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Optimal distributed generation planning in active distribution networks considering integration of energy storage

机译:考虑能量存储集成的主动配电网中的最优分布式发电计划

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A two-stage optimization method is proposed for optimal distributed generation (DG) planning considering the integration of energy storage in this paper. The first stage determines the installation locations and the initial capacity of DGs using the well-known loss sensitivity factor (LSF) approach, and the second stage identifies the optimal installation capacities of DGs to maximize the investment benefits and system voltage stability and to minimize line losses. In the second stage, the multi-objective ant lion optimizer (MOALO) is first applied to obtain the Pareto-optimal solutions, and then the 'best' compromise solution is identified by calculating the priority memberships of each solution via grey relation projection (GRP) method, while finally, in order to address the uncertain outputs of DGs, energy storage devices are installed whose maximum outputs are determined with the use of chance-constrained programming. The test results on the PG & E 69-bus distribution system demonstrate that the proposed method is superior to other current state-of-the-art approaches, and that the integration of energy storage makes the DGs operate at their pre-designed rated capacities with the probability of at least 60%.
机译:针对储能系统的集成问题,提出了一种用于分布式发电(DG)规划的两阶段优化方法。第一阶段使用众所周知的损耗敏感系数(LSF)方法确定DG的安装位置和初始容量,第二阶段确定DG的最佳安装容量,以最大程度地提高投资收益和系统电压稳定性并最小化线路损失。在第二阶段,首先应用多目标蚁群优化器(MOALO)获得帕累托最优解,然后通过灰色关联投影(GRP)计算每个解决方案的优先级成员,从而确定“最佳”妥协解决方案最后,为了解决DG的不确定输出,安装了能量存储设备,其最大输出通过使用机会受限的编程来确定。在PG&E 69总线配电系统上的测试结果表明,所提出的方法优于其他当前的最新方法,并且储能的集成使DG可以在其预先设计的额定容量下运行至少有60%的可能性。

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