Abstract
Along with the development of renewable energy generation technology, energy storage system (ESS), highly effective equipment for suppressing renewable energy fluctuations, plays an indispensable part in power system. A two-step method is proposed to optimally allocate ESS and droop controller considering ESS performances in time domain. In the first step, the top ranked solutions of EES size and locations are determined by economic analysis and Power Sensitivity Analysis (PSA). In the second step, using the solutions obtained in step one as the constraint of solution space, a new Multi-objective Particle Swarm Optimization-Non-dominated Sorting Genetic Algorithm Ⅲ (MOPSONSGA Ⅲ) based on Transient Stability Analysis (TSA) is proposed. Optimization objectives are ESS capital cost and the time-domain voltage and frequency performances subject to a sudden change of wind power. Compared with traditional optimal allocation schemes of ESS, the proposed method produces a economical ESS allocation scheme, while the fluctuation of frequency is cut by 57% and the times of the frequency beyond the limit is reduced by 30% in the IEEE-34 bus system.
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