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Optimal Site and Size of Distributed Generation Allocation in Radial Distribution Network Using Multi-objective Optimization

机译:使用多目标优化的径向分布网络中分布式发电分配的最优现场和大小

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摘要

Distributed generation (DG) allocation in the distribution network is generally a multi-objective optimization problem. The maximum benefits of DG injection in the distribution system highly depend on the selection of an appropriate number of DGs and their capacity along with the best location. In this paper, the improved decomposition based evolutionary algorithm (I-DBEA) is used for the selection of optimal number, capacity and site of DG in order to minimize real power losses and voltage deviation, and to maximize the voltage stability index. The proposed I-DBEA technique has the ability to incorporate non-linear, nonconvex and mixed-integer variable problems and it is independent of local extrema trappings. In order to validate the effectiveness of the proposed technique, IEEE 33-bus, 69-bus, and 119-bus standard radial distribution networks are considered. Furthermore, the choice of optimal number of DGs in the distribution system is also investigated. The simulation results of the proposed method are compared with the existing methods. The comparison shows that the proposed method has the ability to get the multi-objective optimization of different conflicting objective functions with global optimal values along with the smallest size of DG.
机译:分发网络中的分布生成(DG)分配通常是多目标优化问题。 DG注入在分配系统中的最大益处高度取决于选择适当数量的DG和其容量以及最佳位置。在本文中,改进的基于分解的进化算法(I-DBEA)用于选择最佳数量,容量和DG的站点,以便最小化实际功率损耗和电压偏差,并最大化电压稳定性指数。所提出的I-DBEA技术能够纳入非线性,非凸显和混合整数的变量问题,并且它与局部极值陷阱无关。为了验证所提出的技术的有效性,考虑IEEE 33-SCAL,69总线和119总线标准径向分配网络。此外,还研究了分配系统中最佳DG的最佳数量的选择。将所提出的方法的仿真结果与现有方法进行比较。比较表明,该方法具有通过全局最优值获得不同冲突的目标函数的多目标优化,以及DG的最小尺寸。

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