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An improved optimal allocation scheme of energy storage system in a distribution system based on transient stability

机译:基于瞬态稳定性的分配系统中储能系统的改进优化分配方案

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摘要

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 (MOPSO-NSGA 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.
机译:随着可再生能源发电技术的发展,能源储存系统(ESS),高效的设备用于抑制可再生能源的波动,起到在电力系统中不可或缺的一部分。两步法,提出了以最佳地分配ESS和下降控制器考虑时域ESS表演。在第一步中,排名最前EES大小的解决方案和位置是由经济分析和功率敏感性分析(PSA)测定。在第二步骤中,使用所述溶液在步骤一获得的解空间的约束,一个新的多目标粒子群优化 - 非支配排序遗传算法III(MOPSO-NSGA III)的基础上暂态稳定分析(TSA)是建议的。优化的目标是ESS资本成本和时域电压和频率的表演受到风力发电的突然变化。与ESS的传统最优分配方案相比,所提出的方法产生了经济ESS分配方案,而频率的波动是由57%切断,并通过30%在IEEE-34总线系统降低超越极限的频率的倍。

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