Review of the WECC EDT phase 2 EIM benefits analysis and results report.

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A region-wide Energy Imbalance Market (EIM) was recently proposed by the Western Electricity Coordinating Council (WECC). In order for the Western Area Power Administration (Western) to make more informed decisions regarding its involvement in the EIM, Western asked Argonne National Laboratory (Argonne) to review the EIM benefits study (the October 2011 revision) performed by Energy and Environmental Economics, Inc. (E3). Key components of the E3 analysis made use of results from a study conducted by the National Renewable Energy Laboratory (NREL); therefore, we also reviewed the NREL work. This report examines E3 and NREL methods and models used in the EIM study. Estimating EIM benefits is very challenging because of the complex nature of the Western Interconnection (WI), the variability and uncertainty of renewable energy resources, and the complex decisions and potentially strategic bidding of market participants. Furthermore, methodologies used for some of the more challenging aspects of the EIM have not yet matured. This review is complimentary of several components of the EIM study. Analysts and modelers clearly took great care when conducting detailed simulations of the WI using well-established industry tools under stringent time and budget constraints. However, it is our opinion that the following aspects of themore » study and the interpretation of model results could be improved upon in future analyses. The hurdle rate methodology used to estimate current market inefficiencies does not directly model the underlying causes of sub-optimal dispatch and power flows. It assumes that differences between historical flows and modeled flows can be attributed solely to market inefficiencies. However, flow differences between model results and historical data can be attributed to numerous simplifying assumptions used in the model and in the input data. We suggest that alternative approaches be explored in order to better estimate the benefits of introducing market structures like the EIM. In addition to more efficient energy transactions in the WI, the EIM would reduce the amount of flexibility reserves needed to accommodate forecast errors associated with variable production from wind and solar energy resources. The modeling approach takes full advantage of variable resource diversity over the entire market footprint, but the projected reduction in flexibility reserves may be overly optimistic. While some reduction would undoubtedly occur, the EIM is only an energy market and would therefore not realize the same reduction in reserves as an ancillary services market. In our opinion the methodology does not adequately capture the impact of transmission constraints on the deployment of flexibility reserves. Estimates of flexibility reserves assume that forecast errors follow a normal distribution. Improved estimates could be obtained by using other probability distributions to estimate up and down reserves to capture the underlying uncertainty of these resources under specific operating conditions. Also, the use of a persistence forecast method for solar is questionable, because solar insolation follows a deterministic pattern dictated by the sun's path through the sky. We suggest a more rigorous method for forecasting solar insolation using the sun's relatively predictable daily pattern at specific locations. The EIM study considered only one scenario for hydropower resources. While this scenario is within the normal range over the WI footprint, it represents a severe drought condition in the Colorado River Basin from which Western schedules power. Given hydropower's prominent role in the WI, we recommend simulating a range of hydropower conditions since the relationship between water availability and WI dispatch costs is nonlinear. Also, the representation of specific operational constraints faced by hydropower operators in the WI needs improvements. The model used in the study cannot fully capture all of the EIM impacts and complexities of power system operations. In particular, a primary benefit of the EIM is a shorter dispatch interval; namely, 5 minutes. However, the model simulates the dispatch hourly. Therefore it cannot adequately measure the benefits of a more frequent dispatch. A tool with a finer time resolution would significantly improve simulation accuracy. When the study was conducted, the rules for the EIM were not clearly defined and it was appropriate to estimate societal benefits of the EIM assuming a perfect market without a detailed specification of the market design. However, incorporating a more complete description of market rules will allow for better estimates of EIM benefits. Furthermore, performing analyses using specific market rules can identify potential design flaws that may be difficult and expensive to correct after the market is established. Estimated cost savings from a more efficient dispatch are less than one percent of the total cost of electricity production.« less