Technical Report

NREL/TP-550-45071

February 2009

Using Economics to Determine 

the Efficient Curtailment of Wind 

Energy

Erik Ela
National Renewable Energy Laboratory

1617 Cole Boulevard, Golden, Colorado 80401-3393

303-275-3000 • www.nrel.gov

NREL is a national laboratory of the U.S. Department of Energy

Office of Energy Efficiency and Renewable Energy

Operated by the Alliance for Sustainable Energy, LLC

Contract No. DE-AC36-08-GO28308

Technical Report

NREL/TP-550-45071

February 2009

Using Economics to Determine 

the Efficient Curtailment of Wind 

Energy

Erik Ela

Prepared under Task No. WER9.5501
NOTICE

This report was prepared as an account of work sponsored by an agency of the United States government. 

Neither the United States government nor any agency thereof, nor any of their employees, makes any 

warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or 

usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not 

infringe privately owned rights. Reference herein to any specific commercial product, process, or service by 

trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, 

recommendation, or favoring by the United States government or any agency thereof. The views and 

opinions of authors expressed herein do not necessarily state or reflect those of the United States 

government or any agency thereof.

Available electronically at http://www.osti.gov/bridge

Available for a processing fee to U.S. Department of Energy

and its contractors, in paper, from:

U.S. Department of Energy

Office of Scientific and Technical Information

P.O. Box 62

Oak Ridge, TN 37831-0062

phone: 865.576.8401

fax: 865.576.5728

email: mailto:reports@adonis.osti.gov

Available for sale to the public, in paper, from:

U.S. Department of Commerce

National Technical Information Service

5285 Port Royal Road

Springfield, VA 22161

phone: 800.553.6847

fax: 703.605.6900

email: orders@ntis.fedworld.gov

online ordering: http://www.ntis.gov/ordering.htm

Printed on paper containing at least 50% wastepaper, including 20% postconsumer waste
1 

Using Economics to Determine the Efficient Curtailment 

of Wind Energy

Abstract

This paper discusses the potential societal benefits to the energy market by allowing the 

dispatch of wind generation in times when it may enhance reliability and be economically 

advantageous to do so. Because wind is so new to the power system and many system 

operators consider the resource a resource difficult to schedule, most markets force wind 

to offer its energy as a price taker. That is, regardless of what the price is, wind will 

supply all the energy it can and will settle on whatever price the market dictates. Wind is 

a variable resource and more effort is continuing in the industry on being able to forecast 

the output of these resources to be used in market and system operations. 

Many markets, especially those in the United States, are evolving into ones that settle on 

bus-bar or nodal pricing. That is, for every generator bus on the transmission network, 

there is a separate market price (locational marginal price or LMP) usually consisting of 

energy cost, transmission loss cost, and transmission congestion cost components. Lastly, 

because wind generation has been evolving at such a rapid rate – much faster than that of 

transmission infrastructure – issues with transmission congestion can cause some or all of 

the power injected from a wind plant bus to be valueless to the market. This leads to

negative locational prices and wind suppliers who pay for every MWh of energy that is 

produced rather than receive payment for that energy. This paper discusses these issues 

and possible solutions for wind and use of economic dispatch based on energy prices. 

Background

Wind power in the United States and around the world is experiencing a very rapid 

growth period. Wind power as free fuel and as emissions-free output is a very attractive 

alternative to volatile fossil fuel prices in a warming global environment. However, there 

are certain issues with wind that must be considered when interconnecting more and 

more of it onto the power system. The two main issues are its variability and 

unpredictability. The variability of wind is described by the nature of its fuel source, the 

wind. The speed of wind is constantly changing throughout different regions, different 

local areas, different times of day, and different seasons. This changing wind speed 

causes variation in the power output or power potential of a wind turbine that effectively

causes variation of the entire wind plant. The unpredictability describes the inability to 

accurately predict the output or potential of a wind plant, which raises the possibility of 

discrepancies in the generation-load balance that must be maintained. A combination of 

these issues has led power system control-area operators to treat wind most closely to that 

of fixed load because it has no elasticity with price and must accept the market price of 

energy regardless of what it may be. Since wind does have approximately zero variable 

cost, this is usually not considered a large issue to wind plant owners and has brought 

little attention since wind first started participating in the electricity market.
2 

A second issue of wind power integration is that of transmission service. Wind power is 

usually located in wind-rich areas, and usually not in close proximity to load centers or 

existing transmission facilities. The average construction of transmission facilities takes 

several years more than the average construction and completion of a wind plant project. 

This means that transmission may not be available by the time the wind project is 

operational and either the wind project is delayed or alternative transmission with much 

less available capacity must be used. Also, since wind power is seldom operating at its 

full operating capacity, when transmission is built for the additional power needed from 

wind, it may be more economic to build transmission capacity that is lower than the total 

nameplate capacity of the plant. Since the wind does, on occasion, operate at or near its 

operating capacity, depending on what other resources are operating and sharing any 

available transmission capacity, it is not infrequent for these transmission lines to be 

loaded at or exceeding their full capacity. If exceeded, this means that something needs to 

be curtailed and other units redispatched to relieve the congestion. Most often, it is 

beneficial from a market standpoint to curtail or dispatch down the fossil generation since 

it is the most costly resource. However, with more and more wind power being added to 

the system, it may be necessary for other options. 

Negative Market Prices

In certain transmission congestion circumstances, it is possible that power injected at a 

bus is doing more harm than good to the system. This can be explained in more detail by 

the following; the locational marginal price (LMP) is usually defined as the marginal cost

to serve one more megawatt (MW) of load at a certain location. When the generator at a 

specific location is causing economic harm to the entire system, adding one more MW of 

load may have somewhat counterintuitive effects. In other words, although usually 

adding an additional MW of load would typically increase costs because extra power 

from a generator is needed, analysis of the system may show that increasing the load (or 

decreasing the generation) will result in a total savings to the system based on the 

dispatch of all resources. Now let’s examine an example of two fossil-fuel generators on 

a 3-bus system where one bus has a load obligation. 

Figure 1 – A 3-bus, 3-line power network.

2

3

L3: 150 MW

X12 = X13 = X23 

G1: 250 MW

10 $/MWh

G3: 100 MW 

50 $/MWh 

1
3 

Figure 1 is a 3-bus, 3-line power network with generators at busses 1 and 3, a load at bus 

3, and three equal line impedances. Looking at the generation cost and capacity numbers 

on this 3 bus system without line loading limits, it is obvious that Generator 1 (G1) would 

supply all 150 MW of load in this instance and Generator 3 (G3) would not be needed. 

Now, look at the same example with a transmission limit of 33 MW on the 2-3 branch.

Figure 2 – A 3-bus, 3-line power network with transmission limit. 

In Figure 2, if G1 provided the entire load, then the transmission limit would be 

exceeded. The system would need to be redispatched in order to provide the lowest cost 

to the system while still obeying all constraints. The resulting generator output and 

branch line loadings are shown below:

G1: 100 MW 

G3: 50 MW 

1-2 branch: 33 MW

2-3 branch: 33 MW

1-3 branch: 67 MW

Now let’s look at the resulting LMPs from this scenario. A good way to estimate an LMP 

is to add one MW of load to the particular bus in question and calculate the incremental 

costs to serve this one MW added to the total load. By adding one MW of load to bus 1, 

this can easily be supplied by G1 since this does not change any power injections on the

transmission network. By adding one MW of load to bus 3, this power must be supplied 

by G3 since the transmission system is congested and no more power is available from 

G1. If one more MW of load is added at bus 2, this changes the system a bit. Since the 

transmission line that is congested is on the 2-3 branch, G1 can actually supply the load 

at bus 2 and still not violate the transmission limit. In fact, since power will be distributed 

in both directions around the loop to get to bus 2, it actually will produce counter-flow 

and relieve some of the congestion on the 2-3 branch. This allows G1 to supply an 

additional MW of power on top of what it is supplying to the load at bus 2 and that can 

now supply the load at bus 3. Now, one less MW is needed from G3. Table 1 (next page) 

shows the 3 results of this approximation and the resultant LMPs. 

2

3

G1: 250 MW

10 $/MWh 

G3: 100 MW 

50 $/MWh 

1

33 MW limit

L3: 150 MW

X12 = X13 = X23 
4 

Table 1 – Approximation results and the resulting LMPs.

Gen 1 

MW

Gen 1 

Cost

Gen 3 

MW

Gen 3 

Cost

Total How much 

more?

Base Case 100 * $10/ 

MWh

+ 50 * $50/ 

MWh

= $3500

Add 1 

MW to 

Bus 1

101 * $10/ 

MWh

+ 50 * $50/ 

MWh

= $3510 $10

Add 1 

MW to 

Bus 3

100 * $10/ 

MWh

+ 51 * $50/ 

MWh

= $3550 $50

Add 1 

MW to 

Bus 2

102 * $10/ 

MWh

+ 49 * $50/ 

MWh

= $3470 $-30

The “How much more?” column shows the LMPs. Note that increasing the load at bus 2 

will actually lessen the total production costs, thus, giving the negative LMP. 

Now let’s examine the same example, increase the transmission line limit for branch 2-3 

to 100 MW and the load at bus 3 to 250 MW. We add a wind plant at bus 2 currently 

operating or predicted to operate at 100 MW. In this example, we assume the market 

requires the wind generator to bid in the market as a price taker.

Assuming the wind generator’s cost is $0/MWh, this produces an identical result to the 

prior example (see Table 2 below). 

Table 2 – Approximation results with addition of wind generator and the resulting 

LMPs.

Wind

Gen MW

Gen 1 

MW

Gen 1 

Cost

Gen 3 

MW

Gen 3 

Cost

Total How much 

more?

Base 

Case

100 100 * $10/ 

MWh

+ 50 * $50/ 

MWh

= $3500

Add 1 

MW to 

Bus 1

100 101 * $10/ 

MWh 

+ 50 * $50/ 

MWh 

= $3510 $10

Add 1 

MW to 

Bus 3

100 100 * $10/ 

MWh 

+ 51 * $50/ 

MWh 

= $3550 $50

Add 1 

MW to 

Bus 2

100 102 * $10/ 

MWh 

+ 49 * $50/ 

MWh 

= $3470 $-30

In many of the U.S. markets, generators and loads settle on what is called a twosettlement system. That is, they will settle on purely financial terms what is usually 

referred to as a day-ahead market, and will make up any differences that occur from the 

original prediction in what is referred to as a real-time market or balancing market. These 
5 

types of negative prices are usually more prevalent in real-time markets. The reason for 

this is that there can be more unanticipated results that happen in real-time and not 

enough of a time horizon to make the most economic adjustments. Real-time markets 

usually can only dispatch units that have already been committed and because of 

generator ramping rates there is usually much less power that can be dispatched in this 

market. This is sometimes more harmful to wind generators than other generators 

because of the variable and uncertain nature of wind. 

Uncertainties involved in bidding in the market for wind generation can make it

economically harmful to bid in the day-ahead market, so many choose not to and will 

settle solely on real-time prices. For example, if they sell in the day-ahead market and do 

not meet their day-ahead schedule, they must buy back the power in the real-time market. 

Wind generators may try to sell a small amount of power in the day-ahead market and 

similarly, will sell the rest of what they produce in the real-time market at real-time 

prices. Therefore, whether they are selling into the day-ahead market or not, they are 

much more affected by real-time prices due to the uncertainty characteristics. 

Lastly, because they are considered as price takers, they are constrained from the market 

perspective in both upward and downward directions. This results in one less unit that 

can be used in redispatch efforts when a constraint is observed. 

Negative Market Prices in the Real World

These pricing issues are becoming more of an actual problem than just a theoretical 

problem, given the large addition of wind power that has occurred in the past few years. 

In the Electric Reliability Council of Texas (ERCOT), for example, the western zone, 

which has the majority of the wind in the region, had negative prices for more than 20% 

of all hours in the month of April 2008. The average negative price was between $40 and 

$30 per MWh. This occurred even without ERCOT having implemented a nodal market.1

This means that it is possible that once ERCOT moves to a nodal market, certain wind 

generator buses may have more of an impact on the zonal interface transmission 

congestion than is seen today, and may have further consequences on its individual nodal 

price. It is unclear today as to what market constraints are apparent in the ERCOT market

(i.e., if the wind generators are forced to bid as price takers). It is likely due to their 

values that these prices are in fact being set by wind generators. However, the full 

response of the wind generators acting on the prices is unclear. Since generators do not 

individually bid into the market, it is unclear whether the wind power generators are

actually the ones responding to these negative prices in order to relieve congestion.

2

 

1 ERCOT currently settles on zonal prices. Zonal prices use interface limits between different regions in the 

control area. This may hide specific congested lines and specific generators that are contributing most to 

congestion.

2 In the ERCOT market, Qualified Scheduling Entities will submit a plan for a portfolio for a number of 

both generation and load to ERCOT in advance of the market close. 
6 

In other markets, where nodal pricing is available but wind generation may not be as 

substantial of a resource, there are significant occurrences of negative prices as well. In 

the NY Independent System Operator (NYISO), one wind generator bus experienced 

negative prices more than 20% of the hours in May 2008. Of these 20%, close to half are 

below the current production tax credit (PTC) value – a major revenue stream for wind 

generation. This could mean, depending on what state environmental revenues are 

available, that the wind generator lost money to generate during 10% of all intervals. The 

average price below the PTC was $-149 per MWh. To go a bit further, had all negative 

prices been eliminated in this month, the average LMP of the month would have changed 

from $39 to $66, which corresponds to an approximate revenue change of $27,000 per 

average monthly MW to over $42,000 per average monthly MW, or over a 50% increase 

in revenue. 

A related issue is the validity of wind resources selling to a market pool versus the notion 

of them having fixed bilateral contracts with load serving entities that are less impacted

from variable market prices. In the short term, market tariffs have some way of defining 

transmission charges when congestion costs are incurred. That is, even when a bilateral 

agreement for energy is stated, when the prices due to congestion or losses between the 

seller and buyer differ, the owner of the bilateral agreement has to pay the difference. 

This is usually, but not always, the load or utility that is purchasing the power from the 

wind supplier. So in this case, it may be the load that is the one that is being directly 

harmed rather than the wind. 

However, when thinking in terms of the long term, the key idea to understand is that if all 

environmental benefits were put aside and the market value of wind was considered as it 

is with any other type of generation, why would a load continue to purchase power from 

a location where it may continue to pay these large transmission usage charges? Prices 

agreed upon in a bilateral agreement should largely reflect those that are set in the market 

in the long-term. David Patton, ERCOT’s Independent Market Advisor, said something 

to this effect in his 2006 ERCOT State of the Market Report. 

“Although most power is purchased through forward contracts of varying 

duration, the spot prices emerging from the balancing energy market 

should directly affect forward contract prices.” 3

Further Issues

The financial complications that are caused by lack of transmission and dispatch 

capability are sufficient enough an issue for independent system operators (ISOs) and 

regional transmission operators (RTOs) (the entities that operate regional grids and 

wholesale energy markets) to look at mitigation techniques to prevent this situation from 

 

3 “ERCOT 2006 State of the Market Report”, Potomac Economics, August 2007. 

http://www.potomaceconomics.com/uploads/ercot_reports/2006%20ERCOT%20SOM%20REPORT_Final

.pdf
7 

occurring. There are also additional issues that can occur to more than just the settling 

parties, including those of reliability. With a large negative price, where a wind generator 

is selling into the market and having to pay more amounts of money than can be gained 

from any other type of incentive, there are usually a few possible scenarios. The wind 

generator can continue to generate and lose money from the negative-valued production 

of energy. Or the wind generator may decide that it cannot afford to continue to inject 

energy and turn the entire plant off. In the example similar to that described in Table 2, 

there are usually no reliability issues with the wind generator continuing to run. The 

transmission limit is not exceeded because the system operator has scheduled the system 

around the wind generator’s constrained output. The negative LMP value comes from the 

reduction in output of cheap generation somewhere on the system, and to account for that 

loss of generation, the addition of very expensive units elsewhere. 

Because of the small impact, or generation shift factor, that a generator may have on the 

congested line, it may need to adjust a large amount of the generator’s power to reduce 1 

MW of congestion on the line. This multiplies the price impact on the line. However, the 

line limit is not exceeded, and the generation and load on the system is balanced. If the 

plant was a 200 to 300-MW plant, and it took itself offline to avoid negative prices, the 

system has just lost 200 to 300 MW, causing a potentially significant reliability issue. 

Possibly, the wind generator need only reduce output by 10 MW to relieve the congested 

line. In this case, a partial reduction in output of wind power would seem to be the 

appropriate response.

Another possible issue is the efficiency of the market that the system operator is running. 

If prices were set based on the wind generator staying steady, and its power is manually 

reduced, this diverges prices from what the market actually did. To have the most 

efficient market, the economic dispatch program should best predict the outputs of 

generation for the best reflection on the marginal cost or price of energy. LMPs or energy 

prices in general are almost always related to the economic dispatch by the bids that the 

generators provide. If the LMP is below the bid cost of the generator, the generator 

should be ramped down or turned off. If the LMP is above the generator’s bid cost, the 

generator should either be ramped up or operated at its upper limit. Because most markets 

require wind generators to bid as pure price takers, their artificial bid cost is essentially

negative infinite.4

Resolution

Since bid costs are supposed to reflect the actual variable cost of a 

resource, this is obviously not an accurate reflection. 

A possible resolution to some of the inefficiencies described in this paper is to allow 

wind generators to provide economic offers the same way that other generators do. The 

wind generator should use an energy forecast as its upper potential or capacity and 0 MW 

as its minimum operating level. The wind generator then should provide the market 

operator with a bid cost that shows their economic willingness to generate. An example 

 

4 Some markets may have penalty factors in place that will allow curtailment of self-schedules or “price 

takers” below some very negative number.
8 

might be 0 dollars, however, because of certain incentives that wind generators get from 

national or state governments for generating (e.g., production tax credit) they may choose 

to provide a negative value as their bid cost. The purpose would be that the wind 

generator should never be scheduled if the price is below the bid cost that is given. If two 

wind generators are behind a constrained transmission line, one with a bid of $0 and the 

other with a bid of $-15, the one with the $0 bid would most likely be backed down 

before the one with the $-15 bid. The key difference of this idea is that unlike other 

generating resources, the wind’s total potential or upper limit will be changing typically 

every market interval. If this were to be done the market solution – economic dispatch or 

unit commitment program – will determine when it is appropriate to curtail the wind and 

at exactly which level it will curtail it to. We will now use the example shown before and 

give the wind generator a bid cost of $0 and allow the market to dispatch the wind as a 

normal resource. Table 3 shows the outputs of all generators in the case without 

economic curtailment and the case with economic curtailment. Tables 4 and 5 show the 

resulting price information without curtailment and with curtailment, respectively.

Table 3 – Generation Output With and Without Using Economic Wind Curtailment

Without economic 

curtailment

With economic 

curtailment

Generator 1 100 MW 200 MW

Generator 2 (wind) 100 MW 50 MW

Generator 3 50 MW 0 MW

Tables of Production Costs and LMPs

Table 4 – Costs and Prices without Economic Curtailment

Wind

Gen

MW

Gen 1 

MW

Gen 1 

Cost

Gen 3 

MW

Gen 3 

Cost

Total How 

much 

more?

Base 

Case

100 100 * $10/ 

MWh

+ 50 * $50/ 

MWh

= $3500

Add 1 

MW to 

Bus 1

100 101 * $10/ 

MWh 

+ 50 * $50/ 

MWh 

= $3510 $10

Add 1 

MW to 

Bus 3

100 100 * $10/ 

MWh 

+ 51 * $50/ 

MWh 

= $3550 $50

Add 1 

MW to 

Bus 2

100 102 * $10/ 

MWh 

+ 49 * $50/ 

MWh 

= $3470 $-30
9 

Table 5 – Costs and Prices with Economic Curtailment

Wind

Gen

MW

Gen 1 

MW

Gen 1 

Cost

Gen 3 

MW

Gen 3 

Cost

Total How 

much 

more?

Base 

Case

50 200 * $10/ 

MWh

+ 0 * $50/ 

MWh

= $2000

Add 1 

MW to 

Bus 1

50 201 * $10/ 

MWh 

+ 0 * $50/ 

MWh 

= $2010 $10

Add 1 

MW to 

Bus 3

49 202 * $10/ 

MWh 

+ 0 * $50/ 

MWh 

= $2020 $20

Add 1 

MW to 

Bus 2

51 200 * $10/ 

MWh 

+ 0 * $50/ 

MWh 

= $2000 $0

Table 5 shows that the system came up with a much more cost effective solution. Three 

things happened in this new solution. The total production costs were substantially 

lowered, the price that the load at bus 3 pays has been substantially lowered, and the price 

that the wind generator gets paid is no longer financially harmful. Also, there were no 

negative impacts to any party. G3 is no longer generating, but in the original solution 

(Table 4), it was not making any profit, so the profit margin has not changed. 

Because of the transmission distribution effects, it is more economic to curtail the wind 

generator than to curtail G1. If the price were still largely negative, then the wind 

generator should have been scheduled all the way to zero. Theoretically, the only time 

any generator should be affected by negative pricing is due to a physical constraint of the 

generator. This may include minimum operating limits, minimum run times, ramp rates, 

etc. Most modern wind plants do not have these types of physical constraints and, 

therefore, should not be blocked by an artificial market constraint. In the situation shown 

above (Table 5), if the wind generator follows the directions given, the system is 

balanced, the line is not overloaded, and the operators did not have to make any calls or 

decisions. Costs are reduced and prices match what actually occurred.

A list of further benefits from this approach is detailed below:

• Better efficiency of the market; least-cost energy solution to consumers 

– Convergence of day-ahead to real-time pricing

– Convergence of physical results to pricing results

• Less strain on operators to make curtail calls (i.e., scheduling software does it for 

them)

• Less financial harm to wind generators

• Possibly less financial harm to other generators who have true physical 

constraints 

• Reliability benefits; balancing area-directed curtailment vs. self-directed 

curtailment
10 

• Reliability benefits; better management of otherwise unmanageable congestion

• Wind competition: In places where the entire load can be served by wind, this can

determine what plants to curtail

• Same methodology described in this paper with transmission congestion can 

essentially be used for large ramp events and minimum-load periods

Ongoing Issues

The first and most important issue in making these improvements is ensuring that when 

wind generators are getting signals to limit their output, they are following these 

directions. These market mechanisms only incentivize solving reliability problems, and 

without the wind plants following directions, there is no real benefit. It should be up to 

the ISO to determine what best ways are used in incentivizing behavior of other resources 

to follow directions, and how those may apply to wind in this situation. In some 

instances, this may result in the need for financial penalties to wind generators not 

following directions during these conditions. 

With more and more wind power entering the system, and transmission capacity lagging 

behind, this may cause an issue on the amount of wind capacity being built compared to 

RPS goals issued by states. Another issue in need of more research is how this impacts 

wind generation forecasts being produced for the plants. Statistically based forecasts will 

usually use the correlation of wind speed along with wind power to determine applicable 

power curves of the plant. The more often a wind generator is producing at less than 

potential, the more this relationship becomes skewed. Lastly, if it were the plan for this 

communication process to be fully automated from control center to generator, as is other 

generation, there may need to be additional infrastructure built to feed curtailment signals 

to the plant. If the plant ignores any sort of base point coming from a system operator 

99% of the time, how will it know when it needs to follow the base point during the 1% 

of the time this situation occurs? 

It is also important to note that different ISOs will have different market structures, 

bidding structures, and settlement structures, so that this procedure would have to be 

assessed in specific ways for specific regions. Some of the key differences that may 

affect the application of this operation are listed below:

– Ex Ante vs. Ex Post pricing (i.e., prices set based on schedules or on 

actual outcomes) 

– Zonal vs. nodal pricing 

– Individual supplier offers vs. scheduling entities who offer a portfolio of 

suppliers 

– Systems with more aggregation of wind plants vs. concentrated layout 

– Negative price allowance

– Two settlement vs. single settlement

– Market dominated by bilateral power purchase agreements vs. selling 

directly to market pool
11 

– Vertically integrated utilities in footprint vs. fully divested utilities 

– Differences in transmission capacity, and resource and flexibility mix may 

present different needs

– Regulated utilities may also be able to use something to this effect in their 

economic dispatch programs over their footprint 

Conclusion

The amount of wind power being added into many power systems is increasing 

dramatically. This increase requires a similar increase in the amount of transmission 

capacity to be able to supply many loads with low-cost energy. When transmission is not 

yet built and constraints on the transmission network are apparent, fossil generation 

should be dispatched down in order to save costs and fuel. However, when economically 

advantageous to do so, wind power should be allowed to be on dispatch to relieve 

transmission congestion constraints. Constraints set forth in the market should be based 

on physical constraints alone. Allowing wind generation to provide economic offers in 

the electricity market promotes increased market efficiency as well as enhanced 

reliability and large savings to all market participants. 

References

The Electric Reliability Council of Texas (ERCOT) at: http://www.ercot.com/

The New York Independent System Operator (NYISO) at: 

http://www.nyiso.com/public/index.jsp

Many of the solutions in this paper were verified using GAMS and solved using the 

CPLEX solver. 

GAMS Development Corporation, “GAMS: The Solver Manuals,” Washington, DC, 

2005. 
F1147-E(10/2008)

REPORT DOCUMENTATION PAGE Form Approved

OMB No. 0704-0188

The public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, 

gathering and maintaining the data needed, and completing and reviewing the collection of information. Send comments regarding this burden estimate or any other aspect of this 

collection of information, including suggestions for reducing the burden, to Department of Defense, Executive Services and Communications Directorate (0704-0188). Respondents 

should be aware that notwithstanding any other provision of law, no person shall be subject to any penalty for failing to comply with a collection of information if it does not display a 

currently valid OMB control number.

PLEASE DO NOT RETURN YOUR FORM TO THE ABOVE ORGANIZATION.

1. REPORT DATE (DD-MM-YYYY)

February 2009

2. REPORT TYPE

Technical Report

3. DATES COVERED (From - To)

4. TITLE AND SUBTITLE

Using Economics to Determine the Efficient Curtailment of Wind Energy

5a. CONTRACT NUMBER

DE-AC36-08-GO28308

5b. GRANT NUMBER

5c. PROGRAM ELEMENT NUMBER

6. AUTHOR(S)

Erik Ela

5d. PROJECT NUMBER

NREL/TP-550-45071

5e. TASK NUMBER

WER95501

5f. WORK UNIT NUMBER

7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES)

National Renewable Energy Laboratory

1617 Cole Blvd.

Golden, CO 80401-3393

8. PERFORMING ORGANIZATION

REPORT NUMBER

NREL/TP-550-45071

9. SPONSORING/MONITORING AGENCY NAME(S) AND ADDRESS(ES) 10. SPONSOR/MONITOR'S ACRONYM(S)

NREL

11. SPONSORING/MONITORING

AGENCY REPORT NUMBER

12. DISTRIBUTION AVAILABILITY STATEMENT

National Technical Information Service

U.S. Department of Commerce

5285 Port Royal Road

Springfield, VA 22161

13. SUPPLEMENTARY NOTES

14. ABSTRACT (Maximum 200 Words)

This paper discusses the potential societal benefits to the energy market by allowing the dispatch of wind generation 

in times when it may enhance reliability and be economically advantageous to do so.

15. SUBJECT TERMS

wind power; wind energy; curtailment; economics; grid; integration; system integration; utilities; system operation 

16. SECURITY 

CLASSIFICATION OF:

17. LIMITATION OF ABSTRACT

UL

18. NUMBER 

OF PAGES

19a. NAME OF RESPONSIBLE PERSON

a. REPORT

Unclassified

b. ABSTRACT

Unclassified

c. THIS PAGE

Unclassified 19b. TELEPHONE NUMBER (Include area code)

Standard Form 298 (Rev. 8/98)

Prescribed by ANSI Std. Z39.18