SGER: The Engineering Econometrics of Market Power in Electric Power Systems

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The high average prices and high volatility of prices in many restructured markets for electricity have raised concerns about the abuse of market power by generators. At the same time, information about the true costs of generation, that was readily available under regulation, is no longer disclosed by generators. Hence, it is becoming impractical to use a comparison of actual prices with competitive prices as the basis for identifying either the potential for or the use of market power. This proposal is about developing a new index or metric capable of evaluating a generator's potential for market power that doesn't rely on unavailable information or data. Unlike other indices in use by economists, the new index carries with it engineering information about the interconnecting network, its current topology, constraints and limitations. If the index is as innovative as it appears to be, it should also be relevant to identifying transmission bottlenecks of National interest and be able to assist in identifying ways to relieve them.With the restructuring of the electric power business from regulation to markets, ways to monitor and evaluate the performance are essential. The new FERC NOPR on Standard Market Design calls for ideas on market monitoring as well as market mitigation procedures. Virtually all of the metrics in the literature ignore the effects of market operation on the engineering, both planning and operations. The new metric suggested here is innovative in concept and, if the work is successful, it will provide the electric power industry with a new way to evaluate performance and thus, will have a substantial impact on the oversight of future electric power systems. Yet, the work is high risk because, while the index looks attractive, the computational tools and the data needed to compute it in real time are may impose intolerable limits. At present engineering information is not a part of electric power market evaluations, a major oversight at best. Successfully incorporating this information into a sensitivity-based measure will have thebroader impact of enhancing the understanding of the importance of this type of information by economists and engineers alike. The results of this work will be presented at various interdisciplinary conferences. The information will also be integrated into the course ECE551/AEM655 Power Systems Engineering and Economics, a course co-taught by the PI, an engineer, and Professor Timothy Mount, an economist.