18
0.60
0.42
2.17
NPCC, RF, SERC
Storms
MRO, NPCC, RF,
3-Mar
3.03
1.22
0.65
1.16 Severe Storms
SERC
Québec
1-Jun
2.75
1.62
1.07
0.05
NPCC
Wildfires
MRO, NPCC, RF,
26-Jun
2.66
1.16
1.12
0.39 Thunderstorms
SERC
Coincident
3-Feb
2.55
2.28
0.10
0.18
N/A
Large Coal and

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Appendix A: Supplemental Analysis at Interconnection Level

Rank

10

Table A.2: 2023 Top 10 SRI Days Eastern and Québec Interconnections
Regional
SRI and Weighted Components 2022
AtypicalEntities within
Date
Weather
Weighted
Weighted
Weightedthe
SRI
Conditions
Generation Transmission Load Loss
Interconnection
Gas Generator
OutagesQuébec10-Jul
2.55
0.56
1.89
0.10
NPCC
Wildfires

Table A.3 shows the top 10 SRI days for the Eastern and Québec interconnection over the last five years with the only
date in 2023 highlighted in red.

Rank
1
2
3
4
5
6
7
8
9
10

Table A.3: 2019–2023 Top 10 SRI Days Eastern and Québec Interconnections
Regional
SRI and Weighted Components
AtypicalEntities within
Date
Weather
Weighted
Weighted
Weightedthe
SRI
Conditions
Generation Transmission Load Loss
Interconnection
December 23,
Winter Storm
13.72
8.88
0.91
3.92
All
2022
Elliott
December 24,
Winter Storm
9.49
8.13
1.29
0.07
All
2022
Elliott
Cold Weather
February 16, 2021
8.32
4.11
0.59
3.63
MRO, RF, SERC
Event
High
MRO, NPCC, RF,
June 14, 2022
6.10
1.71
0.49
3.90 Temperatures
SERC, TRE
and Derecho
Widespread
April 1, 2023
5.85
0.74
0.64
4.46 Storms and
MRO, RF, SERC
Tornadoes
Hurricane
August 4, 2020
5.33
1.38
1.02
2.93
NPCC, RF, SERC
IsaiasUnnamedAugust 27, 2020
5.28
1.42
1.33
2.52
RF, SERC
Tropical StormHigh
MRO, NPCC, RF,
June 15, 2022
5.23
1.63
0.24
3.36 Temperatures
SERC, TRE
and Derecho
Cold Weather
February 15, 2021
5.16
3.63
0.55
0.99
MRO, RF, SERC
Event
October 29, 2020
4.62
1.03
1.42
2.17 Hurricane Zeta MRO, RF, SERC

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Appendix A: Supplemental Analysis at Interconnection Level

Western Interconnection
The 2023 cumulative SRI for the Western Interconnection (see Table A.4) shows a 4% decrease over the prior fouryear period of 2019–2022. The 2023 cumulative SRI was the second lowest among the five years analyzed.
Table A.4: Annual Cumulative SRI Western Interconnection
Year

Cumulative
Weighted
Generation

2019
2020
2021
2022
2023

421.7
390.8
426.8
423.7
423.2

Cumulative Cumulative
Weighted
WeightedTransmission Load Loss
104.4
100.6
104.0
93.4
74.3

73.9
73.0
96.9
61.6
68.8

AnnualCumulative
SRI

Average
Daily
SRI

599.9
564.4
627.7
578.7
566.3

1.64
1.54
1.72
1.59
1.55

The top 10 SRI days of the Western Interconnection for 2023 were distributed throughout the year as shown in Figure
A.3. None of the top 10 days that occurred in the Western Interconnection align with the top 10 SRI days reported
for North America. All days were driven by either generation or load loss.

Figure A.3: 2023 Western Interconnection Daily SRI with Top 10 Days Labeled, 90%
Confidence Interval

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Appendix A: Supplemental Analysis at Interconnection Level

Figure A.4 shows the Western Interconnection’s top ten SRI days in 2023 relative to the four prior years.

Figure A.4: Western Interconnection Top Annual Daily SRI Days Sorted Descending
Table A.5 details each component’s contribution to the top 10 SRI days for the Western Interconnection; WECC is the
only Regional Entity in the Western Interconnection.
Table A.5: 2023 Top 10 SRI Days Western Interconnection
SRI and Weighted Components 2022
Atypical Weather
Rank
Date
Weighted
Weighted
Weighted
Conditions
SRI
Generation
Transmission
Load Loss
1
26-Feb
5.38
1.30
0.17
3.91 Winter Storm
2
21-Feb
4.82
1.63
0.04
3.14 Winter Storm
325-Feb
4.04
1.20
0.64
2.20 Flooding
4
2-Mar
4.00
1.96
0.21
1.83 Winter Storm
5
1-Mar
3.72
2.66
0.44
0.62 Winter Storm
6
22-Feb
3.68
2.22
1.23
0.22 Winter Storm
7
24-Feb
3.61
2.61
0.96
0.05 Winter Storm
No discernible atypical
818-May
3.53
2.80
0.48
0.25
weather conditions
No discernible atypical
9
7-Nov
3.38
1.54
0.03
1.81
weather conditions
10

1-Jan

3.27

1.92

1.32

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71

0.02 Severe Storms

Appendix A: Supplemental Analysis at Interconnection Level

Table A.6 shows the top 10 SRI days for the Western interconnection over the last five years.

Rank
1
2
3
4
5
6
7
8
9
10

Table A.6: 2019–2023 Top 10 SRI Days Western Interconnection 85
SRI and Weighted Components
Atypical Weather
Date
Weighted
Weighted
Weighted
Conditions
SRI
Generation
Transmission
Load Loss
August 16, 2020
9.40
2.05
0.92
6.43 Extreme Heat
November 17, 2021
9.09
0.62
0.06
8.41 High winds and Special
Protection System
Operation
August 17, 2020
7.55
2.13
0.87
4.55 Extreme Heat
October 11, 2019
7.36
0.75
5.72
0.88 Saddle Ridge Fire
December 22, 2022
7.03
2.40
0.71
3.93 No discernible atypical
weather conditions
September 8, 2020
6.76
3.38
3.14
0.25
Wildfires
September 9, 2020
August 19, 2020
January 13, 2021
January 15, 2021

6.33
6.33
6.00
5.96

1.44
1.63
1.86
1.36

1.11
2.12
4.05
0.12

3.78
2.58
0.09
4.48

Wildfires
Extreme Heat
Northwest Winter Weather
Winter Storm

Extreme Day Analysis by Interconnection

The extreme-day analyses for transmission and generation for 2023 are presented by Interconnection. The maximum
TADS reported MVA capacity or GADS reported net maximum capacity for 2023 is shown in the upper-right cornersof Figures A.5–A.10. The largest outliers and extreme days correlating with NERC-wide extreme days have beenlabeled with any atypical weather conditions during those days. Interconnection extreme days that do not align with
NERC-wide extreme days are dated, but weather conditions are not identified. All dates are shown in UTC.

85 Values in this table do not align with prior years’ SOR reports due to a database error causing load-loss values to be shifted by two days.

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Appendix A: Supplemental Analysis at Interconnection Level

Figure A.5: Eastern and Québec Interconnections—Transmission Impacts during Extreme
Days of 2023

Figure A.6: Eastern and Québec Interconnections—Generation Impacts during Extreme Daysof 2023
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Appendix A: Supplemental Analysis at Interconnection Level

Figure A.7: Texas Interconnection—Transmission Impacts during Extreme Days of 2023

Figure A.8: Texas Interconnection—Generation Impacts during Extreme Days of 2023
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Appendix A: Supplemental Analysis at Interconnection Level

Figure A.9: Western Interconnection—Transmission Impacts during Extreme Days of 2023

Figure A.10: Western Interconnection—Generation Impacts during Extreme Days of 2023
NERC | State of Reliability | 2024
75

Appendix B: Acknowledgements
NERC would like to express its appreciation to the many people who provided direct technical support and identified
areas for improvement to this document as well as all the people across the industry who work tirelessly to keep thelights on every day.
NERC Industry Group Acknowledgements
Group
Officers
Reliability and Security Technical Chair: Greg Ford, Georgia System Operations Corporation
Committee
Vice Chair: Rich Hydzik, Avista
RSTC Sponsor: Darryl Lawrence, PA Office of Consumer Advocate
Performance Analysis
Chair: David Penney, Texas RE
Subcommittee
Vice Chair: Heide Caswell, Oregon Public Utilities Commission
Chair: Chris Moran, PJM
Events Analysis Subcommittee
Vice Chair: James Hanson, WECC
Generation Availability Data
Chair: Danny Small, City Utilities
System User Group
Vice Chair: Ken Sabourin, Sunflower Energy
Chair: Mike Knowland, ISO New England, Inc.
Electric Gas Working Group
Vice Chair: Daniel Farmer, Entergy
Misoperations Information Data Chair: Thomas Teafatiller, ReliabilityFirst
Analysis System User Group
Vice Chair: Stony Martin, SERC
Transmission Availability Data
Chair: John Idzior, ReliabilityFirst
System User Group
Vice Chair: Nick DePompei, SERC
Chair: Greg Park, WECC
Resources Subcommittee
RS Vice Chair and NPCC: Bill Henson, ISO-NE
Real-Time Operating
Chair: James Hartmann, Electric Reliability Council of Texas, Inc.
Subcommittee
Vice Chair: Timothy Beach, California Independent System Operator (RC West)
Reliability Assessment
Chair: Amanda Sargent, WECC
Subcommittee
Vice Chair: VacantSystem Protection and Control
Chair: Jefrey Iler, AEP
Working Group
Vice Chair: Bill Crossland, ReliabilityFirst

Name

Tony Burt
Alex Carlson
Christopher Claypool
Stephen Coterillo
Stephen Crutchfield
Leeth DePriest
Svetlana Ekisheva
Marie Golson
Brad Gordon
Bill Graham
Christian Henke
Marilyn JayachandranMaria KachadurianMark Lauby
Matthew Lewis
Robert Maddox

NERC Staff

Title

Physical Security Analyst
Senior Technical Publications Specialist
Data Science Analyst
Engineer II
Principal Technical Advisor and Coordinator of Reliability Assessments
Senior Engineer
Principal Data Science Advisor
Principal Technical Advisor
Senior Engineer
Manager, Bulk Power System Awareness
Digital Content Specialist
Manager, Advanced System Analytics and Modeling
Principal Analyst
Senior Vice President and Chief Engineer
Manager of Event Analysis
Senior Data Analyst
NERC | State of Reliability | 2024
76

Appendix B: Acknowledgements

NameWilliam G. (Marty) Martin
Kimberly Mielcarek
Darrell Moore
John Moura
Jack NorrisMark Olson
Margaret Pate
Donna Pratt
Elsa Prince
Wei Qiu
Darrel Richardson
Ed Ruck
Janet Sena
Rachel Sherrard
Sandy Shiflett
John (JP) Skeath
Nathan Strobel
Robert Tallman
Lee Thaubald

NERC Staff

Title
Principal Data Analyst
Vice President, Communications
Director, Situation AwarenessDirector, Reliability Assessment and Performance Analysis
Engineer II
Manager, Reliability Assessments
Consultant
Manager, Performance Analysis
Principal Technical Advisor, Reliability Standards
Lead Engineer
Principal Technical Advisor
Senior Engineer
Senior Vice President, Policy and External Affairs
Communications & Media Principal
Senior Program Specialist
Advance System & Mod Engineer II, Advanced System Analytics
Manager of Technical Publications
Senior Engineer
Senior Application Specialist

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77