Abstract

This paper proposes and evaluates a systematic method of scheduling energy storage and conventional generation capacities in a day-ahead frequency regulation market, based on compliance to control performance standard 1 (CPS1), during each hour of the following day. The salient feature of this method is the development of two simple piecewise linear curves that represent the relationship between first, conventional generation and energy storage power capacities, and second, energy storage power and energy capacities, to satisfy CPS1 compliance in the presence of stochastic load variations. These curves are then modeled inside a mixed integer linear program to solve for resource allocations by minimizing total capacity cost. As such, the formulation avoids complex algorithms that are otherwise required to model frequency dynamics inside the optimization problem. To reduce computation time, a scenario reduction algorithm is used to obtain a small set of scenarios to represent the stochastic load. The proposed method is evaluated using comprehensive dynamic simulations of the two-area IEEE reliability test system implemented in PSS/E. The results prove that the proposed method is effective for scheduling capacities to meet CPS1 compliance with minimum cost.

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