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The California energy crisis in 2000-2001 showed what could happen to an electricity market if it did not go through a comprehensive and rigorous testing before its implementation. Due to the complexity of the market structure, strategic interaction between the participants, and the underlying physics, it is difficult to fully evaluate the implications of potential changes to market rules. This paper presents a flexible and integrative method to assess market designs through agent-based modeling. Realistic simulation scenarios are constructed for evaluation of the proposed PJM-like market power mitigation rules of the California electricity market. Simulation results show that in the absence of market power mitigation, generation company (GENCO) agents facilitated by Q-learning are able to exploit the market flaws and make significantly higher profits relative to the competitive benchmark. The incorporation of PJM-like local market power mitigation rules is shown to be effective in suppressing the exercise of market power. [ABSTRACT FROM AUTHOR]

Wind power production is variable, but also has diurnal and seasonal patterns. These patterns differ between sites, potentially making electric power from some wind sites more valuable for meeting customer loads or selling in wholesale power markets. This paper investigates whether the timing of wind significantly affects the value of electricity from sites in California and the Northwestern United States. We use both measured and modeled wind data and estimate the time-varying value of wind power with both financial and load-based metrics. We find that the potential difference in wholesale market value between better-correlated and poorly correlated wind sites is modest, on the order of 5%-10%. A load-based metric, power production during the top 10% of peak load hours, varies more strongly between sites, suggesting that the capacity value of different wind projects could vary by as much as 50% based on the timing of wind alone. [ABSTRACT FROM AUTHOR]