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Optimal placement of distributed energy storage systems in distribution networks using artificial bee colony algorithm

机译:利用人工蜂群算法在配电网中优化分布式储能系统的布局

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The deployment of utility-scale energy storage systems (ESSs) can be a significant avenue for improving the performance of distribution networks. An optimally placed ESS can reduce power losses and line loading, mitigate peak network demand, improve voltage profile, and in some cases contribute to the network fault level diagnosis. This paper proposes a strategy for optimal placement of distributed ESSs in distribution networks to minimize voltage deviation, line loading, and power losses. The optimal placement of distributed ESSs is investigated in a medium voltage IEEE-33 bus distribution system, which is influenced by a high penetration of renewable (solar and wind) distributed generation, for two scenarios: (1) with a uniform ESS size and (2) with non-uniform ESS sizes. System models for the proposed implementations are developed, analyzed, and tested using DIgSILENT PowerFactory. The artificial bee colony optimization approach is employed to optimize the objective function parameters through a Python script automating simulation events in PowerFactory. The optimization results, obtained from the artificial bee colony approach, are also compared with the use of a particle swarm optimization algorithm. The simulation results suggest that the proposed ESS placement approach can successfully achieve the objectives of voltage profile improvement, line loading minimization, and power loss reduction, and thereby significantly improve distribution network performance.
机译:公用事业规模的储能系统(ESS)的部署可能是改善配电网络性能的重要途径。最佳放置的ESS可以减少功率损耗和线路负载,减轻峰值网络需求,改善电压曲线,并且在某些情况下有助于网络故障级别的诊断。本文提出了一种在分布式网络中优化放置分布式ESS的策略,以最小化电压偏差,线路负载和功率损耗。在以下两种情况下,研究了中压IEEE-33总线配电系统中分布式ESS的最佳布置,该系统受可再生能源(太阳能和风能)的高渗透率的影响(1)具有统一的ESS大小和( 2)ESS大小不一致。使用DIgSILENT PowerFactory开发,分析和测试了所建议实现的系统模型。人工蜂群优化方法用于通过Python脚本自动优化PowerFactory中的模拟事件来优化目标函数参数。从人工蜂群方法获得的优化结果也与粒子群优化算法进行了比较。仿真结果表明,所提出的ESS放置方法可以成功实现电压分布改善,线路负荷最小化和功率损耗降低的目标,从而显着提高配电网络性能。

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