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Slide 1

Item No. A-4

March 17, 2016

Transmission Metrics: 

Initial Results

Good morning Mr. Chairman and Commissioners. Office of Energy Policy and 

Innovation staff has attempted to develop objective and standardized measures of 

various characteristics of the electric system and its performance to help assess the 

effectiveness of the Commission’s policies regarding transmission investment and to 

inform potential policy revisions going forward. As the team described in its 

presentation at the April 2015 open meeting, staff considered a range of potentially 

relevant metrics in three broad categories: (1) metrics designed to evaluate key goals 

of Order No. 1000; (2) metrics designed to indicate whether appropriate levels of 

transmission infrastructure exist in a particular region; and (3) metrics designed to 

permit analysis of the impact of Commission policy changes by comparing key values 

before and after changes take place. 

In the staff report being released today, staff describes our methodology for 

calculating each of the three categories of metrics and the results of that analysis. 

We will now provide a brief overview of the report, which will be available through 

the www.ferc.gov website.

To begin, my colleague Ben Foster will discuss the first metric, whose development he 

led, which is intended to help assess a key goal of Order No. 1000 – nonincumbent 

participation in regional transmission planning processes.

AD15-12-000
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Slide 2

Key Goal Order No. 1000 –

Nonincumbent Developer 

Reform

 Purpose: measure nonincumbent participation at 

the bid/proposal stage of the Order No. 1000 

regional transmission planning process

 Analysis focused on PJM and CAISO because 

bid/proposal data from these two regions was 

available at the time of analysis

This metric measures the percentage of bids or proposals for new transmission 

projects in the Order No. 1000 regional transmission planning processes that 

nonincumbent transmission developers submitted. 

At the time that staff was preparing the report, relevant data was only available for 

CAISO and PJM. As explained in more detail in the report, staff gathered data from 

public documents posted on CAISO’s and PJM’s websites and elsewhere. 

Staff applied Order No. 1000’s definition of nonincumbent transmission developer, 

which turns on whether a transmission developer has a retail distribution service 

territory or footprint and, if so, whether the project is located there. To determine 

the incumbency status of developers submitting proposals, which was generally not 

available on the regions’ websites, staff compared the zone in which each proposed 

project would be built with the developer’s retail distribution service territory or 

footprint, where applicable.
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Slide 3

Competitive Proposals by 

Incumbents vs. Nonincumbents

22%

35%

25%

33%

63%

38%

78%

65%

75%

67%

37%

62%

0%

10%

20%

30%

40%

50%

60%

70%

80%

2013 2014 2015 2013 2014 2015

CAISO tJ

n=9 n=20 n=4 n=43 n=304 n=105

Incumbent bonincumbent Incumbent bonincumbent

Sources: CAISO 2012-13 and 2013-14 transmission plans; tJa Transmission Expansion Advisory Committee and RTEt troposal websi

Percent of annual proposals in 

CAISO and PJM (2013-2015)

Slide 3 summarizes the results of staff’s analysis of the bids and proposals that 

developers submitted from 2013 to the period in 2015 when this report was being 

prepared. The figure shows the percentage of proposals in each RTO that came from 

incumbent and nonincumbent transmission developers during the studied period, with 

the associated number of proposals received in each region and year. Overall, of the 

485 proposals submitted in the CAISO and PJM regions, 53 percent were from 

incumbents and 47 percent from nonincumbents. 

On a regional basis, the percentage of proposals from nonincumbents accounted for 

two-thirds to three-quarters of proposals in each of the three years in CAISO. In PJM, 

the percentage of proposals from nonincumbents accounted for more than 60 percent 

of all proposals in 2013 and the studied portion of 2015, but less than 40 percent of 

proposals in 2014, the year in which PJM received the majority of its proposals.
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Slide 4

Metrics to Help Assess Need for 

Transmission Investment

 Assumption: Persistent and costly congestion may

indicate need for additional transmission capacity

 Different approaches for bilateral markets and RTO/ISO 

markets

• Bilateral Markets – based on number of interchange-curtailing 

Transmission Loading Relief (TLR) events

• RTO/ISO markets – based on Locational Marginal Price data

Thank you, Ben. Next we will turn to metrics designed to help indicate whether 

appropriate levels of transmission infrastructure exist in a region. 

Here, staff relied on the assumption that persistent costly congestion in an area may 

indicate insufficient transmission investment because it may suggest that there is not 

enough available transfer capability on the transmission system to support the 

delivery of less costly energy. Ideally, persistent costly congestion would be 

identified directly from historical energy price information by looking for significantly 

large price differentials that persist for extended periods of time. RTO/ISO markets 

generate pricing data directly applicable to this purpose, and as such, staff used this 

data to calculate the metric for RTO/ISO market regions. For non-RTO/ISO market 

regions, staff used a more indirect metric based on historical NERC Transmission 

Loading Relief (TLR) data.
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Slide 5

Load-Weighted 

Curtailment Frequency 

Metric

For non-RTO/ISO market regions, my colleague Abdur Masood led staff’s investigation 

of whether NERC TLR procedures used to manage congestion can serve as an indirect 

measure of the level of transmission infrastructure in the region. Specifically, all 

other things being equal, more TLR events might indicate a need for more 

transmission infrastructure and fewer events might indicate less need for additional 

transmission infrastructure. In practice, staff assumed that such a TLR-based metric 

would need to be used in conjunction with publicly available sources of pricing data, 

such as price indices or retail rate information, in order to incorporate the concept of 

costly congestion. In other words, even if a region experiences large numbers of TLR 

events, in the absence of any significant and persistent price differentials in that 

region, the TLR events might not indicate a need for additional transmission 

infrastructure.

At this point, I need to note that instead of TLRs, the Western Interconnection 

manages unscheduled flows using a coordinated combination of controllable devices, 

such as phase shifting transformers, and schedule curtailments that staff believes are 

similar to TLRs but are not recorded in the NERC TLR logs. Thus, staff did not 

calculate this metric for the Western Interconnection.
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For the Eastern Interconnection, TLR data is publicly available from NERC, but 

reliable price information for non-RTO/ISO market areas is less readily available for 

the types of price indices or retail rate data that staff initially hoped to use. 

However, in the future staff intends to explore whether it could use FERC Electric 

Quarterly Report (EQR) wholesale pricing data to calculate this metric for nonRTO/ISO markets. All jurisdictional and some non-jurisdictional wholesale sellers of 

electricity submit EQR pricing data to FERC, and staff believes that the approximate 

location of associated transactions can be gleaned from the data. Accordingly, EQR 

data may provide a comprehensive view of pricing trends in bilateral market regions 

comparable to what RTO/ISO pricing data provides for organized markets. 

For this report, the basis of this metric is the number of interchange-curtailing TLRs 

that the transmission operators of the region reported to NERC. In order to provide a 

basis for comparing between regions of different sizes, staff normalized this metric 

based on the retail load associated with the region in question.
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Slide 6

Load-weighted TLRs 

(Number of TLRs/GWh retail)

Sources: NERC TLR data

This slide shows the load-weighted TLR metric for Southwest Power Pool, 

Midcontinent Independent System Operator, Inc., and Tennessee Valley Authority, 

which were the areas with the highest numbers of TLRs. While MISO and SPP operate 

organized markets that optimize dispatch based on congestion, greatly reducing their 

internal use of TLRs, it is still possible for RTOs to require TLRs to address 

unscheduled loop flow originating from outside their footprints. Both MISO and SPP 

have extensive borders with non-organized market areas, which may help explain 

their continuing use of TLRs.

Overall, it appears that SPP consistently experienced more TLR events per gigawatthour of retail load than other regions during the analyzed period. However, it should 

be noted that SPP formed its Consolidated Balancing Authority and launched its 

Integrated Marketplace in March of 2014. Prior to that, SPP was acting as the 

reliability coordinator for multiple Balancing Authority Areas and operated an 

imbalance market that was more limited in scope and capability than the Integrated 

Marketplace. The TLR logs show a significant decrease in the rate of SPP’s TLR use 

after the consolidation and market start-up took place. While correlation is not 

necessarily causation, this is what we would expect to happen; consolidating 

Balancing Authority Areas and moving to a more comprehensive market structure 
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should lead to more efficient use of the associated existing transmission facilities, 

which should result in a decrease in the need for TLRs.

The report notes certain potential concerns with reliance on a TLR-based metric, such 

as the fact that TLRs only represent transmission limitations between Balancing 

Authority Areas, and the fact that it is theoretically possible for a system to 

experience costly congestion but not have a significant number of TLRs. However, on 

balance, staff believes that a TLR-based metric can provide one useful data point in 

analyzing non-RTO/ISO bilateral markets.

James Nachbaur will now discuss the price differential metric he developed for 

RTO/ISO market regions.
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Slide 7

RTO/ISO Market Price 

Differential Metric

Staff developed a transmission investment metric that reflects persistent differences 

in RTO/ISO market nodal prices. This metric is expressed in years and it captures how 

long RTO/ISO market nodal price differentials have occurred persistently, though not 

necessarily at all times throughout a year. Staff reasons that consecutive years of 

significant price differentials could indicate insufficient transmission infrastructure 

because, for example, lower cost energy at lower-priced nodes is not being delivered 

to the node with higher prices. Staff, however, notes that available transfer 

capability between places—and the transmission investment that maintains that 

capability—may not be the only variables relevant to persistent price differences.

To calculate this metric, staff used real-time prices at load and generator points. 

Staff gathered these prices from ABB Velocity Suite. To avoid placing excessive 

weight on highly unusual prices, staff used the 95th and 5th percentiles of prices, 

rather than maximum or minimum prices, at each load and generator point in each 

year. Staff then calculated market-wide average high and low generator and load 

prices in each year. Using this information, staff identified points whose high or low 

prices were at least one standard deviation higher or lower than the market-wide 

averages in each year.
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Staff identified high-priced and low-priced points in 2012, 2013, and 2014 to 

determine where price separation occurred persistently and had not yet been

resolved, based on data available as of the time this report was being prepared. To 

focus on the persistence of price separations, staff then calculated how long ago the 

current run of high or low prices began. There are many high-priced and low-priced 

points.
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Slide 8

 

 

Source: Staff analysis of ABB Velocity Suite price data

As shown on this slide staff identified areas within each RTO that contain multiple 

points with persistent price separations in the same direction. Finally, staff identified 

for each region the longest period of price separation experienced by a point in that 

region. That number is the RTO/ISO Price Differential metric for that region.
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Slide 9

RTO/ISO Market Price Differential 

Metric for Select Regions

Region 

identified 

by staff

Baltimore, 

aaryland

Upper 

teninsulaDelmarva teninsula

Long Island, 

New York

Northwestern 

New Jersey

North-central 

aISO

Western 

Stt

Dreater 

/hicago

North DakotaSouth Dakotaainnesota 

border

New York-

/anada border

Northern

New York

West-central 

North Dakota

The Deysers, 

/alifornia

Direction Iigh Iigh Iigh Iigh Iigh Iigh Low Iigh Low Iigh Low Iigh Low Low Low Low Low

Start of 

price 

differential

‘05 ‘05 ‘06 ‘07 ‘07 ‘05 ‘05 ‘08 ‘07 ‘10 ‘06 ‘12 ‘10 ‘06 ‘06 ‘10 ‘11

Years of 

persistence 

through 

2014

10 10 9 8 8 10 10 7 8 5 9 3 5 9 9 5 4

This slide summarizes these results. As you can see, there are several regions that 

experienced significant price differentials for up to 10 years, at least through 2014. 

At this point, I would like to emphasize a few important caveats. By themselves, 

these metric results do not prove that transmission capacity should necessarily be 

added in any of these areas. These data merely provide one indication that it could 

be useful to explore the economics of adding new transmission capacity in these 

regions. Furthermore, significant changes in underlying fundamental inputs to 

electricity prices, like the types of large-scale changes in relative fuel prices that 

we’ve seen in recent years, could greatly impact price trends going forward. 

Accordingly, it would likely be very useful to continue updating this type of analysis as 

more recent data become available. 
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Slide 10

Baseline Transmission 

Investment Metrics

 Basic measures of transmission investment

 Investment dollars and circuit-miles were 

normalized based on associated retail load

 Main use is to permit before-and-after comparison 

following relevant changes in policy

Thank you, James. The third category of metrics is designed to permit analysis of the 

impact of Commission policy changes by allowing the comparison of key values before 

and after policy changes take place. This category includes three interrelated 

metrics: (1) Load-weighted Transmission Investment; (2) Load-weighted Circuitmiles; and (3) Circuit-miles per Million Dollars of Investment. In combination, these 

three metrics allow for a comparison of how much transmission infrastructure has 

been developed in each region and the relative cost of that investment. Ben, who 

also led the development of these metrics, will now discuss each metric in turn.
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Slide 11

Load-Weighted 

Transmission 

Investment Metric

This metric describes the load-weighted dollar value of transmission facilities that 

went into operation each year from 2008-2014 in the eight NERC regions of the 

contiguous U.S. Weighting transmission investment dollars by associated retail load 

allows for comparisons between regions of different sizes. While more load-weighted 

investment may not always be better than less investment, tracking how these values 

change following changes in Commission policy may be informative.

Transmission project data are from the CThree Group’s North American Electric 

Transmission Projects database, and load data are from NERC’s 2014 Electricity 

Supply & Demand database. Staff converted nominal cost or budget figures to 2014 

dollars using the annual average of the consumer price index for all urban consumers. 

To calculate the final, load-weighted metric, staff divided the normalized investment 

figures for each NERC region for each year by the retail load in each year.
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Slide 12

U.S. Incremental Transmission 

Investment 2008-2014

12

$19.70 

$7.28 

$5.31 $5.05 $3.93 $4.25 

$5.00 

$2.42 

$0.88 

TRE 2013 w/o CREZ

$2.56

$4.72 

$3.17 $2.80 $2.61 $2.34 $2.19 $1.88 $0.88 $0.51 

$0

$4

$8

$12

$16

$20

08 11 14 08 11 14 08 11 14 08 11 14 08 11 14 08 11 14 08 11 14 08 11 14 08 11 14

TRE SPP NPCC WECC RFC All Regions MRO SERC FRCC

All New and Upgraded Projects in Operation, $/MWh

Sources:  Three Group, N9w/

Slide 12 shows load-weighted incremental transmission investment in dollars per MWh 

in the eight NERC regions of the contiguous U.S. from 2008 to 2014. The figures in red 

represent the load-weighted investment across all seven years, while figures in black 

refer to the highest load-weighted dollar figure in each region.

Overall, the average load-weighted transmission investment for all regions for all 

years is over two dollars per MWh of load, although investments are “lumpy” for most 

regions, as is typical for large infrastructure projects. Due to a major spike in 

transmission investment in 2013, the average load-weighted investment for TRE (the 

Texas Regional Entity) over all years exceeds four dollars per MWh. Five of the eight 

NERC regions (SPP, NPCC, WECC, RFC, and MRO) are in the range of approximately $1-

3/MWh on average over the period, while two regions (SERC and FRCC) fall below one 

dollar per MWh on average over the period. The metric shows a generally increasing 

trend of load-weighted investment over the period, with all regions except FRCC and 

MRO reporting the greatest load-weighted investment in 2013 or 2014.

The highest all-year average investment over the period, of $4.72/MWh, and highest 

single-year metric ($19.70/MWh in 2013) was in TRE. This was due to the 

approximately $6.5 billion of projects—the largest single-year investment of any 

region—that went into operation in 2013, of which approximately $5.7 billion was 
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under Texas’ Competitive Renewable Energy Zone (CREZ) initiative, which aimed to 

alleviate congestion and integrate wind capacity into the electric grid. Excluding this 

large CREZ investment in 2013, investment in that year would be $2.56/MWh and the 

TRE regional average investment would be $2.22/MWh, much closer to the all-region 

average. Thus the changes in this metric over the period perfectly illustrate the 

powerful impact of one particular policy initiative –Texas’ CREZ initiative.
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Slide 13

Load-Weighted CircuitMiles Metric

The next metric describes the load-weighted circuit-miles of transmission line added 

from 2008 to 2014. As with the previous metric, weighting transmission circuit-miles 

by associated retail load allows for comparisons between regions of different sizes. 

For this metric, staff filtered the data in the C Three Group database, removing the 

data associated with those projects that do not include a line component and a 

limited number of projects without a NERC region designation, or with multiple 

designations.

To determine the number of circuit miles for each project, staff multiplied reported 

line miles by the number of reported circuits. In cases where the number of circuits 

was not reported, staff conservatively assumed that the line has only one circuit.

To arrive at the final metric of load-weighted circuit miles, staff divided the circuitmile figure for each NERC region for each year by that region’s retail load.
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Slide 14

Circuit-miles of Transmission 

Added in U.S. 2008-2014

18.3

8.5

5.1

3.4 2.5 2.3 1.7 1.4 1.0

TRE 2013 w/o CREZ

4.0

5.7

3.4 2.6 1.9 1.8 1.2 1.1 1.0 0.7

0

4

8

12

16

20

08 11 14 08 11 14 08 11 14 08 11 14 08 11 14 08 11 14 08 11 14 08 11 14 08 11 14

TRE SPP MRO All Regions WECC NPCC RFC SERC FRCC

New and Upgraded Lines in Operation, Circuit-miles/TWh

Sources:  Three Group,

Slide 14 shows load-weighted transmission line additions in circuit-miles/TWh from 

2008 to 2014. 

Overall, the results for this metric are similar to those for the previous metric. TRE 

and SPP lead, and SERC and FRCC lag, the other regions in terms of load-weighted 

circuit-miles added, with five regions (WECC, NPCC, RFC, SERC and FRCC) below the 

all-region all-year average of approximately two circuit-miles/TWh. 

TRE added the most circuit-miles on a load-weighted basis. As noted above, this is 

mainly due to the CREZ projects, most of which included a relatively long line 

component. Only WECC built longer lines on average than TRE, but it added fewer 

circuit-miles on an absolute basis and, because its load is almost twice that of TRE, on 

a load-weighted basis as well.
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Slide 15

Circuit-Miles Added Per 

Million Dollars Metric

This last metric is designed to provide a basis for assessing the cost impact of 

different policy choices or factual circumstances on transmission investment. 

Specifically, this metric divides the circuit-miles of transmission line added in the 

contiguous U.S. from 2008-2014 by the amount of money invested over the same 

period in million dollars of investment. Data for this metric are also taken from the C 

Three Group’s transmission database. Staff filtered the data as described earlier.
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Slide 16

Circuit-miles Added per Million 

Dollars 2008-2014

2.9

5.7

2.4

9.2

1.7

1.7 1.6 1.4 1.9 2.0 1.8 1.4 1.3 1.3 1.1 0.8 0.8 0.7

0

2

4

6

8

10

08 11 14 08 11 14 08 11 14 08 11 14 08 11 14 08 11 14 08 11 14 08 11 14 08 11 14

MRO FRCC SERC TRE SPP All Regions NPCC WECC RFC

New and Upgraded Lines in Operation, Circuit-miles/$Million

Sources:  Three Droup, .

Slide 16 shows circuit-miles per million dollars of transmission investment from 2008 

to 2014.

Regions with higher figures represent a greater number of circuit-miles added per 

million dollars invested. By this measure, MRO built the most circuit-miles per million 

dollars on average across all years (1.7), compared to a total of 1.1 for all regions. 

RFC, NPCC, and WECC built the fewest circuit-miles per million dollars across all 

years, of less than one. The difference in circuit-miles per million dollars invested 

may be due to a range of factors, including terrain, population density, and state 

policy choices, among others.

TRE and FRCC appear to have the most variability in their results, although several 

projects that went into operation in TRE in 2008, and FRCC in 2010 and 2012, have 

circuit-mile data but no associated dollar figure, which causes those years to appear 

as outliers in the figure above. SPP appears to have the least variability in this metric 

across the years. From a developers’ perspective, less variability in costs would likely 

be desirable, but more research is necessary to determine what may be driving 

differences in the number of circuit-miles built per million dollars among these 

regions.
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I would like to emphasize that care should be taken in attempting to use the results of 

this metric to gauge the “cost-effectiveness” of different regions’ transmission 

investments because much of the cost of a project is driven by the highly variable 

physical and regulatory challenges particular to each region, project, or developer. 

Nevertheless, staff believes that this metric, in combination with the other two I’ve 

just discussed, can provide useful insights into the impact of Commission policy 

changes, particularly when considered over time.
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Slide 17

Item No. A-4

March 17, 2016

Transmission Metrics: 

Initial Results

Thank you, Mr. Chairman and Commissioners. This concludes our presentation and we 

welcome any questions you may have.