i
ii

Staff Analysis of

Uplift in RTO and ISO Markets

August 2014

For further information, please contact:

William Sauer

Office of Energy Policy and Innovation

Federal Energy Regulatory Commission

888 First Street, NE

Washington, DC 20426

(202) 502-6639

william.sauer@ferc.gov

This report is a product of the Staff of the Federal Energy Regulatory Commission. The 

opinions and views expressed in this paper represent the preliminary analysis of the 

Commission Staff. This report does not necessarily reflect the views of the Commission.
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Contents 

I. Executive Summary.......................................................................................................................1

II. Introduction ..................................................................................................................................3

III. Uplift Credits.................................................................................................................................4

A. Trends........................................................................................................................................5

B. Concentration............................................................................................................................7

C. Correlation Between Uplift and Potential Market Drivers......................................................10

IV. Uplift Charges..............................................................................................................................16

A. Daily Charge Volatility.............................................................................................................16

B. Frequency of Uplift Charge Rates............................................................................................17

V. Transparency...............................................................................................................................21

A. A Comparison of Public and Non-Public Uplift Data ...............................................................21

B. Publicly Available RTO and ISO and MMU Uplift Data ...........................................................26

Appendices

Appendix A ...........................................................................................................................................29

Appendix B............................................................................................................................................30

Appendix C............................................................................................................................................33

Appendix D ...........................................................................................................................................38

Appendix E............................................................................................................................................41
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I. Executive Summary

This paper is part of an effort to evaluate matters affecting price formation in the 

energy and ancillary services markets operated by Regional Transmission Operators 

(RTOs) and Independent System Operators (ISOs) subject to the jurisdiction of the Federal 

Energy Regulatory Commission (FERC or Commission). It covers the period 2009-2013 

and focuses on the levels, trends, volatility and transparency of uplift costs. Data 

underlying this report were submitted confidentially to the Commission and have been 

aggregated to an appropriate level to mask the underlying data.1

As noted by the Commission in the public notice announcing the commencement of 

a proceeding to evaluate price formation issues, locational marginal prices for energy and 

ancillary services ideally would reflect the true marginal cost of production, taking into 

account all physical system constraints, and fully compensate all resources for the variable 

cost of providing service.2

 The RTOs and ISOs would not need to commit any additional 

resources beyond those resources scheduled economically; load would reduce 

consumption in response to price signals such that market prices would reflect the value of 

electricity consumption without the need to administratively curtail load. 

In reality, however, RTO and ISO energy and ancillary services market outcomes are 

impacted by a number of technical and operational limitations.

3 Modeling, software and 

certain other limitations are, to some extent, inherent in the complexity of the electric 

system and the tools available today to maintain reliable operations.4 For example, 

technical limitations in the market software prevent RTOs and ISOs from fully modeling all 

of the system’s physical constraints. If physical constraints (e.g., voltage constraints) are 

not accurately reflected in the system model used to clear the market, the software 

outcome may not clear the resources needed to resolve all such constraints. In such a case, 

system operators may have to manually dispatch a resource that is needed to resolve a 

constraint (and manually re-dispatch other resources), with resulting energy and ancillary 

service prices not reflecting the marginal cost of production. RTOs and ISOs provide make-

 1 Commission Staff appreciates the responsiveness of the RTOs and ISOs in addressing questions about

uplift in their regions. 

2 See Notice, Price Formation in Energy and Ancillary Services Markets Operated by Regional Transmission 

Organizations and Independent System Operators, Docket No. AD14-14-000 (June 19, 2014).

3 Although the discussion herein focuses on RTO and ISO markets, similar technical and operational 

limitations also impact the efficient commitment of resources by electric utilities operating in other market 

structures.

4 Other efforts, like the annual market software conference, are intended to make progress on these 

longer term issues. See http://www.ferc.gov/industries/electric/indus-act/market-planning.asp.
2

whole payments, or uplift payments, to resources whose commitment and dispatch 

resulted in a shortfall between the resource’s offer and the revenue earned through market 

clearing prices. 

Nonetheless, understanding the reasons for uplift payments, the magnitude of uplift 

payments, and the impact on market participants and customers may help to shed light on 

markets, operations or infrastructure improvements to reduce the need for uplift 

payments. Preliminary findings indicate that:

 Uplift payments (i.e., credits) have been highly concentrated and recurring on a 

geographic or resource basis.

 Uplift payments are closely related to market fundamentals, including energy 

and fuel costs.

 Uplift payments are closely related to price divergences between day-ahead and 

real-time markets.

 The volatility of uplift costs varies across RTOs and ISOs and is trending upwards 

in three of the five markets studied.

 Uplift payments and the reasons they are incurred lack transparency.

This paper is intended to spur discussion and lead to a more comprehensive 

understanding of the drivers and market impacts of uplift costs. The conference scheduled 

for September 8, 2014, will provide one opportunity to learn the views of market 

participants, RTOs and ISOs, and market monitoring units (MMU).

Regardless of the underlying causes of uplift, a failure to make the causes 

transparent and to price them into the energy and ancillary services markets can 

undermine the effectiveness of price signals and efficient system utilization, and mute 

investment signals. Volatile uplift charges may also create financial uncertainty for 

customers, depress liquidity and reduce market efficiency.
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II. Introduction

This paper explores historical trends and characteristics of uplift and the statistical 

relationship between uplift and certain market fundamentals in the wholesale markets of 

California Independent System Operator (CAISO), ISO New England, Inc. (ISO-NE), 

Midcontinent Independent System Operator (MISO), New York Independent System 

Operator (NYISO) and PJM Interconnection, LLC (PJM).5 It is organized around three 

topics: uplift credits, uplift charges and data transparency. Throughout this paper the term 

“uplift credit” refers to a payment to a generator or other resource and “uplift charge” 

refers to an RTO’s or ISO’s recovery of uplift costs from market participants. 

This paper does not attempt to assess whether uplift costs are too high or too low or 

whether specific uplift costs are warranted. Rather, the analysis presented here is intended 

to facilitate discussions concerning the matter of uplift as it affects price formation in the 

RTO and ISO energy and ancillary services markets. It is worth noting that costs giving rise 

to uplift payments, such as commitment costs, are not unique to RTO and ISO markets. 

These costs are inherent in reliably operating any electric transmission system. 

Two sources of data were used. Data for the period 2009-2011 were obtained from 

each RTO and ISO in response to a FERC staff data request and includes: (1) daily uplift 

credits (uplift credits are calculated based on total revenues and costs for a given calendar 

day) and details on why individual uplift credits were made; (2) details on resources 

receiving uplift payments, including fuel and driver types (e.g., steam turbine or 

combustion turbine) and output capabilities; (3) bid information and marginal cost 

estimates during periods when uplift credits were made; and (4) details on uplift charges. 

Data for 2012 and 2013, where available, were obtained from RTO and ISO data 

submissions pursuant to Order No. 760.6

 Note that due to incomplete data not every 

analysis reported in this paper covers the complete period 2009-2013.

 5 Southwest Power Pool is not included in this report because its day-ahead market was launched in 

2014.

6 Enhancement of Electricity Market Surveillance and Analysis through Ongoing Electronic Delivery from 

Regional Transmission Organizations and Independent System Operators, Order No. 760, FERC Stats. & Regs. ¶ 

31,330 (2012). Paragraph 35 of Order No. 760 states the Commission may make publicly available staff white 

papers, among other things, that contain analyses derived from data that the Commission uses.
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III. Uplift Credits

Uplift credits are payments made to resources whose commitment and dispatch by 

an RTO or ISO result in a shortfall between the resource’s offer and the revenue earned 

through market clearing prices. While shortfalls can occur for many reasons, three primary 

reasons are: (1) a resource’s operating costs and limits not being reflected in prices; (2) 

unmodeled system constraints; and (3) the dispatch and commitment of inflexible 

resources or the commitment of resources ineligible to set price. Each of these is explained 

further below.

RTOs and ISOs use a system of locational marginal pricing to establish clearing 

prices in the energy and ancillary services markets. At a very basic level, locational 

marginal pricing relies on the economic theory of variable, least-cost pricing. Under this 

theory, resources will offer their variable cost of production. Markets will clear in a leastcost manner based on operational practices and will send appropriate short-term price 

signals based on the marginal cost of production. Market clearing prices do not typically 

reflect certain components of a resource’s actual operating costs (e.g., startup costs).7

 

Because these costs are not reflected in market clearing prices, they must be recovered 

through infra-marginal revenue, which is the revenue a resource receives when the market 

clearing price exceeds its marginal cost. A resource may be able to fully recover start-up 

costs when it is primarily run as baseload, but may not recover start-up costs when 

operated for only a few hours each day. 

Uplift credits may also arise due to an inability to fully model all of the system’s 

physical constraints. If constraints, including voltage constraints, are not accurately 

reflected in the system model used to clear the market, the resulting market prices will not 

reflect the marginal cost of the resources needed to resolve constraints.8

 In such a case, 

system operators may have to manually commit and dispatch a resource that is needed to 

resolve a constraint (and manually re-dispatch or de-commit other resources). When these 

situations occur and the clearing locational marginal prices are insufficient to cover a 

resource’s costs, RTOs and ISOs provide uplift credits to ensure that resources which

followed the dispatch instructions are not harmed financially and thus remain willing to 

follow manual dispatch instructions. 

Another potential cause of uplift is when an expensive resource is committed to be 

online to meet system requirements but some inherent inflexibility (e.g., minimum run 

 7 Start-up costs are generally the costs associated with bringing the boiler, turbine and generator from 

shut-down conditions to a state ready to synchronize to the system. 

8 The security constrained economic dispatch algorithms used by RTOs and ISOs are based on a direct 

current approximation of the transmission system and thus do not directly include voltage and stability 

constraints that exist in an alternating current system. 
5

time) requires the resource to operate while it is uneconomic.

9

 In this situation, the 

resource is precluded from setting the clearing price and the price is set by a less expensive 

(and marginal) resource that is backed down to make room for the inflexible resource

commitment. For instance, a resource with a long minimum run time may need to be 

operated when it is uneconomic to do so. During many of those hours, the resource would 

receive less revenue than needed to cover its operating costs, so that an uplift payment is 

needed to compensate the resource for following the operator’s dispatch signal. 

Additionally, resources that are committed for reliability purposes after the day-ahead 

market results are posted are typically operating at minimum output levels and not eligible 

to set price unless dispatched for energy and thus may operate at a loss. The commitment 

costs associated with such resources can be significant because of their operating 

characteristics. 

Given the complexity of the electric system, it may be unrealistic to expect that uplift 

credits can be entirely eliminated from existing market designs. However, a system that 

takes into account physical system constraints and resource-specific operating 

requirements when determining the marginal cost of production would lessen the need for 

out-of-market actions that give rise to the need for uplift credits. That said, uplift credits

reflect a component of the operating cost necessary to meet system needs and it is 

important to understand these costs and their role in the marketplace. 

As noted above, the complexities of the electric system and the use of locational 

marginal pricing can give rise to the need to pay resources additional revenues (e.g., uplift 

credits) to keep them financially whole when they follow the directives of the RTO or ISO. 

To appreciate the significance of uplift that has been occurring in the RTO and ISO markets, 

the following sections highlight the preliminary observations about overall trends, 

concentration, and volatility of uplift credits and assess the relationship with other market 

fundamentals. 

A. Trends

Uplift credits in absolute terms are large. Over the course of the five years examined 

(2009-2013), and across the RTOs and ISOs studied, they amounted to more than $5.5 

billion dollars.10 While large in absolute terms, uplift credits are relatively small when 

viewed in relation to load served.11 As shown in Figure 1, uplift credits ranged between 

 9 The term “minimum run time” generally refers to the minimum number of hours of operation the 

generator requires the RTO or ISO to recognize when committing the generator.

10 Appendix A contains annual uplift totals for each RTO and ISO. The size of total uplift credits may be 

influenced by alleged wrongful behavior that culminated in settlements with the Commission. See e.g., In Re 

Make-Whole Payments and Related Bidding Strategies, 144 FERC ¶ 61,068, at P 85 (2013).

11 Annual average day-ahead locational marginal prices varied between $28/MWh and $57/MWh across 

the RTOs and ISOs.
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approximately $0.30/MWh and $1.40/MWh, a fraction of the energy market prices during 

these periods. 

Figure 1: Total Annual Uplift Credit by RTO and ISO ($/MWh)
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B. Concentration

Uplift credits, or payments, appear to be highly concentrated within an RTO or ISO. 

To assess the degree to which they are concentrated, a review of the total uplift credits 

received by each plant reveals that most plants receiving uplift payments received small 

credit totals (under $1 million), while a handful of plants received substantially larger

credit totals (varying between $5 million to over $80 million). Figure 2 displays annual 

uplift credit totals for individual plants during the most concentrated year, defined as the 

year when the greatest number of plants received uplift payments totaling more than $10 

million. As can be seen in that Figure, four plants in CAISO, three in ISO-NE, two in MISO, 

19 in PJM and seven in NYISO received more than $10 million in the selected years.12 As a 

comparison, totals for plants receiving more than $5 million are as follows: five plants in 

CAISO, eight in ISO-NE, eight in MISO, 33 in PJM and ten in NYISO. Figures B.1 through B.5

in Appendix B show the yearly distributions.13 These figures suggest that total uplift 

credits are not distributed evenly among resources.

 12 For each RTO or ISO, the year selected was the year in which the highest percentage of total uplift 

payments were made to plants receiving at least $10 million. The analysis contained in Figure 2 and Figure 3 

focuses on plants, which may represent multiple resources.

13 Uplift payment totals have not been included for MISO in 2012 or 2013 and do not include reactive 

services related uplift for PJM. Totals for ISO-NE in 2012 only represent the third and fourth quarter. 

Figure 2: Concentration of Uplift Payments by Plant During each RTO’s or ISO’s Most 

Concentrated Year
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Figure 3 shows the percent of uplift paid to plants receiving uplift credits in excess 

of $5 or $10 million for the most concentrated year. Market participants that received 

more than $5 million in uplift credits received over half of the total annual uplift credits in 

four of five RTOs or ISOs. 

Figure 3: Percent of Annual Uplift Credits Paid to 'Large Recipients' Plants

Year Studied

All >$5 Million 

Receivers

All >$10 Million 

Receivers

CAISO 2012 58% 54%

ISO-NE 2013 53% 32%

MISO 2010 29% 15%

PJM 2013 82% 70%

NYISO 2009 81% 71%

As noted previously, there are legitimate reasons why certain resources may receive 

large uplift credits. However, uplift credits made to the same resources year after year may 

indicate that market pricing is consistently failing to fully capture costs associated with 

committing and dispatching those resources or the existence of market work-arounds. For 

example, eight plants in NYISO each received more than $10 million per year over the 

course of 2009-2013. Of these eight plants, four received more than $10 million in every 

year studied. In PJM, one plant received uplift credits in excess of $60 million in each year 

studied, with the exception of 2012. As a point of comparison, plants under reliability must 

run agreements (RMR) can receive payments comparable to what a number of plants have 

received in uplift credits.14 However, RMR agreements are typically for a defined period 

and are filed with the Commission for approval.

To better understand whether localized reliability concerns contribute to the 

concentration and persistence of uplift credits, a metric of average uplift credit for each 

MW of installed capacity was developed for each RTO and ISO zone. The resulting $/MW 

figures were then grouped into six levels and mapped to provide a visual representation of 

the relative intensity of average uplift credits received in a particular area.15 This analysis 

was conducted for each year from 2009 through 2011. Figure 4, below, showing the 

 14 Several recent RMR examples in PJM include 140 FERC ¶ 61,080 (Elrama and Niles (GenOn Power 

Midwest, LP)) and 135 FERC ¶ 61,190 (Cromby and Eddystone (Exelon Generation Company, LLC)). A recent 

example in MISO includes, Midcontinent Indep. Sys. Operator, Inc., Docket Nos. ER14-109-000 & ER14-111-

000, at 1-2 (Dec. 12, 2013) (delegated letter order) ((Gaylord (Consumers Electric Company)).

15 California Air-Quality Management districts were used to give greater granularity to the data.
9

mapped 2011 uplift credits,

16 illustrates a few emerging patterns. Notably, uplift credits 

are consistently higher on a per MW basis in certain regions. These include the DominionVirginia and Delmarva zones of PJM and the NYISO zones in and around New York City. 

The NYISO North Zone (D) and Genesee Zone (B) had uplift credits of $5000 per MW and 

greater in both 2010 and 2011. Uplift credits per MW in Maine and Western Massachusetts 

have been higher than elsewhere in the ISO-NE region, although they fluctuated year-toyear. Among the RTOs and ISOs analyzed, MISO tends to have the lowest uplift credits per 

MW in all of its regions, although Wisconsin, Upper Michigan and Indiana showed some 

relatively high amounts in 2010. In CAISO, uplift credits per MW have tended to be 

relatively high in the South Coast Air Quality Management (AQM) district (the urban 

portions of Los Angeles, Riverside and San Bernardino counties as well as all of Orange 

County) and the North Coast Unified AQM district (Humboldt, Del Norte and Trinity 

counties in northern California). 17 San Diego also showed relatively high uplift credits per 

MW in 2011, though not as high as payments in the South Coast and North Coast Unified 

AQM districts.

 16 Maps showing the density of uplift credit totals geographically for each of the years 2009 through 

2011 are included in Appendix C.

17 Note that a small percentage of the total uplift data for 2009-2011 are not represented by these maps. 

The maps do not include any information from 2012-2013.

Figure 4: 2011 Uplift Credits Mapped by Region
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Even in areas with relatively low uplift costs, individual plants may receive large 

amounts of uplift payments. For instance, some units in the Wisconsin and Upper 

Peninsula of Michigan received substantial uplift payments to provide voltage support, 

despite the fact that this zone has relatively low uplift density.18 

C. Correlation Between Uplift and Potential Market Drivers

This section explores the relationship between uplift credits and prices in three 

seemingly similar but distinct ways; correlations between uplift and: (1) relative fuel 

prices; (2) clearing prices; and (3) day-ahead and real-time price spreads. 

1. Impact of Fuel Prices

Changes in fuel prices can change the dispatch order of resources, which in turn will 

affect the opportunity for infra-marginal revenues. As the level of infra-marginal revenues

changes so, too, does the need for uplift payments to compensate resources for costs not 

recovered through the clearing prices. For example, as the marginal cost of a coal resource 

approaches the cost of the cleared resource, the coal resource may earn less infra-marginal 

revenue that can be used to offset costs not included in its energy bid. In addition, some 

fuel-related costs (e.g., start-up costs) are not included in an energy bid, so any increase in 

fuel costs would tend to increase uplift credits. Further, resources that are needed for local 

reliability may not be dispatched when relative fuel prices change such that the resource is 

no longer economic. In such a circumstance, the resource may be committed for reliability 

and receive uplift credits to cover its operating costs.

To ascertain the relationship between the level of uplift credits and fuel prices, uplift 

credits paid to natural gas and coal resources in MISO and PJM were assessed. There 

appears to be clear trends in uplift credits to coal generation units associated with fuel 

prices. As shown in Figure 5, uplift credits paid to coal generation units have increased as 

natural gas prices relative to coal prices have decreased. In both MISO and PJM, the 

correlation between relative fuel prices and uplift credits to coal generation units has been 

fairly strong, -0.66 and -0.52, respectively. Additional charts showing this trend, including 

ones illustrating uplift to natural gas-fired plants, are included in Appendix D. Appendix D

also includes information on uplift totals for the year 2011 by resource fuel type and prime 

mover. 

19

 18 See Midwest Independent Transmission System Operator, Transmittal Letter, Docket No. ER12-678-

000, at 3 (filed December 22, 2011). 

19 Prime movers are devices that convert one energy form (such as heat from fuels or the motion of wind 

or water) into mechanical energy. Examples include steam turbines, combustion turbines, reciprocating 

engines, and water turbines.
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2. Correlation Between Uplift Credits and Clearing Prices

The relationship between uplift credit and market clearing prices is not clear-cut. 

Uplift credit may either increase or decrease as prices rise. Uplift credits and prices may be 

negatively correlated when, for example, clearing prices rise relative to bids of baseload 

resources, allowing the baseload resource to receive more infra-marginal revenue that can 

be used to offset costs not reflected in clearing prices. Further, to the extent the clearing 

prices are suppressed because of unit commitment decisions, the need for or level of uplift 

credits may increase. Conversely, uplift credits and clearing prices may be positively 

correlated to the extent both are influenced by fuel costs. Specifically, increases in fuel 

costs result in higher variable operating costs and higher start-up and no-load costs. 

Higher variable operating costs put upward pressure on prices. 

Total monthly uplift credits20 and locational marginal prices were used to assess 

how uplift credit totals change with movements in day-ahead prices.

21 For nearly all the 

RTOs and ISOs, the data showed a strong, positive correlation between uplift credits and 

locational marginal prices. This suggests that uplift credits tend to rise with increases in 

 20 Monthly uplift figures are the simple sum of daily uplift credits.

21 Monthly figures were used to limit “noise” associated with daily volatility.

Figure 5: Uplift Credits to Coal Burning Units in MISO and PJM
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locational marginal prices. Figure 6 shows this trend for MISO - the strongest, positive 

correlation of any RTO or ISO studied. Appendix E contains figures for ISO-NE, NYISO and 

PJM (Figures E.1 through E.3). Although the figures show day-ahead locational marginal 

prices, the correlations between real-time locational marginal prices and uplift credits 

were very similar to the day-ahead correlations. In addition, there were clear seasonal 

patterns for both locational marginal prices and uplift, with both uplift and locational 

marginal prices peaking in the summer and winter and trailing off in the spring and fall. 

However, it is difficult to discern the relative impact of higher load levels versus higher fuel 

costs on uplift credits. 

For CAISO, as found in Figure 7, there was a slight negative correlation between dayahead locational marginal prices and uplift. Interestingly, this negative correlation 

weakened with the addition of data from 2012 and 2013. This pattern is not consistent 

with the suggestion that fuel price changes are driving uplift costs in CAISO.

Figure 6: Uplift and Locational Marginal Price Correlation in MISO

Notes: The day-ahead locational marginal prices are CINERGY.HUB from Ventyx. The Pearson correlation coefficient (r) was used to assess 

correlation between monthly locational marginal price and monthly uplift credits. 
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3. Impact of Day-Ahead and Real-Time Price Spreads

To further understand the relationship between uplift credits and prices, day-ahead 

and real-time price differences and uplift costs were assessed. Price spreads driven by high 

real-time prices relative to day-ahead prices may indicate that insufficient resources were 

committed day-ahead to reliably operate the system in real-time. Conversely, relatively 

low real-time prices could indicate that more resources were committed than were needed. 

The difference between the resources that clear in the day-ahead market or were 

committed prior to the real-time and the resources that are ultimately needed for real-time 

operations could influence uplift costs. 

To ascertain the degree of any relationship between uplift credits and price spreads, 

the differences between day-ahead and real-time prices (hourly DA/RT spreads) at major 

price points in each RTO and ISO were identified. The absolute value of each DA/RT spread 

was used to calculate a monthly average of hourly DA/RT spread values. The values 

showed a clear correlation between price deviations and uplift payments. The correlation 

coefficient values for ISO-NE, MISO and NYISO were relatively strong at 0.85, 0.65 and 0.68, 

respectively. Analysis of PJM data also suggested a strong correlation, although less so at 

0.47. Interestingly, these correlations weakened with the addition of 2012 and 2013 data. 

Similar to the above analysis on locational marginal prices, CAISO stood out in comparison 

to the other RTOs and ISOs and exhibited weak correlation between price deviations and 

Figure 7: Uplift and Locational Marginal Price Correlation in CAISO

Notes: The day-ahead locational marginal prices are TH_SP15_GEN-APND from Ventyx. The Pearson correlation coefficient (r) was used to 

assess correlation between monthly locational marginal price and monthly uplift credits. 
14

uplift (0.23).22 Results of this analysis are shown in Figures 8 and 9 for NYISO and PJM and 

in Appendix E for the other RTOs and ISOs (Figures E.4 through E.6).

The strong correlation between uplift credits and price spreads between the dayahead and real-time markets suggests the accuracy of commitment decisions may strongly 

influence uplift and day-ahead and real-time price differences in RTO and ISO markets.

 22 Unlike other RTOs and ISOs, CAISO operates an hour-ahead market in addition to operating day-ahead 

and real-time markets. The correlation between day-ahead/hour-ahead and hour-ahead/real-time prices did 

not show strong relationships between these price spreads and uplift credits.

Figure 8: Uplift and DA/RT Price Spreads in NYISO

Notes: The day-ahead locational marginal prices are ZONE J from Ventyx. The DA/RT spread is the monthly average of the hourly, absolute 

value difference between the day-ahead and real-time locational marginal prices. The Pearson correlation coefficient (r) was used to assess 

correlation between monthly locational marginal price and monthly uplift credits.
15

Figure 9: Uplift and DA/RT Price Spreads in PJM

Notes: The day-ahead locational marginal prices are WESTERN HUB from Ventyx. The DA/RT spread is the monthly average of the hourly, 

absolute value difference between the day-ahead and real-time locational marginal prices. The Pearson correlation coefficient (r) was used to 

assess correlation between monthly locational marginal price and monthly uplift credits.
16

IV. Uplift Charges

While the preceding section focused on payments to resources (credits), this section 

focuses on uplift allocations (charges) to market participants. From the perspective of 

some market participants, unpredictable and highly volatile uplift charges tend to increase 

the risk of participating in the organized wholesale energy and ancillary services markets. 

If participants increase their bids to reflect increased risk or limit their participation in the 

market, this may result in increased market prices. This section presents an analysis of the 

volatility and uncertainty of uplift charges faced by market participants.

A. Daily Charge Volatility

To measure and compare daily uplift charge volatility in RTO and ISO markets, a 

coefficient of variation as a statistical indicator of volatility was employed. It shows the 

variation in values from the mean23 and is a frequently used statistical indicator when 

measuring and comparing volatility of data sets with different means, which is the case for 

the uplift charges in RTOs and ISOs. In the following analysis, the coefficient of variation is 

expressed as a percentage. 

As shown in Figure 10, there was volatility in uplift charges on an annual basis and 

three of the five RTOs and ISOs experienced increasing uplift volatility during the study 

period. In 2009, the coefficient of variation in ISO-NE was approximately 117%, while the 

second highest was in MISO (64%), followed by CAISO (58%), PJM (41%) and NYISO 

(36%).24 Annual uplift charge volatility in ISO-NE, PJM and NYISO increased in each year 

from 2009 through 2011. Notably, the volatility of uplift charges in ISO-NE increased to 

167% in 2011 and, on average, was about 146% during the study period, exhibiting 

substantially higher volatility relative to other RTOs and ISOs throughout the three-year 

study period. 25 

 23 The coefficient of variation is simply the standard deviation divided (normalized) by the mean of the 

daily uplift charges over the annual measurement period. A low coefficient of variation indicates that the data 

points tend to be very close to the mean, whereas a high coefficient of variation indicates that the data points 

are spread over a larger range of values.

24 During the three-year study period from 2009 through 2011, the average daily uplift charge per MWh 

was approximately $0.44/MWh in CAISO, $0.56/MWh in ISO-NE, $0.36/MWh in MISO, $1.13/MWh in NYISO

and $0.66/MWh in PJM. 

25 The ISO-NE internal market monitor has noted liquidity reductions due to uplift charge volatility. See 

ISO-NE, 2013 Annual Markets Report, May 1, 2014, at http://www.isone.com/markets/mkt_anlys_rpts/annl_mkt_rpts/2013/2013_amr_final_050614.pdf, Page 6.
17

B. Frequency of Uplift Charge Rates

The previous section shows how total uplift charges for the entire market 

participant pool change on a daily basis. In order to better understand the impact of uplift 

charge volatility, the distribution of volatility across market participants was assessed. The 

uplift charges that an individual market participant is responsible for paying can vary 

significantly due to, for example, positions taken in the markets or unexpected events that 

may cause deviations (e.g., generator trips). Focusing on an uplift charge rate ($/MWh) 

instead of total uplift charges allows parallels to be more easily drawn across market 

participants with different market positions.26 

Figures 11 through 13 depict the frequency of different uplift charge rate levels for 

day-ahead and real-time markets. In MISO during 2009-2013, day-ahead uplift charge 

rates were relatively consistent. MISO’s day-ahead uplift charge rates averaged 

 26 MISO and PJM are the only RTOs to publicly post the charge rates; charge rates for ISO-NE were 

calculated for the second half of 2012 and all of 2013. The day-ahead charge rate was calculated by dividing 

daily day-ahead uplift charge totals (in dollars) by total daily load obligation (in MWhs). Real-time rates were 

calculated by dividing daily real-time uplift charge totals (in dollars) by total daily deviations (in MWhs). 

Generation, load, virtual and import deviations were included in the real-time deviation calculation.

Figure 10: Annual Volatility of Uplift Charges by RTO/ISO
18

$0.04/MWh for the vast majority of days and were only above $0.25/MWh on two days.

Day-ahead uplift charge rates averaged $0.16/MWh in ISO-NE and $0.12/MWh in PJM. In 

ISO-NE and PJM, 78% and 93% of days contained day-ahead uplift charge rates at or below 

$0.25/MWh.

Real-time uplift charge rates, however, varied much more widely from day-to-day, 

occasionally reaching above $10/MWh. Daily uplift charge rates greater than $10/MWh 

never occurred in MISO. These high uplift charge rates were observed approximately 1%

of the time in PJM and 7% of the time in ISO-NE. The simple averages of real-time uplift 

charge rates ($1.23/MWh in MISO, $2.38/MWh in ISO-NE and $1.57/MWh in PJM) were 

generally much higher than day-ahead uplift charge rates.27

Real-time uplift charge rates display greater variation than day-ahead uplift charge 

rates. The distribution of real-time uplift charge rates in MISO and PJM was concentrated 

in the $0.50/MWh to $1.00/MWh and $1.00/MWh to $2.00/MWh ranges. In MISO and PJM, 

these two ranges accounted for about 46% and 63% of observed uplift charge rates, 

respectively. The number of uplift charge rates observed at higher price levels generally 

dropped progressively in MISO and PJM. Conversely, the ISO-NE real-time uplift charge 

rate distribution has greater frequency at both low and high rates, suggesting that market 

participants are more frequently exposed to either relatively low or relatively high rates. 

 These data show that in real-time a market participant in MISO, ISO-NE and PJM 

faces uncertain and volatile uplift charge rates. As a result, market participants may build 

risk premiums into any resource bids placed into real-time energy markets to shield them 

from the risk and uncertainty associated with unexpected uplift charge rates. 

 27 In this section, real-time PJM rates are the RTO RT Deviations rate. Because some uplift charges are 

allocated RTO-wide while others are allocated regionally, rates for East and West regions do not add up to 

RTO-wide rates. Different types of commitments are allocated to the deviation and reliability categories. 

Although the following is not exhaustive, units committed as part of a reliability analysis to meet forecasted 

real-time load are allocated to deviations. Units committed as part of a reliability analysis due to extenuating 

conditions are allocated to reliability. Additionally, if a unit is called to operate during the operating day and 

the locational marginal price for that unit does not exceed the unit’s cost for at least four, five-minute 

intervals of at least one clock hour, the costs are allocated to reliability. In the previous example, when the

locational marginal price does exceed the unit’s cost for at least four, five-minute intervals of at least one 

clock hour, the costs are allocated to deviations.
19

Figure 11: Frequency of Daily Uplift Charge Rates in MISO (2009-2013)

Figure 12: Frequency of Daily Uplift Charge Rates in ISO-NE (2012-2013)
20

Figure 13: Frequency of Daily Uplift Charge Rates in PJM (2009-2013)
21

V. Transparency

As noted elsewhere in this paper, there are numerous potential causes of uplift, 

some of which may not be transparent to the market. Failure to identify, make transparent,

and price such causes can result in uplift credits that undermine the effectiveness of market 

signals and efficient system utilization and mute investment signals. The Commission’s 

Electric Quarterly Report (EQR) has the potential to provide a great deal of detailed 

information regarding uplift.28 Sellers with market-based rate authority are required to 

report on a quarterly basis uplift credits received by day and by resource location. If data 

are reported accurately with this level of granularity, some concerns about transparency 

could be addressed. However, EQR data does not make transparent the underlying system 

information or the market reasons a resource received uplift. As discussed below, there 

may be opportunities for the RTOs and ISOs and their respective MMUs to improve upon 

and augment reporting on uplift payments.

In an attempt to ascertain the usefulness of publicly-available data on uplift credits, 

a comparative analysis of two sources of information – public EQR and RTO and ISO 

reports and non-public data - was undertaken. The analysis involved the comparison of 

publicly-available EQR data to non-public RTO and ISO data from 2009-2013 and 

considered: (1) whether the magnitude of uplift credits received by a resource reported in 

the EQR was similar to uplift credits paid to each resource as reported in the non-public 

RTO and ISO data; and (2) the degree to which the two sources of data provided similar 

levels of locational information. In addition to the comparative analysis of EQR data to 

non-public RTO and ISO data, there is a qualitative assessment of the information on uplift 

as reported publicly by the RTOs and ISOs and MMUs. 

A. A Comparison of Public and Non-Public Uplift Data

The non-public data are sufficiently granular in both location and time to allow an 

analysis of whether the information reported on a public basis is reported at the same level

of granularity, and whether the public source provides sufficiently transparent and 

meaningful uplift information. 

Certain entities, including those that received market-based rate authorization from 

the Commission, are required to file EQR reports with the Commission. These filings 

contain data on contracts and transactions for certain products, including uplift. Some 

entities, including certain cooperatives and municipalities, were not required to file EQRs

 28 See Elec. Mkt. Transparency Provisions of Section 220 of the Fed. Power Act, Order No. 768, FERC Stats. 

& Regs. ¶ 31,336 (2012), order on reh'g, Order No. 768-A, 143 FERC ¶ 61,054 (2013).
22

during the majority of the time period analyzed in this paper. Accordingly, while the EQR is 

believed to provide the most detailed public source of uplift data, not all uplift credits are 

reflected in the analysis.

A comparison of the aggregate uplift credits, reported as “sales” in market 

participants’ EQRs, with total uplift credits found in non-public RTO and ISO data shows 

that the non-public RTO and ISO data contained roughly $200 million more in uplift credits 

each year than what was reported in the EQR (See Figure 14). EQR uplift credits in MISO 

were routinely about 15% below the RTO’s figures. Potentially underreported uplift 

credits in PJM hovered around 20%, while in NYISO it varied between 29% and 49%. Some 

of the disparity between the two data sources may be attributable to certain entities not 

being required to report sales to the EQR, which is why EQR reported data for 2013 most 

closely matched RTO and ISO reported data.29

To ascertain the degree to which the two sources of information provide a similar 

level of transparency of uplift information, EQR data were compared to non-public RTO and 

ISO data on a location-specific basis.30 Initially, the number of unique settlement locations 

that received uplift credits reported in the EQR was compared to settlement locations in 

the non-public RTO and ISO data. In all cases, as seen in Figure 15, non-public RTO and ISO 

data contained additional settlement location granularity. Specifically, for MISO, NYISO and 

ISO-NE markets, the EQR data generally contained 70% to 80% of unique settlement 

locations found in RTO and ISO data. Unique settlement location instances in CAISO- and 

PJM-related EQR data were significantly fewer than in RTO and ISO data.31 

 29 Cooperative and municipal utilities are now required to file EQRs for transactions that occur on or 

after July 1, 2013. EQR totals for 2013 were queried on June 2, 2014 and, therefore, may not have captured

updated 2013 data reported after that date. Additionally, approximately 15% of historic filers had not filed 

EQR reports for the second half of 2013 by June 2, 2014. 

30 RTO and ISO data contained unique settlement locations for each resource receiving uplift credits; 

these were generally reflected in price node names or price node IDs. Unique settlement locations were 

identified for transactions reported in the EQR using the “Point of Delivery Specific Location (PODSL)” field. 

PODSL locations are not standardized in the EQR but are supposed to match the location specified in the 

contract. Per the EQR data dictionary, the PODSL is “the specific location at which the product is delivered if 

designated in the contract. If receipt occurs at a trading hub, a standardized hub name must be used.”

31 Each of the RTOs and ISOs, with the exception of CAISO, prepares a pre-formatted, EQR-ready report 

for their market participants containing information on sales made to the RTO or ISO, including uplift credits 

for which a market participant received payment. Each EQR filer may incorporate each RTO’s or ISO’s report 

along with additional data into its quarterly filing. Thus, even though individual filers bear responsibility for 

the timeliness and accuracy of their filings, the quality of information may, in many cases, reflect how each 

RTO or ISO prepares these pre-formatted, EQR-ready reports. In the case of CAISO, the divergence may be 

due to the lack of a pre-formatted, EQR-ready report being generated by CAISO; meaning that decisions on 

how to report settlement locations are entirely left to individual filers. Over 90% of the value of uplift credits 

reported in EQRs as sales in PJM provides no specific settlement location information, which may result from 

PJM’s pre-formatted, EQR-ready report. One way to improve the quality of EQR reports could be for the RTOs 

or ISOs to adjust the data provided in their EQR-ready reports. In the case of CAISO, this would entail the 

creation of a new report.
23

Figure 14: RTO/ISO Reported vs. EQR Reported Annual Uplift Credits
24

With the unique settlement locations identified, sales data from the EQR and RTO

and ISO data sources were matched and compared. Figure 16 shows the percentage of 

EQR-reported uplift credits that were matched to unique RTO and ISO settlement locations. 

Most of the ISO-NE, MISO and NYISO and some of the CAISO locations reported in the EQR 

contained sufficient descriptions of that location to allow them to be readily traced to an 

RTO and ISO settlement location.32 Very few of the PJM locations could be attributed to 

discrete locations.

 

32 The majority of the CAISO non-matched locations in 2010 and 2011 were reported in the 

EQR at SP-15. 

Figure 15: RTO/ISO Reported vs. EQR Reported Settlement Location Granularity
25

2009 2010 2011

CAISO 63% 39% 83%

ISO-NE 76% 95% 98%

MISO 91% 96% 97%

NYISO 93% 93% 94%

PJM 8% 6% 6%

The total values of uplift credits in dollars were then compared at the matched 

locations. As seen in Figures 14 and 16, the MISO EQR figures most closely matched the 

RTO’s data, while the other RTOs and ISOs occasionally had some very significant 

differences. Figure 17 shows the total percentage difference between EQR and RTO and 

ISO uplift credit data at only the matched locations. The figure for MISO may be interpreted 

to mean that EQR reported uplift credit totals were 1% higher, 2% lower and 3% higher 

than RTO and ISO credit totals in 2009, 2010, and 2011, respectively. This figure, however, 

does not account for differences at each settlement location but looks at the total for all 

matched locations.33 Positive differences between the data for some locations may offset 

negative differences for other locations, masking absolute differences. 

2009 2010 2011

CAISO -20% 17% 9%

ISO-NE -31% -12% 10%

MISO 1% -2% 3%

NYISO 13% 2% 17%

PJM 9% 1% 0%

 33 The total for all matched locations is a computation of the difference between EQR-reported uplift 

and uplift from the RTO and ISO data for each location with differences summed across locations.

Figure 17: Percentage Difference Between EQR and RTO/ISO Reported Uplift Credits at 

Matched Locations (RTO/ISO wide)

Figure 16: Percentage of EQR Reported Uplift Credits Matchable to a Unique RTO/ISO 

Settlement Location
26

This analysis was further refined to assess the absolute value differences between 

EQR and RTO and ISO data at each matched settlement location and weighted any 

divergences using total sales at that location, as found in RTO and ISO data. After 

accounting for these factors, EQR uplift data in every RTO and ISO, and most notably for 

CAISO, often diverged significantly from RTO and ISO reported uplift data. See Figure 18. 

2009 2010 2011

CAISO 62% 30% 17%

ISO-NE 47% 25% 15%

MISO 16% 8% 5%

NYISO 15% 3% 18%

PJM 9% 3% 22%

As noted above, the EQR data have the potential to provide valuable information on 

uplift credits by location and by day. However, the data suggest that EQR reporting, 

especially for sellers in PJM and CAISO, may not be providing substantially useful or 

accurate transparency. This is particularly true with respect to the location of the resource 

receiving uplift credits. Using EQR data to provide transparency on uplift credits and 

charges has limitations including limited background information on the type of uplift or 

the reason for incurring the uplift reported in the EQR. This information may be important 

when market participants and other stakeholders assess market-based solutions to uplift.

B. Publicly Available RTO and ISO and MMU Uplift Data 

This section focuses primarily on the degree to which RTOs and ISOs and their 

respective MMUs provide summary information, with some high-level discussion of the 

degree to which RTOs and ISOs add context to the data reported. RTOs and ISOs have the 

opportunity to provide additional transparency in several ways. First, RTOs and ISOs can 

provide summary data on uplift credits so that it is not necessary to review all the EQR 

filings for an RTO or ISO in order to understand general trends. Second, RTOs and ISOs can 

provide additional context, commentary or trends analysis for summary information 

provided. Third, RTOs and ISOs have information about the causes of uplift that is not 

reported in EQRs. 

Figure 18: Percentage Difference Between EQR and RTO/ISO Reported Uplift Credits at 

Matched Locations (RTO/ISO wide)
27

In general, publicly posted information by RTOs and ISOs and their MMUs provides

useful background on trends in uplift credits.34 There are routine data postings on uplift by 

each RTO and ISO. MMUs summarize uplift credits and charges in their annual and subannual reports. Uplift credit data from both sources, as shown in Figure 19, is usually 

reported at system-wide levels, with only PJM and NYISO’s MMU reporting at a zonal level. 

When reporting is more granular, aggregation has occurred at a regional level, whether by

zone(s), hub or intertie.

CAISO System-Wide

ISO-NE System-Wide

MISO System-Wide

NYISO 5 aggregate locations (zones A-G, F-I, J, and K and interties)

PJM Zones, hubs, and interties

CAISO System-Wide for BCR, Local Reliability Area for Exceptional Dispatch

ISO-NE System-Wide

MISO System-Wide

NYISO Zones and some unit level reporting

PJM System-Wide and some zone level reporting

MMU RTO

The lack of location specificity may limit the usefulness of publicly-posted data, 

particularly with respect to investment decisions.35 Information on the category of uplift 

credit is generally included in these postings; categories often reflect charge codes or 

identify the market in which the uplift credits were incurred (e.g., day-ahead). 

RTO and ISO and MMU uplift data postings also do not tend to include information 

about reasons for incurring uplift credits, with several exceptions.36 The CAISO posted 

exceptional dispatch report lists reasons for utilizing exceptional dispatches, including: 

intertie emergency assistance, conditions beyond the control of the CAISO, load forecast 

uncertainty, software limitations, and references to certain procedure numbers, among 

 34 This analysis looked at both internal and external MMUs when applicable.

35 The PJM MMU recently recommended revising uplift confidentiality rules in order to allow disclosure 

of complete information about the level of operating reserve charges by unit and the detailed reason for the 

level of operation reserve payment by unit. Monitoring Analytics, 2013 State of the Market Report for PJM, 

March 13, 2014 at http://www.monitoringanalytics.com/reports/PJM_State_of_the _Market/2013/2013-

som-pjm-volume2-sec4.pdf.page_123. 

36 For example, charge codes may highlight that a resource received uplift while operating to resolve a 

real-time reliability issue. However, charge codes are designed to be generic and do not contain information 

on the specific reliability issue the unit was called on to resolve.

Figure 19: Uplift Credit Location Reporting 
28

others. The MISO MMU report generally states whether the uplift was due to voltage, 

capacity or congestion needs and whether the credit was designed to reimburse energy or 

commitment costs. Finally, the PJM MMU reports 17 different categories, some of which 

include the reason a credit was paid, such as black start services. To varying degrees, all of 

the MMUs provide context on the reason for some uplift credits. 

With added transparency, market participants and other stakeholders are in the 

best position to develop solutions to address the causes giving rise to uplift. For instance, 

knowing that the vast majority of uplift in a particular import-constrained zone is related 

to the provision of reactive power could make clear to market participants that the zone is 

reactive power deficient. This could lead to proposals to address reactive power 

compensation and potentially send a price signal to enhance reactive power capability. On 

the other hand, knowing that a majority of uplift in a particular zone is related to local 

“reliability” could suggest that the model is not incorporating certain constraints or the 

operators are conservatively committing units to address generic concerns. In either case, 

this raises the possibility that energy prices do not fully reflect the marginal cost of 

production. Further, enhancing the transparency of the cost of such local reliability 

concerns may provide information necessary to appreciate the full cost of managing such 

local reliability concerns and to consider alternative solutions. This is particularly 

important when uplift costs are allocated in a manner different than the cost of alternative 

solutions. 
29

Appendix A

Figure A.1: Total Annual Uplift Credit by RTO and ISO
30

Appendix B

Figure D: Concentration of Uplift Payments by Plant in 2009

$-

$10,000,000

$20,000,000

$30,000,000

$40,000,000

$50,000,000

$60,000,000

$70,000,000

$80,000,000

- 50 100 150 200 250 300 350

Number of Plants Receiving Uplift

Uplift Credits in Dollars

CAISO

ISO-NE

MISO

PJM

NYISO

Figure E: Concentration of Uplift Payments by Plant in 2010

$-

$10,000,000

$20,000,000

$30,000,000

$40,000,000

$50,000,000

$60,000,000

$70,000,000

$80,000,000

- 50 100 150 200 250 300 350

Number of Plants Receiving Uplift

Uplift Credits in Dollars

CAISO

ISO-NE

MISO

PJM

NYISO

Figure B.1: Concentration of Uplift Credits by Plant in 2009

Figure B.2: Concentration of Uplift Credits by Plant in 2010
31

Figure F: Concentration of Uplift Payments by Plant in 2011

$-

$10,000,000

$20,000,000

$30,000,000

$40,000,000

$50,000,000

$60,000,000

$70,000,000

$80,000,000

- 50 100 150 200 250 300 350

Number of Plants Receiving Uplift

Uplift Credits in Dollars

CAISO

ISO-NE

MISO

PJM

NYISO

Figure B.4: Concentration of Uplift Credits by Plant in 2012

Note: Uplift payment totals have not been included for MISO in 2012 or 2013 and do not 

include reactive services related uplift for PJM. Totals for ISO-NE in 2012 only represent 

the third and fourth quarter. 

Figure B.3: Concentration of Uplift Credits by Plant in 2011
32

Figure B.5: Concentration of Uplift Credits by Plant in 2013

Note: Uplift payment totals have not been included for MISO in 2012 or 2013 and do not 

include reactive services related uplift for PJM. Totals for ISO-NE in 2012 only represent 

the third and fourth quarter. 
33

Appendix C

Figure C.1: NYISO and ISO-NE 2009 Uplift Credits Mapped by Region
34

Figure C.2: NYISO and ISO-NE 2010 Uplift Credits Mapped by Region

Figure C.3: NYISO and ISO-NE 2011 Uplift Credits Mapped by Region
35

Figure C.4: PJM and MISO 2009 Uplift Credits Mapped by Region

Figure C.5: PJM and MISO 2010 Uplift Credits Mapped by Region
36

Figure C.6: PJM and MISO 2011 Uplift Credits Mapped by Region

Figure C.7: CAISO 2009 Uplift Credits Mapped by Region
37

Figure C.8: CAISO 2010 Uplift Credits Mapped by Region

Figure C.9: CAISO 2011 Uplift Credits Mapped by Region
38

Appendix D

Figure D.1: Uplift Credits to Coal and Gas Burning Units in MISO
39

Figure D.2: Uplift Credits to Coal and Gas Burning Units in PJM

Figure D.3: Total Annual Uplift Credits ($ million) by Fuel Type in 2011
40

Figure D.4: Total Annual Uplift Credits ($ million) by Prime Mover in 2011
41

Appendix E

Notes: The day-ahead locational marginal prices are H.INTERNAL_HUB from Ventyx. The Pearson correlation coefficient (r) was used to 

assess correlation between monthly locational marginal price and monthly uplift credits. There were no reportable data for Q1 and Q2 2012.

Notes: The day-ahead locational marginal prices are ZONE J from Ventyx. The Pearson correlation coefficient (r) was used to assess 

correlation between monthly locational marginal price and monthly uplift credits. 
42

Notes: The day-ahead locational marginal prices are WESTERN HUB from Ventyx. The Pearson correlation coefficient (r) was used to assess 

correlation between monthly locational marginal price and monthly uplift credits. 

Notes: The day-ahead locational marginal prices are TH_SP15_GEN-APND from Ventyx. The DA/RT spread is the monthly average of the 

hourly, absolute value difference between the day-ahead and real-time locational marginal prices. The Pearson correlation coefficient (r) was 

used to assess correlation between monthly locational marginal price and monthly uplift credits.
43

Notes: The day-ahead locational marginal prices are H.INTERNAL_HUB from Ventyx. The DA/RT spread is the monthly average of the 

hourly, absolute value difference between the day-ahead and real-time locational marginal prices. The Pearson correlation coefficient (r) was 

used to assess correlation between monthly locational marginal price and monthly uplift credits. There were no reportable data for Q1 and Q2

2012.

Notes: The day-ahead locational marginal prices are CINERGY.HUB from Ventyx. The DA/RT spread is the monthly average of the hourly, 

absolute value difference between the day-ahead and real-time locational marginal prices. The Pearson correlation coefficient (r) was used to 

assess correlation between monthly locational marginal price and monthly uplift credits.