Abstract— Texas continues to lead as the top wind power producer in the USA. The Electric Reliability Council of Texas (ERCOT) is an Independent System Operator (ISO), transmission operator and reliability coordinator in Texas. In recent years, numerous policies and incentives to promote renewable energies have been enacted. These policies were very appealing to many states including Texas because of its richness in renewable energy potential. It has been almost a year since ERCOT transitioned from the zonal to nodal market operation. This electricity market has seen significant improvements and consumers are reaping the benefits of lower spot electricity price based on a recent ERCOT report for the first 6 months since the transition took effect. This paper discusses the impact of wind power generation, based on favorable renewable energy policies coupled with the transition from zonal to nodal market, on the electricity price. The analysis performed in this paper indicates that it is very difficult to compute fairly the impact of wind energy on electricity price due to the number of uncertain variables involved and the scale of the problems.
Index Terms— Day-ahead market, Electric Reliability Council of Texas (ERCOT), electricity market, electricity price, independent system operator (ISO), wind generation, wind power.
EXAS produces and consumes more electricity compared to any other state in the USA . In order to satisfy the increasing demand for electricity, ERCOT made significantly large investments in the renewable energy sector, particularly in wind energy. Consequently, ERCOT continues to lead as the top wind production in the nation. The American Wind Energy Association reported that Texas has the highest wind installation capacity of 10,223 MW bringing the total installations in 2011 to 43,461 MW in the USA . Most importantly, the system operators are successful in sustaining the reliability as wind output achieved new heights.
H. Y. See Tao is with the Department of Electrical and Computer
Engineering at the University of Texas at El Paso, TX 79968 USA (e-mail: firstname.lastname@example.org).
A. K. Srivastava is with the School of Electrical Engineering and Computer Science, Washington State University, Pullman, WA 99163 USA (e-mail: email@example.com).
R. L. Pineda is with the Department of Industrial, Manufacturing and Systems Engineering at the University of Texas at El Paso, TX 79968 USA (e-mail: firstname.lastname@example.org).
P. Mandal is with the Department of Industrial, Manufacturing and Systems Engineering at the University of Texas at El Paso, TX 79968 USA (e-mail: email@example.com).
In October 2011, ERCOT set the highest wind generation record of 7,400 MW, representing over 70 percent of the total wind installation capacity . This new wind record places Texas well beyond the average of 30 to 40 percent of other electricity capacity that wind farms usually generate. Fig. 1 displays the installed capacity and energy produced in 2010 in Texas. Wind power produced 8 percent out of the total 12 percent of wind power installed capacity .
Fig. 1. ERCOT general overview of the installed capacity and energy produced in 2010 .
Wind power is an abundant source of renewable energy and has a tremendous impact on the environment and economy. There are numerous advantages as Texas continues to dominate as the largest wind energy production state. In terms of a competitive electricity market, there is a decrease expected in spot electricity prices with the increase in wind generation as it displaces marginal generation with a large fuel cost . The electricity customers will benefit from lower electricity price since the price reduction would be applicable to all of the spot-market purchases bought by the customer themselves in the competitive electricity market .
This paper contributes to provide an overview of impact of wind power on electricity price in the ERCOT market. This paper further reports on impact of the recent transition from
Wind Power Generation Impact on Electricity
Price in ERCOT
Hoong Yan See Tao, Student Member, IEEE, Anurag K. Srivastava, Senior Member, IEEE,
Ricardo L. Pineda, Member, IEEE, andParas Mandal, Member, IEEE
zonal to nodal market in ERCOT. In order to have a better understanding of the electricity market, a comparison of wind power generation in Texas with other states is also discussed. Section II provides a general overview of the ERCOT electricity market as it evolved throughout the years. Section III discusses the wind energy progression in the state of Texas. Section IV describes the wind power impacts on ERCOT electricity market price. Section V includes a brief discussion based on the findings of this paper, and Section VI concludes the paper with a summary of wind power generation impacts on the ERCOT electricity price.
II. OVERVIEW OF ERCOTELECTRICITY MARKET ERCOT is an independent system operator (ISO) and is a non-profit organization mainly responsible for the management of the flow of electric power to 23 million customers in the state of Texas. The 23 million Texas customers represent 75 percent of the Texas land area, and 85 percent of the state’s electric load. The scheduling of power on the electric grid that connects 40,500 miles of transmission lines and over 550 generation units are part of ERCOT’s responsibilities as the ISO for the Texas region. ERCOT is also responsible for the financial settlement management for the competitive wholesale bulk-power market .
The Texas Legislature voted and passed the Senate Bill 7 (SB7) to deregulate the retail electricity market on May 21, 1999 . The SB7 required the formation of a competitive retail electricity market to provide consumers with options to decide their own retail electric suppliers by January 1, 2002. In addition, the Texas Legislature made ERCOT responsible for planning and operations of the system reliability, maintaining the open access to the transmission system, administering the retail switching process for customer choice, and settling the wholesale market for electricity production and delivery. These responsibilities became ERCOT’s missions to serve the public interest in Texas. ERCOT’s vision is to be innovative in providing world-class, cost-effective, reliable electric grid and efficient electricity market .
The Public Utility Commission of Texas (PUCT) requested that ERCOT develop a nodal market in September 2003. The previous zonal market had several downfalls including the insufficient price transparency, resources grouped by portfolio, and indirect assignment of local congestion . On April 5, 2006, the PUCT approved the following protocols for the nodal market: improve price transparency and liquidity in the wholesale electricity day-ahead market (DAM); improve dispatch efficiencies; increase locational price transparency for resources; reduce the local congestion costs; diminish opportunities for manipulation in the wholesale electricity market; and minimize the amount of new transmission plants required to support the reliability of, and competition in, the wholesale electricity market .
The recent transition from the zonal to nodal market in ERCOT took effect on December 1, 2010, as illustrated in Fig. 2. With the new transition, ERCOT is implementing locational marginal pricing (LMP) at over 8,000 nodes with over 500 settlement price points, and DAM . The DAM used in
ERCOT normally begins at 06:00hrs and ends at 13:30hrs on the day prior to the Operating Day . Regular Operating Days are every day including weekends and ERCOT holidays. The real-time (RT) market is also utilized in ERCOT where the 15 minutes frequency of the RT dispatch is used to calculate the RT prices to obtain the LMP .
ERCOT reported the initial findings for the first 6 months since the implementation of the Texas nodal market operation. According to the rules set by the PUCT, ERCOT has made some prominent changes. The electricity market is already obtaining positive feedbacks and ERCOT is measuring the benefits of the nodal market compared to the zonal market. In terms of reducing the local congestion costs, ERCOT has conducted a back-cast analysis to compare the zonal and nodal congestion management. In order to improve the price transparency and liquidity in the wholesale electricity DAM, the day-ahead and real-time hub and load zone prices have converged in the first 6 months. To increase the locational price transparency for resources, the nodal prices per settlement point are calculated and posted compared to only the zonal marginal clearing price of energy (MCPE). To increase efficiency and transparency in dispatching of resources in real-time, those resources obtain base points not only for proper congestion management but also for providing proper price incentives . ERCOT requires more time to measure the other benefits such as reducing the amount of new transmission facilities required to support the reliability of the wholesale electricity market, and minimizing opportunities for manipulation tactics in the wholesale electricity market to maintain the competitiveness in the electricity market .
III.WIND ENERGY PROGRESSION IN TEXAS
A good understanding of the wind power progression in Texas is necessary in order to comprehend the impact of wind power generation on the electricity price in Texas. In 1999, Texas merely had 184 MW of installed wind capacity. Since then, Texas has come a long way and expanded the wind power generation capacity. The largest wind farm in the world is Roscoe Wind Farm in Texas with 627 wind turbines and a total installed capacity of 781.5 MW .
Up until 2005, California had been the leader in wind power Fig. 2. Transition from the zonal to nodal market in ERCOT .
installation capacity in the U.S. In 2006, Texas reached a significant milestone by surpassing California in wind installation capacity by a difference of 360 MW. As time progresses, Texas continues to maintain its lead as the top wind producer in the nation followed by Iowa and California . Iowa exceeded California’s wind power installation capacity in 2008. Fig. 3 displays the enormous growth of wind power capacity from the last decade amongst the top three states in the U.S. The current locations of wind power generating plants throughout Texas are shown in Fig. 4. Majority of these plants are located in the West Zone.
Fig. 4. Comparison of wind power installation capacity in MW in Texas, Iowa, and California. Source based on the U.S. Department of Energy .
The success of the vast growth of wind power in Texas can be attributed to the fact that wind is an abundant natural resource. There are several favorable and prominent policies that motivated wind generators to increase the installation of wind farms across Texas . The first incentive is the Renewable Energy Credits (RECs), which are also referred to as renewable energy certificates offered to wind generators that produce a certain amount of MWh of energy and used by a load. The value of the RECs ranges between $5 and $90 per REC with an average rate of $20, which is a great benefit for wind generators .
There were also a number of initiatives established by the U.S. federal government to boost the renewable energy generation across the nation. One of the federal programs that provides tax credits to renewable energy production companies is the renewable energy Production Tax Credits (PTCs) . The value of the PTC is estimated at $20 per MWh produced per year for wind generating companies . Congress extended the PTC until December 31, 2012 through the American Recovery and Reinvestment Act that was passed in February 2009 . The federal wind Investment Tax Credits (ITCs) is also a federal program that emerged from the Emergency Economic Stability Bill . The ITCs are catered towards small-scale wind farms with installation of small and micro-wind turbines up to 100 kW through 2016. The ITC is valued at $500 per half kW up to $4,000 in capacity .
In the case of Texas, ERCOT administered the Texas REC trading program for 68 resource entities and also 318 market participants in 2007 . ERCOT also issued nearly 10 million RECs to Texas renewable energy generation companies. One of the conditions imposed by ERCOT is the generation company must generate 1 MWh of energy to earn one REC . As a result of these clean air initiatives in Texas, wind power supplied 10 percent of the total generation capacity of in ERCOT in 2011.
IV. WIND POWER IMPACTS ON ERCOTELECTRICITY MARKET PRICE
As wind power growth rates averaged around 30 percent annually in the world, it is becoming the world’s most rapid growing renewable source of energy. In Texas, the wind installation capacity dramatically increased from 184 MW in 1999 to 10,223 MW in 2011 . Currently, Texas is one of the most competitive electricity markets in the world. In order to maintain ERCOT’s competitive edge in the overall electricity market, the competitive renewable energy zones (CREZs) penetration (wind power in particular) in ERCOT is necessary to provide continuous supply to meet the demands of the 23 million consumers in Texas . The four ERCOT zones are the North Zone, West Zone, South Zone, and Houston Zone. The estimated peak load and generation capacities for each zone, including the wind power generation capacities are displayed in Fig. 5 .
The plans for transmission line upgrades in Texas necessary to support the wind power expansion are shown in Fig. 6. The ERCOT West Zone benefiting from the transmission line upgrades include the West Texas and the Texas Panhandle areas. The CREZs involve approximately $4.93 billion in the
Fig. 5. Estimated peak load and generation capacities in the four ERCOT zones .
investment of transmission energy to expand its capability to transmit up to 18,456 MW of wind power from the West Zone to the other high-demand zones in Texas . Once the transmission lines are fully operational, residential customers will be required to pay around $4 per month to supplement the investment of these transmission lines.
In general, when the wind power generation is high and the loads are low, the price volatility causes low electricity prices, also known as negative electricity prices. If the negative prices becomes too depressed up to the point that the average prices are insufficient to cover the variable operating costs of the power generator, the resource will leave the market and affects the reliability of the resource.
Wind generation from West Texas is anti-correlated with the ERCOT demand due to the seasonality and volatility of the weather . In West Texas, the wind has a tendency to blow more in winter, spring and fall seasons, rather than in summer, which is the peak demand period in ERCOT, especially with the air-conditioning used heavily during summer time. This causes a negative electricity price impact during the off-peak periods despite the transmission constraints. The negative Fig. 6. Transmission lines upgrade plans required to accommodate the growth of wind power in the CREZs .
electricity price in ERCOT indicates that the market has no other choice but to absorb that cost transferred from the taxpayers for taking wind power during off-peak periods. A comparison of the marginal clearing price of energy and the wind generation in the ERCOT West Zone on a particular day in 2010 is shown in Fig. 7. Based on Fig. 7, it clearly proves the volatilities in both the electricity price and wind generation capacity. The continuous expansion of the wind generation capacity in Texas coupled with the upcoming transmission lines upgrades will further enhance the wind power generation and transmission process. The disparaging time for wind power generation that contributes to the negative electricity prices during the early morning from 1:00a.m. to 5:30a.m. occurs not only in the West Zone but throughout the other ERCOT zones, as displayed in Fig. 8 .
Fig. 7. Marginal clearing price of energy (MCPE) and wind generation on March 5, 2010 in the ERCOT West Zone .
Fig. 8. Negative price in the ERCOT West Zone balancing market prices on April 22, 2009 .
Since the changes took effect on December 1, 2010 from the zonal to nodal market, the average energy price was observed and recorded from the last month of the Texas zonal market in comparison with the first month of the Texas nodal market operation as shown in Fig. 9, where the average nodal market price (DAM and RT) were lower than the average zonal market price.
Fig. 9. Average energy price comparison between the zonal and nodal market in ERCOT .
The transition from the zonal to nodal market operations in ERCOT is expected to show a remarkable difference in terms of estimated cost savings with the nodal market. In an extensive study conducted by ERCOT in 2008, the load charge based on the zonal pricing was $86,438,077 per hour but using the nodal pricing, the load charge will be drastically reduced to only $6,523,751 per hour In the same analysis, the generation revenue was estimated at $77,732,096 per hour for the zonal pricing but the nodal pricing will be lower at $6,237,579 per hour The congestion rent comparison was also evaluated as the zonal pricing was approximately $8,705,982 per hour, compared to only $286,172 per hour using the nodal pricing method . In summary, this analysis indicated that the efficiencies of the nodal market (had it been in place) could have minimized the annual costs for customers by $90 million to $180 million, assuming 5-10 percent of customers in the South Zone and Houston Zone were exposed to balancing energy prices .
Wind power will continue to rise in the renewable energy sector based on the positive impact on the electricity price and its ability to supply to the growing demand of the electricity market. Therefore, Texas is expected to maintain the lead in renewable energy in terms of wind power generation and continues to establish more wind farms to take advantage of the abundance of wind energy in the U.S. Even though negative electricity prices may seem abnormal in terms of regular commodity markets, the access of electricity supply without incurring an additional cost signifies that negative prices are conceivable.
In 2008, negative electricity prices happened for 116 intervals, 130 intervals in 2009, but not once in 2010 . These observed variability in negative price time period may be temporary. The negative electricity prices in ERCOT might continue to happen in the near future as Texas continues to grow in wind power generation, increase its transmission capability and operate under new rules and regulation of enhanced wind energy penetration. The volatility and uncertainty of wind power is a challenge that might affect the
electricity price. Will wind uncertainty cause higher operational cost due to the increase in reserve margin? Even though Texas is rich in its wind energy potential, the generation, transmission, and distribution operational costs caused by wind power penetration are substantially high. As the transmission capability becomes more efficient from the West Zone to central demand centers in ERCOT, the opportunity cost and the transmission price will most likely increase as well. However, the higher transmission price can be offset using the financial tools in ERCOT. In a long run, the upgrading of transmission lines is an essential investment that will benefit the growing demand in the metropolitan areas in Texas.
Since the time of transition from the zonal to nodal, the ERCOT nodal market has been operating in a stable manner. According to the early reports since the transition, ERCOT expects to perform continuous evaluations on the performance of the nodal market. In addition, the establishment of policies and incentives by the U.S. state and federal government aimed at encouraging investments in the renewable energy sector, especially in the wind energy sector, have greatly contributed to the continuous implementation of wind installation capacity in Texas, and will maintain ERCOT’s status as the leader in utilizing wind turbines to generate carbon-free electric power.
Currently, the renewable energy policies and tax credit incentives are motivating wind power generation companies to continue its efforts to further increase its wind power generation capacity. In return, customers are paying a lower electricity price. The question is whether the expiration of the tax credits will continue the wind power generation efforts and what will be the future impact on electricity price. Some of the challenges perceived are the transmission capability and the electricity market operation in Texas. It is challenging to compute increase in operation cost and hence on electricity cost caused by increase in wind installation and transmission lines upgrades. Similarly, it is very challenging to find cost of ramping up and down base units due to wind energy variability.
In the midst of the crucial transition from zonal to nodal, ERCOT continues to successfully increase its wind power generation capacity by tapping into its natural renewable energy potential. This paper found that the timely implementation of the renewable energy policies and tax credits are a huge success in terms of catalyzing the exponential growth of wind power generation in Texas. This success proves that the vast improvements in both wind generation capacity and appropriate policies can be achieved within a competitive electricity market environment such as ERCOT. Although negative prices occur when the supply is high and the demand is low, the wind power generation companies are still gaining profits from the tax credits. The key impact of wind power generation is probably lower electricity price for customers in the competitive ERCOT electricity market. Ultimately, all the market participants benefit from the positive impacts of wind power generation at least temporarily with current rules and regulation. It is very challenging to find out the impact of wind energy on electricity price due to number of operational, planning and
policy variable involvements. Texas will serve as an ideal role model for other states to follow suit as it progresses in the renewable energy sector and continues leading the nation in wind power generation capacity.
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Hoong Yan See Tao (S’07) received her B.S. degree in 2009 and M.S. degree
in 2011, both in electrical and computer engineering from the University of Texas at El Paso (UTEP), USA. She was the past President of the IEEE student chapter at UTEP in 2008-09. She was also the past President of the Society of Women Engineers (SWE) student chapter at UTEP in 2011. Currently, she is pursuing her Ph.D. degree in the department of electrical and computer engineering at UTEP and working as a Research Assistant at the Research Institute for Manufacturing and Engineering Systems (RIMES) at UTEP. Her research interests are renewable energies (solar and wind) in terms of the evolution of a smarter planet using service systems engineering.
Anurag K. Srivastava (M’05, SM’08) received the B.Tech. in Electrical
Engineering from Harcourt Butler Technological Institute, Kanpur, India (1997), the M.Tech. degree from Institute of Technology, Varanasi (1999), and the Ph.D. degree from Illinois Institute of Technology (IIT), Chicago (2005). Currently, he is an Assistant Professor with the School of Electrical Engineering and Computer Science, Washington State University, USA. His research interests include power system security, power system deregulation, power system modeling, smart grid and micro grid, and artificial intelligence application in power system.
Ricardo L. Pineda (M’05) received his Ph.D. and M.Sc. degrees from Lehigh University and a B.Sc. degree from Universidad Nacional de Colombia. He is currently the AT&T Distinguished Professor in the College of Engineering, Chair of the Industrial, Manufacturing and Systems Engineering department and the Director of the Research Institute for Manufacturing and Engineering Systems (RIMES) at the University of Texas at El Paso, USA. His research interests include service systems engineering, network centric systems, complex systems development management, renewable energy systems, energy systems security, and energy markets.
Paras Mandal (M’06) received the B.E. degree in Electrical and Electronic
engineering from Kuvempu University, India (1998); the M.E. degree from Asian Institute of Technology, Thailand (2002), and the Ph.D. degree from the University of the Ryukyus, Japan (2005). He is presently an Assistant Professor with the Department of Industrial, Manufacturing and Systems Engineering, University of Texas at El Paso, USA. His research interests include AI application to forecasting problems, power and renewable energy systems, power systems operations and markets, complex systems, smart grid, machine learning techniques in electricity markets.