Evaluating the Impact of 

the 2017 Solar Eclipse 

on U.S. Western Interconnection Operations

SOLAR ECLIPSE REPORT
ii SOLAR ECLIPSE REPORT

Santosh Veda, Yingchen Zhang, Jin Tan, Erol Chartan, Jonathan Duckworth, 

Nick Gilroy, Dylan Hettinger, and Sean Ericson

National Renewable Energy Laboratory

Jason Ausmus, Slaven Kincic, and Xiaping Zhang 

Peak Reliability

Guohui Yuan

U.S. Department of Energy Solar Energy Technologies Office

List of Acronyms

BA Balancing Authority

CAISO California Independent System Operator

CC Combined cycle

CE Continental Europe synchronous area

DPV Distribution-level PV Systems

ENTSO-E European Network of Transmission System

Operators for Electricity

HVDC High-voltage DC

ISO Independent system operator

MODIS Moderate Resolution Imaging 

Spectroradiometer

NASA National Aeronautics and Space 

Administration

NSRDB National Solar Radiation Database

NERC North American Electric Reliability 

Corporation

NREL National Renewable Energy Laboratory

NSS Nordic synchronous system

PDCI Pacific DC Intertie

PV Photovoltaic 

RC Reliability Coordinator

SAMPA Solar and Moon Position Algorithm

TOP Transmission Operating Plan

TSO Transmission system operator (European 

nomenclature)

WECC Western Electric Coordinating Council

UPV Utility-scale PV systems

Notice 

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sponsored by an agency of the United States 

government. Neither the United States government nor 

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government or any agency thereof. The views and 

opinions of authors expressed herein do not necessarily 

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SOLAR ECLIPSE REPORT iii

Executive Summary

With support from the U.S. Department of Energy Solar Energy Technologies Office, the National Renewable Energy 

Laboratory (NREL) partnered with Peak Reliability to evaluate the impact of the August 21, 2017, total solar eclipse 

on reliability and electric grid operations in the Western Electricity Coordinating Council (WECC) territory. As a North 

American Electric Reliability Corporation Reliability Coordinator, Peak Reliability manages the grid reliability across all or 

parts of the14 western United States, British Columbia, and the northern region of Baja California, Mexico. Peak Reliability 

used inputs from the study to augment its own analysis for preparing transmission operating plans for the day of the 

eclipse. Peak Reliability also provided NREL with data from across its footprint to uncover important insights into the 

impact of the eclipse from the penetration of photovoltaics (PV) along its path.

The 2017 total solar eclipse came and went without causing any issues to the operation of the North American electric 

power system. This report presents the results of NREL’s studies performed before and after the August 21 event. In a preevent analysis, NREL researchers focused on the spatial and temporal profile of the eclipse and how the output of PV sites 

across WECC would be affected. Although the size and location of utility-scale PV (UPV) sites are known and their outputs 

are monitored, distributed PV (DPV) (e.g., rooftop solar) poses a greater challenge for grid operations because of its lack 

of visibility. 

The estimated installed capacity of UPV and DPV across the WECC region is 15,800 MW (without concentrating solar 

power plants) and 9,200 MW, respectively. NREL used databases developed through previous efforts funded by the U.S. 

Department of Energy to determine how much DPV was present at the substation level and then estimated the impact of 

the eclipse on its output. This geospatial analysis assumes a typical meteorological day from NREL’s typical meteorological 

year database. NREL researchers estimated that during the peak of the event, the loss of PV would be around 5.2 GW, with 

UPV loss at 4 GW and the rest from DPV. 

The second part of the analysis was a simulation of production costs. Using the results from the geospatial study, the 

economic dispatch and unit commitment strategies were evaluated to see how the other generators would be redispatched. The analysis showed that the loss of PV generation can be easily compensated by the existing generation 

fleet, with the natural gas fleet picking up the majority of the slack because of its flexibility. The change in system 

production costs were minimal. The third part of the analysis consisted of transient simulations to assess the stability and 

reliability of grid operations. No reliability concerns were identified, even for large system disturbance events. The system 

also exhibited high damping capabilities to mitigate inter-area oscillations. 

In the post-event analysis, NREL researchers used the data collected by Peak Reliability to uncover additional insights 

into the impact of the eclipse on actual PV output, system loading, transmission flows, and generation by fuel types and 

by utility areas. The loss of UPV estimated during the pre-event analysis matches the observed values. Because there is 

insufficient data to measure the loss of DPV, the loss estimation was used to further study the impact of the eclipse on 

load as a result of non-PV factors. The production cost simulation estimated that natural gas and hydro resources would 

be most responsive, given their fast ramp rates, relative to their output at the start of the eclipse. A similar effect was 

observed with natural gas generators, which increased their output by 18%, and hydro power, which increased by 15%.

NREL researchers are working to extend this analytical approach to study the impacts of future large-scale disturbances 

caused by solar eclipses and weather storms.
iv SOLAR ECLIPSE REPORT

Table of Contents

1. Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

2. Literature Review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

2.1 2015 European Total Eclipse . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

2.1.1 Pre-event Eclipse Simulation Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

2.1.2 Mitigation Countermeasures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

2.1.3 Grid Operation on March 20, 2015 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

2.1.4 Other Considerations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

2.1.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

2.2 Impact Studies for the 2017 Eclipse . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

2.2.1 The California Independent System Operator Report . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

2.2.2 The North American Electric Reliability Corporation Report . . . . . . . . . . . . . . . . . . . . . . . . . 8

2.2.3 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

3. Pre-Event Impact Estimation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

3.1 Spatiotemporal Analysis of Photovoltaics Generation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

3.1.1 Distributed Photovoltaics Capacity Extrapolation and Aggregation . . . . . . . . . . . . . . . . . . . . 9

3.1.2 Utility-Scale Photovoltaics Capacity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

3.1.3 Solar Insolation Calculation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

3.1.4 Photovoltaics Generation Calculation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

3.1.5 Impact of Eclipse on Photovoltaics Production . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

3.2 Production Cost Simulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

3.2.1 Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

3.2.2 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

3.3 Transient Simulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

3.3.1 Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

3.3.2 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18

3.4 Peak Reliability Eclipse Preparation Efforts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21

4. Post-Event Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22

4.1 Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22

4.2 Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22

4.2.1 Determining Baseline for Grid Operations on August 21 . . . . . . . . . . . . . . . . . . . . . . . . . . 22

4.2.2 Determining Impact on Photovoltaics Output . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24

4.2.3 Determining Impact on System Loading . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28

4.2.4 Impact on System Reserves . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29

4.2.5 Impact on Western Electricity Coordinating Council Path Flows . . . . . . . . . . . . . . . . . . . . . . 30

4.2.6 Impact on Generation Dispatch . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32

4.2.7 Impact on Generation by Fuel Type and Area . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34

4.2.8 Peak Reliability Operations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34

5. Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36

6. References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36

Appendix A – WECC Path Definition and Ratings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37

Appendix B – Generation by Fuel Type for Each Utility Area . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38
SOLAR ECLIPSE REPORT v

List of Figures

Figure 1. Transmission lines of the WECC region . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 

Figure 2. Path of the August 21 solar eclipse . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

Figure 3. European PV output variation during solar eclipse . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

Figure 4. Estimated minute-to-minute ramping rate with and without solar eclipse . . . . . . . . . . . . . . . . . . . 4

Figure 5. CAISO forecast of grid-connected solar production on August 21, 2017 Eclipse . . . . . . . . . . . . . . . . 7

Figure 6. Flowchart of the eclipse study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

Figure 7. Cumulative DPV capacity in WECC . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

Figure 8. DPV cumulative WECC generation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

Figure 9. UPV cumulative WECC generation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

Figure 10. Impact of eclipse on UPV and DPV sites . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

Figure 11. Aggregate headroom for the CC fleet for August 21, 2017 . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

Figure 12. Aggregate footroom for the CC fleet for August 21, 2017 . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

Figure 13. Change in energy production by generator type due to the eclipse . . . . . . . . . . . . . . . . . . . . . 15

Figure 14. Identified contingencies for stability studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

Figure 15. Transmission flows and bus frequencies at selected locations (Palo Verde) . . . . . . . . . . . . . . . . . 18

Figure 16. Transmission flows and bus frequencies at selected locations (PDCI) . . . . . . . . . . . . . . . . . . . . . 19

Figure 17. Transmission flows and bus frequencies at selected locations (Intermountain Power Plant) . . . . . . 20

Figure 18. Transmission flows and bus frequencies at selected locations ( California-Oregon Intertie) . . . . . . . 21

Figure 19. Total generation at WECC-level . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23

Figure 20. Total load at WECC-level . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23

Figure 21. Loss of distributed PV during eclipse (estimated) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24

Figure 22. UPV generation at WECC-level . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25

Figure 23. Minimum PV impact on eclipse day . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26

Figure 24. Maximum PV impact on eclipse day . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26

Figure 25. WECC-level aggregate PV output . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27

Figure 26. WECC-level Aggregate PV output normalized . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27

Figure 27. Actual and net load at WECC-level on eclipse day . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28

Figure 28. Actual and net load impact due to eclipse . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29

Figure 29. Total reserves at WECC-level . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30

Figure 30. Affected WECC paths . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31

Figure 31. Transmission flow trends along affected paths . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31

Figure 32. Transmission flows along affected paths . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32

Figure 33. Total generation by affected utility areas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32

Figure 34. Generation trends in affected utility areas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33

Figure 35. Total WECC generation by fuel types . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33

Figure 36. Generation trends by fuel type . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34

Figure 37. Solar eclipse display for real-time monitoring (internal) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35

Figure 38. Solar eclipse display (external) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35

List of Tables

Table 1. Eclipse Path and Times . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

Table 2. 2015 European Solar Eclipse Countermeasures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

Table 3. CAISO Grid Protection Plan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

Table 4: Utility Areas in WECC with Significant DPV Capacities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

Table 5. WECC-Coordinated Underfrequency Load-Shedding Plan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

Table 6. Definition and Ratings of Affected WECC Paths . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30
1 SOLAR ECLIPSE REPORT

1. Background

Funded by the U.S. Department of Energy Solar Energy Technologies Office, the National Renewable Energy Laboratory 

(NREL) partnered with Peak Reliability to estimate the impact of the August 21, 2017, transcontinental solar eclipse on the 

reliability and operations of the western U.S. electric power grid. The objectives of this project were to:

1. Learn from past grid operation experience to prepare for the solar eclipse event.

2. Develop tools to investigate the spatiotemporal evolution of the solar eclipse, its impact on renewable power 

generation, and the effect on grid operations and system reliability during these conditions.

3. Extend the framework and tools to perform extreme event analysis that can be translated to other significant 

weather events.

This report covers the pre-event and post-event analysis, which addresses objectives 1 and 2. The analysis was performed 

in partnership with Peak Reliability and covers the western United States, as shown in Figure 1. A follow-up report will 

focus on the framework. 

On Monday, August 21, 2017, North America experienced a total solar eclipse from one coast to another. The total eclipse 

was first observable in Oregon at 10:15 a.m. PDT and was observed in South Carolina at 2:49 p.m. EDT. Though the path 

of totality was a relatively thin ribbon that extended about 70 miles wide, the rest of the continent experienced a partial 

eclipse. Although the peak of the eclipse lasted only a few minutes at locations along the path of totality, the darkness 

from the penumbra lasted a few hours before and after the peak. The U.S. Energy Information Administration estimated 

that more than 21 GW of installed photovoltaic (PV) systems would be affected [1].

Because total solar capacity on the grid has increased from 5 MW in 2000 to more than 42,619 MW in 2016 [2], such an 

extreme solar eclipse event called for further evaluation and analysis. With increasing penetrations of PV systems, it is 

important that grid operators understand the impact of an eclipse like the North American 2017 event on PV output and 

grid operations to undertake adequate preparatory measures. 

Source: Western Electricity Coordinating Council (WECC) 

Figure 1. Transmission lines in the WECC region. 
SOLAR ECLIPSE REPORT 2

Table 1. Eclipse Path and Times

Eclipse Begins Totality Begins Totality Ends Eclipse Ends

Madras, OR 09:06 a.m. 10:19 a.m. 10:21 a.m. 11:41 a.m. PDT

Idaho Falls, ID 10:15 a.m. 11:33 a.m. 11:34 a.m. 12:58 p.m. MDT

Casper, WY 10:22 a.m. 11:42 a.m. 11:45 a.m. 01:09 p.m. MDT

Lincoln, NE 11:37 a.m. 01:02 p.m. 01.04 p.m. 02:29 p.m. CDT

Jefferson City, MO 11:46 a.m. 01:13 p.m. 01:15 p.m. 02:41 pm. CDT

Carbondale, IL 11:52 a.m. 01:20 p.m. 01:22 p.m. 02:47 p.m. CDT

Paducah, KY 11:54 a.m. 01:22 p.m. 01:24 p.m. 02:49 p.m. CDT

Nashville, TN 11:58 a.m. 01:27 p.m. 01:29 p.m. 02:54 p.m. CDT

Clayton, GA 01:05 p.m. 02:35 p.m. 02:28 p.m. 04:01 p.m. EDT

Columbia, SC 01:13 p.m. 02:41 p.m. 02:44 p.m. 04:06 p.m. EDT

Source: National Aeronautics and Space Administration/Goddard/SVS/Ernie Wright 

Figure 2. Path of the August 21, 2017, solar eclipse. 
3 SOLAR ECLIPSE REPORT

2. Literature Review

This section presents a review of previous eclipse studies, most notably the transcontinental European eclipse in 2015 

and lessons from the 1999 partial eclipse in Great Britain. Given the high penetration of PV in Germany and Italy, regions 

that witnessed the eclipse, European transmission operators had undertaken special measures to prepare for the 2015 

eclipse. Studies performed by the California Independent System Operator (CAISO) and the North American Electric 

Reliability Corporation (NERC) are also presented in this section.

2.1 2015 European Total Eclipse 

On March 20, 2015, a solar eclipse affected continental Europe. The eclipse started at 8:01 a.m. UTC in the western part 

of Portugal and ended at 11:58 a.m. UTC in the eastern part of Romania. For the first time, the eclipse had a significant 

impact on the operation of the European power system because of the fast growth in PV in the recent past.

2.1.1 Pre-Event Eclipse Simulation Analysis

Before the 2015 event, the European Network of Transmission System Operators for Electricity (ENTSO-E) community 

produced an analysisto assess the operational impacts from the 2015 total solar eclipse and developed a plan to mitigate 

these impacts [3]. Because of the widely distributed geographic locations—and therefore varying eclipse impacts 

on solar production—ENTSO-E conducted this study by dividing the grid into three areas: the continental Europe 

synchronous area (CE), Nordic synchronous system (NSS), and Great Britain synchronous area.

The main focus was on CE because the majority of the solar installation capacity and most significant effects of the eclipse 

were located in this area. As of 2014, the PV installation capacity in Europe had reached 90 GW, wherein Germany (38.3 

GW), Italy (18.5 GW), France (5.6 GW), and Spain (4.8 GW) were the leading countries in terms of installation. Because of 

the large amount of PV installed, the transmission system operators (TSOs) in Italy and Germany were the most affected.

The assessment was based on input from different countries, such as an estimation of the total installed PV capacity by 

the date of the eclipse, an estimation of the energy from PV that would be produced during the hours of the eclipse, 

and an estimation for the energy demand. ENTSO-E also estimated the solar obscuration production during the eclipse 

by considering the radiation factor and obscuration factors. In the case of a clear sunny day, the eclipse was expected to 

cause a reduction in solar power by more than 34 GW, as shown in Figure 3. 

0

10,000

20,000

30,000

40,000

50,000

60,000

MW

08:00 08:30 09:00 09:30 10:0010:3011:00 

Clear sky

Solar eclipse

Dierence

Figure 3. European PV output variation during solar eclipse
SOLAR ECLIPSE REPORT 4

As shown in Figure 4, the maximum minute-to-minute ramping-down rate exceeded -400 MW/minute and the rampingup rate after the solar eclipse was almost +700 MW/minute, which are two to four times higher than the normal daily PV 

ramping rates from sunrise and sunset, respectively [3]. Among these countries, 50% (16.9 GW) of the infeed reduction in 

the system was expected in Germany, and the maximum ramping-down rate and ramping-up rate were -273 MW/minute 

and +361 MW/minute, respectively. In Italy, the estimated reduction was 21% (7.2 GW), with a maximum ramping-down 

rate of -111MW/minute and ramping-up rate of +159 MW/minute.

MW/1min

0

-400

-600

-200

200

400

600

800

Gradient solar eclipse MW/min

Gradient clear sky MW/min

08:00 08:30 09:00 09:30 10:00 10:30 11:00

UTC

Figure 4. Estimated minute-to-minute ramping rate with and without the solar eclipse

Considering the simulation analysis, the main challenge for grid operation is the fast change in PV power generation. It 

was estimated that generation would decrease by 20 GW within 1 hour and increase by nearly 40 GW after the maximum 

impact of the eclipse. This situation could pose serious challenges to the regulating capability of the interconnected 

power system in terms of available regulation capacity, regulation speed, and geographical location of reserves.

2.1.2 Mitigation Countermeasures

The European grid is well-recognized as a strong grid capable of supporting power flow exchange based on flexible 

market operation among TSOs from different countries. To reduce the complication of control and prevent event 

propagation, TSOs were encouraged to limit the exchange and be prepared for emergency support. In addition, the dayahead forecast of PV is particularly important for the management of power generation during an eclipse event. Careful 

preparation and coordination of solar forecasts were required among individual TSOs as well as careful preparation and 

coordination among TSOs and distribution system operators. 

The recommended countermeasures for the March 20, 2015, event were made at two levels: CE coordination and 

individual TSOs. Primary recommendations included the preparation of extra reserve, strategic use of pumped storage 

power plants, the reduction in the interchange among TSOs, and the strengthening of management and coordination 

across CE.

The main countermeasures are summarized in Table 2. 
5 SOLAR ECLIPSE REPORT

Table 2. 2015 European Solar Eclipse Countermeasures

All TSOs TSOs in Germany Terna (Italy)

Higher 

Reserves

Some TSOs increased amount of 

primary, secondary, and tertiary 

control reserves

Procured approximately 

double the amount of 

reserves

Established a special 

operational concept for 

activation of reserves 

and emergency reserves

Strategic Use 

of Pumped 

Storage 

Power Plants

Some TSOs used strategic pumped 

storage power plants in real-time 

operation

Adjust 

Operation 

Rule

Reduced the interchange of HVDC 

for the NSS, Great Britain, and CE 

regions

Increased synchronous area 

independence

Minimized planned outages 

Minimized the area control error 

in nearly real time rather than at 

typical intervals of 15 minutes 

Reduced the total net 

transfer capacity on 

the northern border 

of Italy to 1,000 MW

Market Marketed the forecasted 

amount of PV at the 

quarterly hour market

Implemented a 

preventive decrease 

of planned PV 

production in the 

day-ahead market

Management 

and

Coordination

Raised awareness and informed 

market players

Held an operational teleconference

Held a backup teleconference 

among system operation managers

Provided extra training of control 

room operators and exercises on 

coordination procedures

Hired additional operator staffing 

during the event

Coordinated continuous 

communications among control 

rooms in CE and the NSS
SOLAR ECLIPSE REPORT 6

Because the TSOs in Italy and Germany had the highest relative impact on their available reserves, they took additional 

market response mitigation measures. TSOs in Germany broadcasted the forecasted amount of PV at the 15-minute 

market to ensure that they only needed to manage the difference between the quarterly hour market and the real feed-in 

with a high gradient in real time. Meanwhile, TSOs in Germany increased the additional upward/downward reserve, which 

is about twice the reserve for their normal operation. The TSO in Italy, Terna, had a preventive curtailment of planned PV 

production in the day-ahead market of approximately 4.4 GW through shutdowns between 7 a.m. and 2 p.m. CEST.

NSS operated independently during the eclipse event and was not significantly affected by the reduction in PV power 

production. The role it took was to provide regulation flexibility to support CE and maintain communications with 

neighboring CE TSOs. In operation, NSS was encouraged to limit the exchange with CE and NSS to a level that would 

allow energy security to CE in the unlikely event of a blackout.

Finally, increasing awareness during the event was also important from a management perspective. Therefore, the TSOs 

set up an extraordinary operational coordination the day before and during the eclipse, including day-ahead and realtime teleconferencing to coordinate PV forecasts, real-time frequency management, reserve exchanges, and power 

flow management.

2.1.3 Grid Operation on March 20, 2015

The weather conditions on March 20, 2015, the day of solar eclipse event, were cloudier than originally anticipated, which 

led to a less severe reduction in PV generation compared to a clear-sky condition. Thus, the observed ramp rates were 

lower than what was estimated during the pre-event analysis. In Germany, the actual solar output was 21 GW [4], and 

the change in Great Britain was about 850 MW, with no significant impact on grid operations. The quality of frequency 

regulation during the eclipse time frame was observed to be very good [5]. Note that increased reserve procurement 

during the eclipse event resulted in higher power prices. No significant changes were observed in the NSS. With Terna 

enforcing curtailment in Italy, the impact was muted.

2.1.4 Other Considerations

Residual Demand Effect

The eclipse effect on energy demand partially depends on human behavior, e.g., halting normal activities to observe 

the eclipse and the transient cooling effect. These two effects lower the actual energy demand. When distributed PV is 

present, an eclipse reduces the output from these sources, leading to an apparent increase in energy demand. Thus, these 

two counteract each other during an eclipse.

In the analysis of Great Britain, the change in residual demand dominated the PV effect. The greatest rates of change were 

caused by reduced demand rather than reduced solar insolation, with a maximum minutely rate of change of -300 MW/

minute, but with typical values of -200 MW/minute before the maximum eclipse and +200 MW/minute after.

During the partial eclipse in August 1999, Great Britain experienced a 3-GW drop in demand that was attributed to 

people watching the event. Because there was such a high level of media interest in the 2015 solar eclipse, it was 

assumed that many people would again be watching the 2017 eclipse and there would be a similar drop in energy 

demand [6]. 

Impact on Wind Speed

Some discernible changes in meteorological signals during the eclipse were detected by comparing actual weather 

measurements with the predictions from a high-resolution spatiotemporal meteorological model ignorant of the eclipse 

[7]. These included changes to wind speeds, variability, and direction. For example, during the August 11, 1999, solar 

eclipse, the measurements show that the transient eclipse zone experienced temperature decreases of up to 3°C, a mean 

regional wind speed decrease of 0.7 m/s during the maximum eclipse hour with a mean anticlockwise wind direction 

change of 17°[8]. During the 2015 eclipse in Great Britain, wind generation dropped by around 10% (500 MW) because of 

the fall in wind speeds associated with the eclipse [6]. 
7 SOLAR ECLIPSE REPORT

2.1.5 Summary

Pre- and post-event analysis of the 2015 European total eclipse indicated that there was “a great deviation in the amount 

of solar generation that [is] available before, during, and post eclipse which cause[s] the need for far more advanced 

coordination of primary, secondary, and tertiary reserves across Europe within a reduced time frame (faster than 10–15 

minute intervals)” [2].

Through pre-risk evaluation, accurate forecasting, properly adjusted operational planning, improving reserve 

management, and using market rules to improve generation flexibility, the European grid operated safely during this 

event. Nevertheless, these mitigation strategies—acquiring additional reserves in particular—do have a significant cost, 

leaving such measures to be reserved for exceptional circumstances.

For Italy, the cost of the additional reserves during the solar eclipse has been estimated at €140,000, for Germany at 

€3.6 million, and for Czechia at €215,000. Note that because of the different mechanisms for reserve procurement, the 

prices for different countries are not comparable. The general conclusion is that the disconnection of PV resulted in 

higher power prices, and the additional reserve requirement resulted in higher service prices.

2.2 Impact Studies for the 2017 Eclipse

2.2.1 The California Independent System Operator Report 

In August 2017, CAISO predicted that it would be affected by a partial eclipse between 9:02 a.m. and 11:54 p.m. PDT, 

obscuring 62% to 76% of the sun from Southern California to Northern California, respectively [9]. CAISO has nearly 

10,000 MW of installed capacity of commercially operational utility-scale PV (UPV) within the balancing area. In addition, 

the California Energy Commission estimated that there would be more than 5,800 MW of rooftop solar installed in CAISO 

by August 2017. To maintain grid stability, CAISO identified the eclipse trajectory, estimated UPV and DPV installed 

capacities, and developed mitigation strategies to minimize risk. 

Initial estimates showed that at the peak of the eclipse, UPV solar production within CAISO would be reduced from an 

estimated 8,754 MW to 3,143 MW before returning to 9,046 MW. The solar ramping-down rate was estimated at -70 MW/

minute and ramping-up rate at 98 MW/minute (see Figure 5). By comparison, the estimated ramping-up rate during a 

similar period was 12.6 MW/minute on a normal clear day; however, DPV was expected to have a smaller effect. Assuming 

a clear sky during the eclipse, a total net load increase of around 1,365 MW was expected because of the loss of DPV 

generation. CAISO developed a net load forecast model that took rooftop solar generation into account.

∆ +98 MW/min

(5,903 MW)

7,337 MW @ 9:00 8,754 MW @ 10:22 

3,143 MW @10:22

5,611 MW

0

1,000

2,000

3,000

4,000

5,000

6,000

7,000

8,000

9,000

10,000

MW Anticipated Solar Production 06:00 06:10 06:20 06:30 06:40 06:50 07:00 07:10 07:20 07:30 07:40 07:50 08:00 08:10 08:20 08:30 08:40 08:50 09:00 09:10 09:20 09:30 09:40 09:50 10:00

10:1010:2010:3010:40 10:5011:00 11:10 11:2011:3011:4011:50

9,046 MW @ 11:56

Obscured MW

8/17 scaled-up production

∆ -70 MW/min

(4,194 MW)

Figure 5. CAISO forecast of grid-connected solar production for the August 21, 2017, eclipse
SOLAR ECLIPSE REPORT 8

Like the 2015 European total eclipse, the main challenges for CAISO were potential large ramping rates and energy 

imbalance. Faster-than-normal ramping during the eclipse would increase the burden on other generators, having a 

direct impact on CAISO’s regulation capability in terms of available regulation capacity, speed, and location of reserves. 

The energy imbalance market would be impacted because of an additional 866 MW of UPV shortfall. 

Informed by the 2015 European total eclipse and analysis, CAISO proposed a grid protection plan to maintain grid 

reliability and encouraged coordination across the Western Electricity Coordinating Council (WECC). Table 3 summarizes

the proposed mitigation measures. 

Table 3. CAISO Grid Protection Plan

Reserves procurement Gas supply needs coordination. 

Flex-ramp usage Scheduling coordinator interaction 

Special operating procedures WECC/Peak Reliability coordination 

Use of energy imbalance market transfer capability Hydro generation 

Internal market simulation Potential use of Flex Alert 

Day +2 conference bridge Market participant coordination 

2.2.2 The North American Electric Reliability Corporation Report 

NERC combined region-specific hourly load estimates, generating unit capacity, and solar data from SEIA and GTM 

Research’s U.S. Solar Market Insight 2016 Q3 report to estimate the impact of the August 21, 2017, eclipse on gridconnected PV capacity across North America [2].

From 2013 – 2015, the reported load for each Monday in August was used as the set of possible hourly data points. For 

PV generation, an assumption was made to use the aggregated capacity of a facility and three representative hourly 

generation percentages to map the general shape of PV production.

The report found that the top four states that would require advanced system coordination for operations prior to the 

eclipse, during the eclipse, and after the eclipse were Utah, California, Nevada, and North Carolina. In some parts of each 

of these states, a 0.9 obscuration would be observed. (Utah had a maximum obscuration of 0.95, and Nevada and North 

Carolina would experience a total eclipse).

Where peak eclipse and peak demand coincided, the ramping-up and ramping-down rates required Balancing 

Authorities (BAs) with minimal standby energy storage to be challenged in maintaining grid stability. Following 

Germany’s response to the 2015 eclipse, disconnecting UPV generators from the grid would mitigate instability caused by 

extreme ramping for the 2017 eclipse.

Peak eclipse obscuration occurred around 10 a.m. PDT for CAISO, many hours before peak demand and peak generation 

typically occurs in the late afternoon, therefore mitigating the ramping and balancing concerns. California and North 

Carolina, however, were identified as states that would require advanced planning and operating coordination for the 

August 21, 2017, eclipse because of their large PV installation capacity. NERC highlighted the need to coordinate the 

distributed energy resources for system protection and perform advanced planning and operating coordination.

2.2.3 Summary

Though CAISO and NERC relied on simple assumptions and simulations based on physical energy balance, both suggested 

significant changes to generation and load profiles in high PV areas during the eclipse event. To maintain grid stability, 

coordinated pre-event planning with tightly coupled cross-region communications during the event was required and 

proved beneficial by the response to the 2015 eclipse. This NREL report complements the CAISO and NERC reports by 

providing a detailed geospatial analysis followed by detailed production simulation and transient simulation studies. 
9 SOLAR ECLIPSE REPORT

3. Pre-Event Impact Estimation

The NREL team developed the detailed approach shown in Figure 6 for studying the impact of an eclipse on grid 

operations. This framework is flexible, developed with the intention to be extended to other wide-area phenomena that 

could similarly impact grid operations: 

• Spatiotemporal analysis to estimate PV output

• Production cost simulation to estimate generation redispatch

• Transient simulation to assess grid stability.

UPV, DPV site location and 

capacities, weather

Spatiotemporal analysis Set points for PV sites

Grid-wide generation 

Dispatch

Grid stability contingency 

analysis

Production simulation studies

Phasor models Transient simulation studies

Production models

Study owchart

Figure 6. Flowchart of the eclipse study

3.1 Spatiotemporal Analysis of Photovoltaic Generation

NREL compared uPV and DPV minute-by-minute generation profiles for a typical meteorological day with and without 

the effects of the August 21, 2017, eclipse event on solar insolation.

3.1.1 Distributed Photovoltaic Capacity Extrapolation and Aggregation

The data for DPV installed capacity were derived from the Lawrence Berkeley National Laboratory Tracking the Sun report 

[10], which examined trends in the installed price of grid-connected PV systems in the United States by summarizing DPV 

systems through 2015. Of the 821,188 systems considered in Tracking the Sun, 338,386 were geocoded to precise latitude 

and longitude coordinates, 293,996 were geocoded to a zip code or utility service territory centroid, and 188,806 were 

outside the study area or removed because of incomplete information. The remaining 632,382 installations were then 

aggregated to the nearest substation location; general system characteristics such as array type, average tilt, and azimuth 

grouped by array type, generalized latitude, and longitude were retained.
SOLAR ECLIPSE REPORT 10

To estimate the total DPV capacity in WECC, the 2015 Tracking the Sun data were extrapolated using several growth rates 

derived from state-level Solar Market Insight 2017 Q2 data [11]. First, the total Tracking the Sun capacity from 2015 was 

linearly extrapolated to 2017 using the Solar Market Insight annual growth rate from 2015–2016 and 2016–2017. The 

resulting capacity was further extrapolated to 2017 Q2 using an average quarterly growth from Q1–Q2 for years 2014– 

2017. Finally, a daily growth rate for Q3 was determined from Q2–Q3 growth rates from 2014–2016. This allowed the 

extrapolation to consider both medium- and short-term growth rates. Rates were applied based on a per-state allocation 

across all of WECC. The extrapolation results in the total estimated DPV capacity in WECC grew from 6,000 MW at the end 

of 2015 to 9,200 MW on August 21, 2017.

0

2,000

4,000

6,000

8,000

10,000

MW WECC Cumulative DPV Capacity

August 21, 2017

Q1–2017Q2–2017

1998199920002001200220032004200520062007200820092010201120122013201420152016

The DPV sites were then aggregated to the closest transmission substation. The objective was to disaggregate the 

loading at each substation into actual loading and DPV generation. This approach would allow the NREL team to study 

the impact on PV output more accurately. The utility areas with significant DPV penetration are shown in Table 4. 

Table 4. Utility Areas in WECC with Significant DPV Capacities

Utility Area Estimated DPV 

Capacity (MW) Utility Area Estimated DPV Capacity (MW)

Arizona Public Service 2,160 PacifiCorp East 57

Bonneville Power Administration 109 Pacific Gas and Electric 1,513

El Paso 261 Public Service Company of Colorado 101

Imperial Irrigation District 201 Southern California Edison 2,016

Idaho Power Company 453 San Diego Gas and Electric 522

Los Angeles Department of 

Water and Power 1,077 Sierra 97

Public Service Company 

of New Mexico 449 Western Area Power Administration 81

Nevada Power Company 169

Figure 7. Cumulative DPV capacity in WECC
11 SOLAR ECLIPSE REPORT

3.1.2 Utility-Scale Photovoltaic Capacity

The UPV capacity estimates were provided by the WECC Transmission Expansion Planning Policy Committee. The 

WECC Transmission Expansion Planning Policy Committee conducts an annual transmission system study program as 

a component of WECC’s regional transmission planning process in accordance with WECC’s broader mission to assess 

the reliability impacts of the Western Interconnection under varying economic, technological, and regulatory (policy) 

conditions. Installed UPV capacity is implemented in baseline PLEXOS models. The total UPV capacity (excluding 

concentrating solar power plants) was estimated at 15.8 GW.

3.1.3 Solar Insolation Calculation

Insolation profiles for a typical clear sky on August 21, 2017, were calculated at each generator location using the Solar 

and Moon Position Algorithm (SAMPA) [12]. A profile was created for a typical day without an eclipse event and with a 

total eclipse.

Weather data were obtained from NREL’s National Solar Radiation Database (NSRDB) typical meteorological year 

approach and supplemented with atmospheric data from the National Aeronautics and Space Administration’s (NASA’s) 

Moderate Resolution Imaging Spectroradiometer (MODIS) database. The 2012–2016 MODIS data were averaged, and the 

NSRDB data were linearly interpolated from hourly values to minute values.

3.1.4 Photovoltaic Generation Calculation

NREL’s System Advisory Model v2016.08.01 with PVWatts v5 was used to calculate minute generation profiles for each 

characteristic UPV and DPV system at each generator location. Again, profiles for both eclipse and non-eclipse days were 

generated using the SAMPA-derived insolation profiles. Generation was calculated assuming typical meteorological 

weather conditions in both scenarios.

3.1.5 Impact of Eclipse on Photovoltaic Production

3.1.5.1 Distributed Photovoltaics

DPV was estimated to reach a peak generation of less than 8 GW across WECC. Also, by 9 a.m. PDT, generation dropped 

until 10:30 a.m. PDT, when it began growing rapidly until 1 p.m. PDT (see Figure 6). The maximum loss of DPV production 

across WECC reached 1.9 GW.
SOLAR ECLIPSE REPORT 12

02:00 04:0006:0008:0010:0012:00 14:00 16:0018:00 20:00 22:0024:00

0

1,000

2,000

3,000

4,000

5,000

6,000

8,000

7,000

MW

DPV Cumulative WECC Generation 

August 21, 2017

No eclipse

Eclipse

Figure 8. DPV cumulative WECC generation

3.1.5.2 Utility-Scale Photovoltaics

Across WECC, UPV saw a peak generation of more than 12 GW. The effects of the solar eclipse on generation became 

apparent around 9 a.m. PDT, when generation began to decrease to a nadir near 7 GW by 10:15 a.m. PDT. Generation 

then increased rapidly until 1 p.m. PDT, when the effects dissipated, and generation returned to non-eclipse scenario 

rates (Figure 7). The maximum loss of UPV production across WECC is estimated at 4 GW.

0

2,000

4,000

6,000

8,000

10,000

12,000

MW

UPV Cumulative WECC Generation 

August 21, 2017

No eclipse

Eclipse

02:00 04:0006:0008:0010:0012:00 14:00 16:0018:00 20:00 22:0024:00

Figure 9. UPV cumulative WECC generation
13 SOLAR ECLIPSE REPORT

3.1.5.3 Combined Utility-Scale Photovoltaics and Distributed Photovoltaics

The impact of the solar eclipse on the UPV and DPV sites combined is presented in Figure 10. The eclipse peak, from PV 

output reference data, occurred at 10:21am PDT. The total decrease in PV production across WECC reached 5.5 GW. 00:00 00:25 00:50 01:15 01:40 02:05 02:30 02:55 03:20 03:45 04:10 04:35 05:00 05:25 05:50 06:15 06:40 07:05 07:30 07:55 08:20 08:45 09:10 09:35 10:00 10:25 10:50 11:15 11:40 12:05 12:30 12:55 13:20 13:45 14:10 14:35 15:00 15:25 15:50 16:15 16:40 17:05 17:30 17:55 18:30 18:45 19:10 19:35 20:00 20:25 20:50 21:15 21:40 22:05 22:30 22:55 23:20

23:45 

-5,000

0

5,000

10,000

15,000

20,000

25,000

MW

08/21/2017 Solar Eclipse–Total UPV and DPV Generation

No solar eclipse

Solar eclipse

Dierence

Figure 10. Impact of eclipse on combined UPV and DPV sites

3.2 Production Cost Simulation 

The impact of the solar eclipse was examined using a standard differential study methodology. Two scenarios were 

simulated: the first was a standard operation model for WECC as it exists today, and the second was the same standard 

operation model but with the solar eclipse limiting the output of solar generators, both DPV and UPV. 

The PLEXOS model simulates the real-time operations, consisting of a real-time security-constrained unit commitment 

and economic dispatch problem. This model was used to determine the operating schedules (commitments and 

dispatch) of all generation plants in the model at a 5-minute resolution. 

3.2.1 Approach

The solar generation profiles, both with consideration of the eclipse and without, were calculated based on the 

methodology described in Section 2.2. The operation model was simulated in the commercially available software 

PLEXOS Integrated Energy Model. The simulations started from August 18 to allow the simulation model to settle an 

appropriate steady-state solution prior to the eclipse operating day. The simulations ran until August 22 to allow each 

time step a full 24 hours of foresight.

The baseline operations assumed a typical meteorological day in NREL’s NSRDB database. Contingency reserves were 

assumed to be 3% of the load; different gas prices were assumed for different regions. Operation and management costs 

were included and assumed that the thermal power plants were running at a steady load without any on/off cycling. The 

transmission system was modeled without losses and was a fixed shift-factor AC optimal power flow. The chosen mixed 

integer program tolerance was 0.01% to ensure a near-perfect solution. The model ran with BA resolution, meaning that 

transmission was aggregated within BAs, and transmission details including constraints were maintained between BA 

areas. 
SOLAR ECLIPSE REPORT 14

Three stages comprised the model. First, a generator maintenance schedule was determined so that a minimum risk of 

capacity shortage would be based on load forecast. The 5-day operation ran in a single step under system constraints, 

such as hydro availability. Finally, these constraints were further decomposed to finer resolution, and the model ran at 

5-minute steps. 

3.2.2 Results

The solar eclipse results showed an approximate peak reduction of 5–6 GW in solar generation across WECC. One 

observation the research team made was that the geographical footprint of WECC is quite large, and this allowed for 

a staggered impact of the solar eclipse on the region during the approximate 4 hours that the eclipse occurred. This 

geographic smoothing naturally helps mitigate the impact of the eclipse. 

During the eclipse, the burden of compensating for the lost energy from solar generators fell to the thermal fleet, mostly 

natural gas combined cycle (CC) generators. The CC generators have sufficient capacity with sufficient flexibility (i.e., ramping 

capacity, operational capacity) and therefore could shoulder most of the burden. The available headroom (remaining 

capacity) and footroom (current output) for the CC fleet is shown in Figure 11 and Figure 12, respectively. The figures also 

illustrate that there was sufficient capacity to compensate for the fall and rise in solar production during the eclipse.

0

2,000

4,000

6,000

8,000

10,000

12,000

14,000

16,000

18,000

00:00 00:5001:40 02:30 03:20 04:1005:0005:50 06:40 07:30 08:20 09:10 10:0010:50 11:40 12:30 13:20 14:10 15:00 15:50 16:40 17:3018:2019:10 20:00 20:50 21:40 22:30 23:20

Headroom (MW) 

Figure 11. Aggregate headroom for the CC fleet for August 21, 2017, EDT

0

5,000

10,000

15,000

20,000

25,000

00:0000:50 01:40 02:30 03:20 04:10 05:00 05:50 06:40 07:30 08:20 09:10 10:00 10:50 11:40 12:30 13:20 14:10 15:00 15:50 16:40 17:30 18:20 19:1020:00 20:50 21:40 22:30 23:20 

Headroom (MW) 

Figure 12. Aggregate footroom for the CC fleet for August 21, 2017, EDT
15 SOLAR ECLIPSE REPORT

During the eclipse, from approximately 8 a.m. until noon PDT, the CC generators ramped up to compensate for the loss 

in solar generation, and the headroom decreased. Expectedly, the footroom increased as generators moved higher into 

their operating range. There was, however, substantial CC availability during this time, and these generators were able to 

provide the majority of the solar energy compensation. Figure 13 shows the change in aggregate energy production by 

generation technology type because of the solar eclipse.

-5

-4

-3

-2

-1

0

1

2

3

4

5

6

DPV

UPV

Biomass

CC

Combustion turbine

Coal_ST

Geothermal

Hydro

IC

NG_ST

Other_ST

Figure 13. Change in energy production by generator type due to the eclipse

The next largest generation technology that helped make up the energy deficit was hydro generation. Hydro generators 

have desirable flexibility characteristics, but because of energy conservation constraints, they cannot compensate for the 

loss of solar generation alone. The total production cost for August 21, 2017, was 0.2% higher than a no-eclipse scenario, 

which was mostly attributable to the loss of solar generation being replaced with thermal generation for the duration of 

the eclipse.

3.3 Transient Simulation 

Transient simulations were used for assessing the stability of the electric grid. During the eclipse, the stability of the grid 

was of utmost concern during the peak (at 10:21 a.m. PDT). 

Transient simulation studies required a two-part differential-algebraic model to represent the entire WECC system: (1) a 

static model that represented the algebraic equations governing the flow of real and reactive power among all the buses 

and (2) a dynamic model that represented the differential equations describing the behavior of individual power system 

equipment and their controls. These models were updated to include the peak eclipse scenario by adjusting the current 

injections from different generators (generator set points), equipment status, and system loading at the load buses. 

The WECC model described here was used for operational planning for the western U.S. grid. It consists of power plants, 

transmission lines, and substations from 500 kV to 69 kV, utility-scale renewable generation sites, and other special 

power systems equipment such as high-voltage DC (HVDC) systems and flexible AC transmission systems. The load and 

distribution systems are typically aggregated at the level of 69 kV. The current modeling paradigm does not distinguish 

between actual load and DPV because of lack of sufficient information from the distribution systems. The load is generally 

characterized as fractions of motor and static loads. The simulation does not consider further tripping of PV inverters 

because of high/low frequency, which might cause cascaded events; however, this is worth further studies.
SOLAR ECLIPSE REPORT 16

3.3.1 Approach

Power system stability is typically assessed through the following characteristics: voltage, frequency, and phase angle. 

Angular stability is further divided into small-signal and large-angle stability. For stability analysis, the following credible 

contingencies were identified in collaboration with Peak Reliability. These contingencies are shown in Figure 14.

1. Loss of Palo Verde generators

2. Loss of Pacific DC Intertie (PDCI)

3. Loss of Intermountain HVDC line

4. Loss of one of the lines along the California-Oregon, Intertie

Source: WECC

Figure 14. Identified contingencies for stability studies

The four selected contingencies were not only severe but also represented unique challenges to the grid. These 

challenges were: loss of PV units represents a loss of massive generation, loss of PDCI represents a loss of a major 

DC intertie, loss of Intermountain HVDC represents a combined loss of generation and major DC intertie, and loss of 

California-Oregon Intertie represents a major contingency along a critical AC transmission corridor.

Transient simulations were performed by loading the power flow files that represent the static model of WECC. Then 

the dynamic models were loaded, and the simulation run was initialized. The dynamic simulation was run for a few 

seconds to ensure steady-state initial conditions. The dynamic solution was computed at a time step of 4.2 ms (4 time 

steps for each power system cycle at 60 Hz). Then a three-phase fault was placed at a bus near the selected contingency 

location, and the generator or line was removed from service. The simulation was allowed to run for the next 15 seconds 

to observe the system dynamics. Bus voltages, bus frequencies, and tie line power across the interconnection were 

monitored for discrepancies and stability concerns. The contingency studies showed that the system is stable in voltage, 

frequency, and angular terms during the peak eclipse. 

During the transient simulations, triggering underfrequency load shedding was not observed. The prevalent 

underfrequency load shedding settings for WECC [13] are presented in Table 5. 

2

4

3

1
17 SOLAR ECLIPSE REPORT

Table 5. WECC-Coordinated Underfrequency Load-Shedding Plan

Load-Shedding 

Block

Customer Load 

Dropped (%)

Pickup 

Frequency (Hz) Tripping Time*

1 5.3% 59.1 14 cycles

2 5.9% 58.9 14 cycles

3 6.5% 58.7 14 cycles

4 6.7% 58.5 14 cycles

5 6.7% 58.3 14 cycles

Additional automatic load shedding to correct underfrequency stalling

2.3% 59.3 15 seconds

1.7% 59.5 30 seconds

2.0% 59.5 60 seconds

Load automatically restored from 59.1-Hz block to correct frequency overshoot

1.1% 60.5 30 seconds

1.7% 60.7 5 seconds

2.3% 60.9 15 cycles

*Tripping time includes relay and circuit breaker time.
SOLAR ECLIPSE REPORT 18

3.3.2 Results

The plots for frequency and tie line power for selected locations across WECC are shown for each of the selected 

contingencies described in this report. 

3.3.2.1 Loss of Palo Verde units

The loss of three generating units at Palo Verde was considered the most severe contingency. The three generating units 

at Palo Verde produced about 3.3 GW. As shown in Figure 15, this caused a significant impact on the tie line flows and 

system frequencies. 

Figure 15. Transmission flows and bus frequencies at selected locations (Palo Verde)

Figure 15 shows how the change in power flow along selected corridors represented a change in system flows because 

of the loss of Palo Verde units. (Line flows were not identified because of confidentiality.) In the frequency plot, the 

frequency nadir was 59.8 Hz. The frequency and tie line flows showed small-signal oscillations with high damping. No 

other trips, load shedding, or voltage problems were observed. The flows along the tie lines were also within their rating 

limits. 

3.3.2.2 Loss of PDCI

PDCI is a bipolar, multiterminal HVDC transmission system that brings power (chiefly, hydropower) from the Pacific 

Northwest region of the United States to Los Angeles, California. It is rated for 3,100 MW. 
19 SOLAR ECLIPSE REPORT

Figure 16. Transmission flows and bus frequencies at selected locations (PDCI)

In Figure 16, the tie line flows respond to the loss of PDCI. As the PDCI power transmission corridor was lost, the rest of 

the tie lines that cater to California picked up in response. (Line flows were not identified because of confidentiality.) 

Though the frequency nadir was 59.7 Hz, the frequency recovered to the nominal value before the end of the 20 seconds. 

Inter-area oscillations could also be observed; high system damping led to quick damping of these modes. 

3.3.2.3 Loss of Intermountain Power Plant 

The Intermountain Power Plant has an installed capacity of 1,900 MW and consists of two generating units. Most of the 

power from the Intermountain Power Plant is shipped through the Intermountain HVDC transmission line to Adelanto, 

California. This contingency combines aspects of the first two cases because of the loss of an HVDC line and the 

generation station. (Line flows were not identified because of confidentiality.)
SOLAR ECLIPSE REPORT 20

Figure 17. Transmission flows and bus frequencies at selected locations (Intermountain Power Plant)

Because the contingency represented a loss of generation and a major transmission corridor, the research team saw a 

pronounced impact on the tie line flows and on system frequencies. The frequency nadir was 59.5 Hz, and the oscillations 

were completely damped before 20 seconds. The frequency of oscillations was markedly different from the previous two 

cases. 

3.3.2.4 Loss of California-Oregon Intertie

The California-Oregon Intertie is a collection of high-voltage AC transmission lines that are designated as Path 66 by 

WECC. The California-Oregon Intertie connects the electric grids of Oregon and California and is rated at 4,800 MW. For 

this case, one line along the California-Oregon Intertie path was removed from service after a three-phase fault.
21 SOLAR ECLIPSE REPORT

Figure 18. Transmission flows and bus frequencies at selected locations (California-Oregon Intertie)

As with the previous cases, frequency and tie line shifts were within acceptable limits. Underfrequency load shedding 

was not observed because of the short duration of frequency transients. The frequency recovered to the nominal because 

the load balance was not affected. The spike in tie line power during the three-phase fault was observable in this case 

because the fault was placed on a major AC corridor.

3.4 Peak Reliability Eclipse Preparation Efforts

As the Reliability Coordinator (RC), Peak Reliability has the highest level of authority for the WECC region and is therefore 

responsible for the reliable operation of the bulk electric system. In preparation for the solar eclipse, Peak Reliability 

surveyed its member BAs in the footprint of the eclipse as well as Alberta Electric System Operator (the other RC in the 

Western Interconnection) regarding the expected impact of the solar eclipse. The survey included a request for the 

estimated maximum amounts of both UPV and DPV that would potentially be reduced during the solar eclipse event. 

In addition, the survey requested any operating plans developed for the event and for information on reserves, asking 

Peak Reliability members how they expected to make up for the reduction in the UPV and DPV output. Peak Reliability 

summarized the results of the survey responses and created a footprint-wide operating memo to ensure awareness 

among its members.

Peak Reliability also performed a footprint-wide study to analyze the expected impact of the solar eclipse on its RC area. 

The study leveraged data from NREL, solar eclipse obscuration factors from NASA, recent state-estimator snapshots 

from its energy management system, and data obtained from its member survey to develop a case study that could be 

used to simulate two worst-case scenarios. The objective of the studies was to ensure readiness at the RC level for the 

solar eclipse event while also verifying the effectiveness of the member-supplied transmission operating plans (TOPs), 

including reserves sufficiency. After performing its assessments, Peak Reliability concluded that with the application of 

the member-supplied TOPs and their plans for reserves, its RC area was not expected to experience any reliability issues 

related to the solar eclipse.
SOLAR ECLIPSE REPORT 22

4. Post-Event Analysis

The post-event analysis presented here studied the impact of the eclipse from actual field data collected by Peak 

Reliability and applies to the entire footprint. The U.S. Energy Information Administration performed a study to evaluate 

the impact on California, given its high PV penetration [1].

4.1 Data

Peak Reliability provided the data for the analysis. There are two types of data that are used in this study:

1. Real-time measurements. Peak Reliability used the OSIsoft PI system, a common utility supervisory control and data 

acquisition system, to collect real-time measurements from critical bulk grid elements such as generators, including 

utility wind and solar power plants; transmission lines; and interties among the different BA areas. In addition, 

Peak Reliability collected BA-level information, such as area control error, scheduled exchanges, spinning and total 

reserves, and total load and generation. The archived real-time measurements for 4 selected days were collected. The 

reporting rate for the data was at 10-second intervals on the day of the eclipse, and for the other three baseline days 

it was collected at 1-minute intervals. In addition, data archives spanning the first 6 months of 2017 were collected 

for renewable sites. 

2. Energy management system-solved cases. The energy management system used the measurement data to estimate 

states for the entire WECC network through its state estimation application. The solved state estimation case was the 

most accurate representation of the system at that instant of time. Peak Reliability provided these cases at 1-minute 

intervals for the day of the eclipse and at lower rates for the other selected days.

4.2 Approach

4.2.1 Determining Baseline for Grid Operations on August 21, 2017

To estimate the impact of the eclipse on grid operations, it was important to establish a credible baseline for what the 

grid operations may have been without the eclipse event on August 21, 2017. To do this, the research team selected 3 

days: August 22 (the day after the eclipse), August 14 (the Monday before the eclipse), and August 18 (the Friday before 

the eclipse). The total generation and load for WECC for the 4 days (including the eclipse day) between 8 a.m. and 2 p.m. 

PDT is shown in Figure 19. The gray-shaded areas represent the duration of the eclipse in the WECC footprint. The vertical 

black line represents the peak of the eclipse, defined as the point at which the impact on PV output was the highest. 
23 SOLAR ECLIPSE REPORT

105,000

100,000

115,000

110,000

120,000

125,000

130,000

135,000

08:0009:0010:0011:0012:0013:0014:00

Real Power (MW) 

Total Generation

08_14

08_18

08_21

08_22

Figure 19. Total generation at WECC-level

105,000

100,000

115,000

110,000

120,000

125,000

130,000

135,000

08:0009:0010:0011:0012:0013:0014:00

Real Power (MW) 

Total Load

08_14

08_18

08_21

08_22

Figure 20. Total load at WECC-level

The system generation and loading charts may seem identical, but there is a certain offset. This offset represents the 

system losses at the transmission level. These charts illustrate that the load and generation profiles at the WECC level 

exhibit a linear characteristic as they ramp up during the day. The research team used this linearity assumption when 

determining the impact on load in a later section. 
SOLAR ECLIPSE REPORT 24

4.2.2 Determining Impact on Photovoltaic Output

The impact on the DPV output cannot be measured directly because of the lack of sufficient measurements from the 

distribution network. Hence, the impact on the DPV was interpreted as the same as the impact that was estimated earlier. 

This approach aligns with the approach adopted by Peak Reliability for their estimation of impact. The NREL team’s 

previous studies showed a total DPV capacity of 9.2 GW across WECC. The maximum loss of DPV was expected to happen 

around 10:21 a.m. PDT with a loss of 1.9 GW. 02:00 04:00 06:00 08:00

10:0012:00 14:00 16:0018:00 20:00 22:0024:00

0

1,000

2,000

3,000

4,000

5,000

6,000

8,000

7,000

MW

DPV Cumulative WECC Generation 

August 21, 2017

No eclipse

Eclipse

Figure 21. Loss of DPV during eclipse (estimated)

The impact on the PV output can be estimated by comparing the WECC-level PV output for the selected baseline days. 

The UPV output at the WECC level for the selected dates is shown in Figure 22.
25 SOLAR ECLIPSE REPORT

3,000

2,000

5,000

4,000

6,000

7,000

8,000

9,000

10,000

11,000

08:0009:0010:0011:0012:0013:0014:00

Real Power (MW) 

UPV Generation

Aug 14

Aug 18

Aug 21

Aug 22

Figure 22. UPV generation at WECC-Level

As shown in Figure 22, the PV profile on August 21 at 8 a.m. PDT resembles a PV profile of August 14, a relatively cloudy 

day; however, at the end of the eclipse event (around 1 p.m. PDT), the output resembles the profile recorded on August 

18, a relatively sunny day. It can be hypothesized that August 14 provided a lower estimation for the expected PV output 

on August 21, whereas August 18 provided a higher estimation for the expected PV output, hence the profiles for 

computing the impact on PV output. 

The research team estimated that the observed loss of UPV was between 4 GW and 6.5 GW at the peak of the eclipse. The 

overall loss of energy from UPV resources was estimated to be between 5.5 GWh and 11 GWh. 
SOLAR ECLIPSE REPORT 26

08:0009:0010:0011:0012:0013:0014:00

-2,000

0

2,000

4,000

6,000

8,000

10,000

Real Power (MW) 

Lower Threshold of PV Impact

Aug 14

Aug 21

Impact threshold

Figure 23. Minimum PV impact on eclipse day

08:0009:0010:0011:0012:0013:0014:00

-2,000

0

2,000

4,000

6,000

8,000

10,000

Real Power (MW) 

Upper Threshold of PV Impact

Aug 22

Aug 21

Impact threshold

Figure 24. Maximum PV impact on eclipse day

When determining the impact on PV output, it is also pertinent to ask how an eclipse differs from another type of large 

weather event. To answer this question, the NREL research team collected PV output at the WECC system level for the first 

6 months of the year and plotted the data in Figure 25, where each color represents a different month.
27 SOLAR ECLIPSE REPORT

8 10 12 14 16

0 2000 4000 6000 8000 10000

January

Time

Solar (MW)

Figure 25. WECC-level aggregate PV output

Although overall PV output can vary from one day to another, the ramp rate associated with ramping up and down 

during the eclipse was markedly different. This can be seen clearly when the PV outputs are normalized to output power, 

as shown at 1 p.m. PDT in Figure 26. 

8 10 12 14 16

0.0 0.2 0.4 0.6 0.8 1.0

January

Time

Output Normalized to 13

Figure 26. WECC-level aggregate PV output normalized
SOLAR ECLIPSE REPORT 28

4.2.3 Determining Impact on System Loading

As the first few charts indicate, there was a drop in the total system load because of the eclipse. The change in system 

loading can be attributed to the following factors:

1. Loss of DPV (increases loading)

2. Non-PV factors: transient weather changes and behavioral factors (decreases loading).

As the eclipse gained totality across the footprint, it caused a loss of DPV as well. Assuming the profile for the DPV profile 

as was estimated earlier, it would result in a general increase in the actual load. This is shown in Figure 27, where the 

actual total load was computed after applying the DPV profile. 

110,000

105,000

120,000

115,000

125,000

130,000

135,000

140,000

08:0009:0010:0011:0012:0013:0014:00

Real Power (MW) 

Impact of Loss of DPV on System Loading

Net WECC load

Net WECC load - no eclipse

Actual WECC load

Actual WECC load - no eclipse

Figure 27. Actual and net load at WECC-level on eclipse day

The impact on actual and net load as a result of the eclipse can be estimated by calculating the difference between 

the eclipse and no-eclipse profiles, shown in Figure 28. The change in net loading as a result of the eclipse was 7.2 GW. 

Assuming a system loading of 120 GW, the change was 6%. This magnitude represents the change in load as a result 

of DPV and non-PV factors. The change in actual load (where DPV is removed) represents the change in load because 

of non-PV factors. Although there are currently limited means to estimate the impact caused by non-PV factors, the 

information from this study and from previous studies can provide a rule-of-thumb estimate for future studies. Figure 28 

shows that a change in actual system loading (without DPV) as a result of the eclipse is 5.4 GW, or 4.5%. The maximum 

impact on load did not coincide with the maximum impact on PV output.
29 SOLAR ECLIPSE REPORT 08:00

09:0010:0011:0012:0013:0014:00

1,000

0

3,000

4,000

2,000

5,000

6,000

7,000

8,000

Real Power (MW) 

Impact of Eclipse on Actual and Net Loading

Net WECC load change

Actual WECC load change

Figure 28. Actual and net load impact due to eclipse

4.2.4 Impact on System Reserves

The total system reserves for the 4 selected days are plotted below in Figure 29. The higher reserves were procured by the 

WECC entities, which was confirmed by Peak Reliability. Note that the available reserves continued to dip until the peak of 

the eclipse, after which they increased as the totality left the WECC footprint. 

Another observation is that the peaking of the available total system reserves at 29.5 GW coincided with the start of the 

PV curtailment. After the eclipse event, reserves were taken off the market, which could lead to declining reserves until 

the valley point occurring at about 28 GW at 11:56 a.m. PDT. This valley point marks the end of PV curtailment, thus the 

curtailment must have been caused by the availability of additional reserves coupled with a decrease in system loading, 

leading to a potential overgeneration scenario. 
SOLAR ECLIPSE REPORT 30

08:0009:0010:0011:0012:0013:0014:00

22,000

24,000

26,000

28,000

30,000

Real Power (MW) 

Total Reserves

08_14

08_18

08_21

08_22

Figure 29. Total reserves at WECC-level

4.2.5 Impact on Western Electricity Coordinating Council Path Flows

As the eclipse event progressed, the flows along the critical WECC paths were altered because of the redispatch of 

resources to account for the loss of PV. WECC has 25 paths defined for power transfer among the different BA areas. 

Although a path typically represents multiple transmission lines, a path could also be a single, long, high-capacity 

transmission line. The definitions and ratings for all WECC paths are presented in Appendix A. The path flows that were 

impacted by the eclipse were identified by power flow trends during the eclipse event, after being normalized by the preeclipse flows. These ratings and definitions of the affected paths are shown in the Table 6.

Table 6. Definition and Ratings of Affected WECC Paths

Path # Path Name

Path Rating Transfer Limit (MW) Primary 

Direction 

E to W (N to S) W to E (S to N) (Positive Flow)

Path 03 NorthWest to British Columbia 3,150 2,000 S to N

Path 04 NorthWest to British Columbia 10,200 E to W

Path 05 Bonneville Power Administration to 

Bonneville Power Administration

7,000 E to W

Path 15 Pacific Gas and Electric to 

Pacific Gas and Electric

500 360 N to S

Path 61 Southern California Edison to Southern 

California Edison

2,400 900 N to S

Path 65 PDCI 3,100 3,100 N to S

Path 66 California-Oregon Intertie 4,800 3,675 N to S

Path 73 North of John Day
31 SOLAR ECLIPSE REPORT

The selected paths are shown in the Figure 30 [14].

Source: WECC

Figure 30. Affected WECC paths

During the eclipse, the paths that transfer power from the north of the footprint to the load centers in Southern California 

had increased to make up for the loss of PV in California. Conversely, the flows along the paths inside California were 

affected. The path flow trends for selected paths are presented in Figure 31. The plot shows how the path flows trended 

relative to the start of the eclipse. 

09:0010:0011:0012:0013:00

0.5

1.0

1.5

2.0

Rate to Start Eclipse

Path 66

Path 03

Path 73

Path 05

Path 04

Path 15

Transmission Path Trends

Figure 31. Transmission flow trends along affected paths
SOLAR ECLIPSE REPORT 32

Path 3 and Path 66 picked up more than twice their flow relative to the start of the eclipse. As the eclipse left the 

footprint, the flows returned to the pre-eclipse values. The actual power flows for the impacted paths are shown 

in Figure 32. 

09:0010:0011:0012:0013:00

-2,000

-1,000

0

1,000

2,000

3,000

MW

Transmission Paths

Path 73

Path 04

Path 05

Path 66

Path 15

Path 03

Figure 32. Transmission flows along affected paths

4.2.6 Impact on Generation Dispatch

The change in transfer flows was caused by the change in generation dispatch among the different BA areas. Change in 

flows by BA for the affected areas is presented in Figure 33. 09:00 10:00

11:0012:0013:00

0

5,000

10,000

15,000

20,000

25,000

MW

Generation by Area

Rest

BA1

BA3

BA4

BA2

BA9

BA8

BA7

BA10

BA11

BA5

BA6

Figure 33. Total generation by affected utility areas
33 SOLAR ECLIPSE REPORT

The change in generation profiles by area is more obvious after normalization in relation to the start of the eclipse. 

Generation trends are presented in Figure 34. Note that BA4 and BA10 picked up 20% more generation relative to the 

start of the eclipse. BA1 shows a modest 5% drop at the peak of the eclipse. The other affected areas show increased 

levels of generation during the eclipse duration. 09:00 10:00

11:0012:0013:00

0.8

0.9

1.0

1.1

1.2

1.3

Ratio to Start of Eclipse

Generation Trends by Area

BA1

BA3

BA4

BA9

BA7

BA6

BA10

Figure 34. Generation trends in affected utility areas

Impact of generation can also be studied based on fuel type, as shown in Figure 35. 09:00 10:00 11:00 12:00

13:00

10,000

0

20,000

30,000

40,000

50,000

60,000

MW

Generation by Fuel Type

Coal

Hydro

NG

Solar

Figure 35. Total WECC generation by fuel types
SOLAR ECLIPSE REPORT 34

The impact of an eclipse is clearer after normalization relative to the start of the eclipse. Figure 36 represents generation 

trends by fuel type. As shown, the loss of PV was made up by an increase in hydropower plants, natural gas, and 

coal-powered plants.

09:0010:0011:0012:0013:00

0.4

0.6

0.8

1.0

1.2

Ratio to Solar Eclipse

Generation Trends by Fuel Type

NG

Hydro

Coal

Solar

Figure 36. Generation trends by fuel type

4.2.7 Impact on Generation by Fuel Type and Area

Appendix B shows how generation by fuel type was impacted as a result of the eclipse in selected utility areas.

4.2.8 Peak Reliability Operations

A week prior to the eclipse, Peak Reliability hosted a solar eclipse readiness webinar with all of its BAs and TOPs to ensure 

the entities were prepared for the solar eclipse. During the webinar, Peak Reliability disseminated its study results from 

the worst-case scenario studies while discussing portions of the footprint-wide operating memo. Peak Reliability also had 

a few larger solar-producing BAs discuss their plans with the other BAs and TOPs in their RC area. The night before the 

eclipse, Peak Reliability followed up with all the BAs and TOPs to verify the information in their respective operating plans. 

Peak Reliability developed displays to monitor the grid during the eclipse event in real time, shown in Figure 37.
35 SOLAR ECLIPSE REPORT

Figure 37. Solar eclipse display for real-time monitoring (internal)

Figure 38. Solar eclipse display (external)

4.2.8.1 Photovoltaic Curtailment

CAISO curtailed UPV within its footprint as PV was ramping up after the eclipse peak [15]. The curtailment was because of 

the inability to back off conventional generators, leading to overgeneration. CAISO indicated that it had curtailed 1.7 GW 

of PV between 11 a.m. and 12 p.m. MDT, losing 0.8 GWh of energy. Considering the data shown in Figure 22, the research 

team estimated that the curtailment happened between 11:16:41 a.m. and 11:56:36 a.m. MDT, for a duration of 

40 minutes. 
SOLAR ECLIPSE REPORT 36

5. Summary

This NREL-conducted study played an important role in helping Peak Reliability and the BAs in the western United States 

prepare for the eclipse event. Although Peak Reliability focused on a worst-case “clear-day” scenario, the NREL team 

worked on a typical day scenario. This approach allowed for greater certainty as Peak Reliability prepared and reviewed 

mitigation measures as well as transmission operating plans for the eclipse day. 

The study uncovered important insights for bulk grid operators, utility industry, and researchers using previouslydeveloped tools and databases to study the penetration of DPV in the WECC footprint. This information will enable Peak 

Reliability to disaggregate the load into DPV and actual load in its study and operational models.

NREL capitalized on the opportunity to not only study the impact of the August 2017 solar eclipse on grid operations, 

but also develop a framework for studying a large, geophysical phenomenon, such as a significant weather event or a 

future eclipse. A subsequent report with more details on the framework will be published in 2018. Such a framework will 

be critical because entities like NERC and transmission utilities are increasingly considering the impact of DPV on the 

reliability of the bulk grid and defining their role for grid operations. 

6. References

1. U.S. Energy Information Administration, “Solar Eclipse on August 21 Will Affect Photovoltaic Generators Across 

the Country,” Today in Energy (blog), August 7, 2017, https://www.eia.gov/todayinenergy/detail.php?id=32372#. 

2. North American Electric Reliability Corporation, “A Wide-Area Perspective on the August 21, 2017, Total Solar Eclipse (white paper)” 

(Washington, D.C.: 2017), http://www.nerc.com/pa/RAPA/ra/Reliability%20Assessments%20DL/Solar_Eclipse_2017_Final_4-25-17.pdf. 

3. Regional Group Continental Europe and Synchronous Area Great Britain, Solar Eclipse 2015: Impact Analysis (Brussels, Belgium: European 

Network of Transmission System Operators for Electricity, 2015) 

https://www.entsoe.eu/Documents/Publications/SOC/150219_Solar_Eclipse_Impact_Analysis_Final.pdf.

4. Sven Killinger, Niklas Kreifels, Bruno Burger, Björn Müller, George Stiff, and Christof Wittwer, “Impact of the Solar Eclipse from 20th March 2015 on

the German Electrical Supply—Simulation and Analysis,” Energy Technology (2015), http://doi.org/10.1002/ente.201500228. 

5. International Energy Agency Photovoltaic Power Systems Programme, How an Energy Supply System with a High PV Share Handled a Solar 

Eclipse, (IEA-PVPS T14-06:2016), Kassel, Germany: Fraunhofer IWES, 2016) 

http://www.iea-pvps.org/fileadmin/dam/public/report/statistics/PVPS__T14-06_2016_EuropeanSolarEclipse2015inGermany.pdf. 

6. European Network of Transmission Systems Operators for Electricity, Solar Eclipse March 2015: The Successful Stress Test of Europe’s 

Power Grid—More Ahead (Brussels, Belgium: July 2015), 

https://docs.entsoe.eu/dataset/solar-eclipse-the-successful-stress-test-of-europe-s-power-grid-more-ahead.

7. Carmen Köhler, Andrea Steiner, Daniel Lee, Jens Thieler, Yves-Marie Saint-Drenan, Dominique Ernst et al., “Assessing the Impact of a Solar Eclipse

on Weather and Photovoltaic Production,” Meterologische Zeitschrift 25 no. 1 (2016): 55–69, http://doi.org/10.1127/metz/2015/0672. 

8. Suzanne Gray and Giles Harrison, “Diagnosing Eclipse-Induced Wind Changes,” Proceedings of the Royal Society A (2012): 1839–1850, 

https://doi.org/10.1098/rspa.2012.0007. 

9. California Independent System Operator, 2017 Solar Eclipse Report (Folsom, CA: May 2017), 

https://www.caiso.com/Documents/Briefing_SolarEclipse-ISOReport-May_2017.pdf. 

10. Galen Barbose and Naïm Darghouth, Tracking the Sun IX: The Installed Price of Residential and Non-Residential Photovoltaic Systems in the 

United States (LBNL-1006035) (Berkeley, CA: Lawrence Berkeley National Laboratory, 2016), 

https://emp.lbl.gov/sites/default/files/tracking_the_sun_ix_report.pdf.

11. A. Perea et al., U.S. Solar Market Insight Q2 2017 (Washington, D.C.: Solar Energy Industries Association, 2017), 

https://www.seia.org/research-resources/solar-market-insight-report-2017-q2.

12. Ibrahim Reda, Solar Eclipse Monitoring for Solar Energy Applications using the Solar and Moon Position Algorithms

(NREL/TP-3B0-47681) (Golden, CO: National Renewable Energy Laboratory, 2010), https://www.nrel.gov/docs/fy10osti/47681.pdf. 

13. Western Electricity Coordinating Council, Western Electricity Coordinating Council Off-Nominal Frequency 

Load Shedding Plan (Salt Lake City, UT: 2011), https://www.wecc.biz/Reliability/Off-Nominal%20Frequency%20Load%20Shedding%20Plan.pdf.

14. “WECC Paths,” Western Electricity Coordinating Council (WECC), last modified 2016, 

https://www.wecc.biz/epubs/StateOfTheInterconnection/Pages/Transmission/WECC-Paths.aspx.

15. California ISO, “Wind and Solar Curtailment August 21, 2017,” 

http://www.caiso.com/Documents/Wind_SolarReal-TimeDispatchCurtailmentReportAug21_2017.pdf.
37 SOLAR ECLIPSE REPORT

Appendix A: WECC Path Definition 

and Ratings

Path # Name

Path Rating Transfer Limit (MW) Defined Positive 

Flow Direction 

E to W (N to S) W to E (S to N) (Primary Direction)

Path 1 Alberta to BC 1,000 1,200 E to W

Path 3 Northwest to Canada 3,150 2,000 S to N

Path 8 Montana to NW 2,200 1,350 E to W

Path 14 Idaho to NW 2,400 1,200 E to W

Path 17 Borah W 2,557 Not defined E to W

Path 18 Montana to Idaho 337 256 N to S

Path 19 Bridger West 2,200 Not defined E to W

Path 20 Oath C 1,000 1,000 S to N

Path 22 Southwest of 4-Corners 2,325 Not defined E to W

Path 23 4-Corners Transformer N/A N/A N/A

Path 27 IPP DC Line 1,920 1,400 N to S

Path 30 TOT 1A 650 Not defined E to W

Path 31 TOT 2A 690 Not defined N to S

Path 34 TOT 2B 795 900 N to S

Path 35 TOT 2C 300 300 NE to SW

Path 36 TOT 3 1,605 Not defined N to S

Path 45 CISO - CFE 408 800 S to N

Path 46 West of Colorado River 10,623 Not defined E to W

Path 47 Southern New Mexico 1,048 Not defined N to S

Path 48 Northern New Mexico 1,970 Not defined NW to SE

Path 49 East of Colorado River 9,300 Not defined E to W

Path 50 Cholla Pinnacle Peak 1,200 Not defined NE to SW

Path 51 Southern Navajo 2,800 Not defined N to S

Path 65 Pacific DC Intertie 3,100 3,100 N to S

Path 66 California-Oregon 

Intertie

4,800 3,675 N to S
SOLAR ECLIPSE REPORT 38

Appendix B: Generation by Fuel Type for 

Each Utility Area 09:00 10:00

11:0012:0013:00

0.1

0.0

0.2

0.3

0.4

Generation Per Unit (pu)

Generation by Fuel Type for BA1

Coal

Hydro

NG

Solar

09:0010:0011:0012:0013:00

0.1

0.0

0.2

0.3

0.4

0.5

0.6

Generation Per Unit (pu)

Generation by Fuel Type for BA2

Coal

Hydro

NG

Solar
39 SOLAR ECLIPSE REPORT 09:00

10:0011:0012:0013:00

0.2

0.0

0.4

0.6

Generation Per Unit (pu)

Generation by Fuel Type for BA3

Coal

Hydro

NG

Solar

09:0010:0011:0012:0013:00

0.2

0.0

0.4

0.6

0.8

Generation Per Unit (pu)

Generation by Fuel Type for BA4

Coal

Hydro

NG

Solar

09:0010:0011:0012:0013:00

0.1

0.0

0.2

0.3

0.4

0.5

Generation Per Unit (pu)

Generation by Fuel Type for BA5

Coal

Hydro

NG

Solar
SOLAR ECLIPSE REPORT 40

09:0010:0011:0012:0013:00

0.2

0.0

0.4

0.6

Generation Per Unit (pu)

Generation by Fuel Type for BA6

Coal

Hydro

NG

Solar

09:0010:0011:0012:0013:00

0.2

0.0

0.4

0.6

0.8

Generation Per Unit (pu)

Generation by Fuel Type for BA7

Coal

Hydro

NG

Solar

09:0010:0011:0012:0013:00

0.2

0.0

0.4

0.6

0.8

Generation Per Unit (pu)

Generation by Fuel Type for BA8

Coal

Hydro

NG

Solar
41 SOLAR ECLIPSE REPORT09:00

10:0011:0012:0013:00

0.1

0.0

0.2

0.3

0.4

0.5

0.6

Generation Per Unit (pu)

Generation by Fuel Type for BA9

Coal

Hydro

NG

Solar

09:0010:0011:0012:0013:00

0.2

0.0

0.4

0.6

0.8

1.0

Generation Per Unit (pu)

Generation by Fuel Type for BA10

Coal

Hydro

NG

Solar
SOLAR ECLIPSE REPORT 42

09:0010:0011:0012:0013:00

0.2

0.0

0.4

0.6

Generation Per Unit (pu)

Generation by Fuel Type for BA11

Coal

Hydro

NG

Solar

09:0010:0011:0012:0013:00

0.1

0.0

0.2

0.3

0.4

0.5

0.6

Generation Per Unit (pu)

Generation by Fuel Type for BA12

Coal

Hydro

NG

Solar
SOLAR ECLIPSE REPORT

Evaluating the Impact of the 2017 

Solar Eclipse 

on U.S. Western Interconnection Operations

April, 2018 • NREL/TP-5D00-71147

Cover photo from iStock 810937516