In this study a probabilistic optimal power flow approach is used to analyze an energy and reserve co-optimized electricity market using the Philippine Wholesale Electricity Spot Market (WESM) model. The probabilistic optimal power flow problem is solved using the Point Estimate Method which is shown to be faster and more efficient than the traditional, resource-heavy and time consuming Monte Carlo Simulation method. Simulation of test cases using various market set-ups are performed to evaluate the performance and accuracy of the Point Estimate Method as applied to the probabilistic optimal power flow problem. The resulting locational marginal prices, generator energy schedules, zonal reserve prices and generator reserve schedules are then compared with the results obtained using the Monte Carlo Simulation method. Analyses of the results show that the Point Estimate Method significantly reduces simulation time while maintaining accuracy.
Keywords-energy and reserve co-optimizatio, point estimate metho; Monte Carlo simulation; probabilistic optimal power flow
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