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Optimal allocation of energy storage systems considering wind power uncertainty

机译:考虑风能不确定性的储能系统优化分配

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Energy storage systems (ESSs) play a major role in power system planning and operation. As evolution of the storage technologies continues, planners will be regarded the ESSs in future power systems more than ever. Simultaneous determination of size and site of ESSs is a non-deterministic, and non-convex problem, which should take into account the uncertain nature of today's power systems. This paper, for the first time, investigates uncertain optimal allocation of ESSs considering practical constraints, including prohibited zones, and ramp rate, as well as simultaneous reduction of three different and incompatible objective functions of operation cost, voltage deviation, and air emission. Due to complexity of the problem, two multi-objective hybrid algorithms called MOGSA and MOPSO-NSGA_II were proposed. Furthermore, five-point estimation method is utilized in order to model the wind power uncertain nature. The simulation results on IEEE 30-bus test system are detailed. To increase the accuracy and ensure selection of the best solution from among the set of optimal solutions, the multi-criteria decision-making techniques (TOPSIS) are used. The simulation results clearly show the efficiency and effectiveness of the proposed method.
机译:储能系统(ESS)在电力系统规划和运行中起着重要作用。随着存储技术的不断发展,规划人员将比以往任何时候都被视为未来电力系统中的ESS。同时确定ESS的大小和位置是一个不确定性和非凸性的问题,应考虑到当今电力系统的不确定性。本文首次研究了考虑到实际约束(包括禁区和斜坡率)以及同时降低运行成本,电压偏差和空气排放的三个不同且不兼容的目标函数的实际约束条件时,不确定的ESS最佳分配。由于问题的复杂性,提出了两种称为MOGSA和MOPSO-NSGA_II的多目标混合算法。此外,利用五点估计方法来建模风能不确定性。详细介绍了在IEEE 30总线测试系统上的仿真结果。为了提高准确性并确保从最佳解决方案集合中选择最佳解决方案,使用了多准则决策技术(TOPSIS)。仿真结果清楚地表明了该方法的有效性。

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