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Distribution expansion planning considering reliability and security of energy using modified PSO (Particle Swarm Optimization) algorithm

机译:使用改进的PSO(粒子群优化)算法考虑能源可靠性和安全性的配电扩展计划

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摘要

Distribution feeders and substations need to provide additional capacity to serve the growing electrical demand of customers without compromising the reliability of the electrical networks. Also, more control devices, such as DG (Distributed Generation) units are being integrated into distribution feeders. Distribution networks were not planned to host these intermittent generation units before construction of the systems. Therefore, additional distribution facilities are needed to be planned and prepared for the future growth of the electrical demand as well as the increase of network hosting capacity by DG units. This paper presents a multiobjective optimization algorithm for the MDEP (Multi-Stage Distribution Expansion Planning) in the presence of DGs using nonlinear formulations. The objective functions of the MDEP consist of minimization of costs, END (Energy-Not-Distributed), active power losses and voltage stability index based on SCC (Short Circuit Capacity). A MPSO (modified Particle Swarm Optimization) algorithm is developed and used for this multiobjective MDEP optimization. In the proposed MPSO algorithm, a new mutation method is implemented to improve the global searching ability and restrain the premature convergence to local minima. The effectiveness of the proposed method is tested on a typical 33-bus test system and results are presented.
机译:配电馈线和变电站需要提供额外的容量,以满足客户不断增长的电力需求,同时又不损害电网的可靠性。而且,更多的控制设备,例如DG(分布式发电)单元已集成到配电馈线中。在构建系统之前,并未计划将这些间歇性发电单元托管在配电网中。因此,需要规划和准备更多的配电设施,以应对未来的电力需求增长以及DG部门增加网络托管容量的需求。本文提出了使用非线性公式表示存在DG的MDEP(多阶段分布扩展计划)的多目标优化算法。 MDEP的目标功能包括最小化成本,END(能量未分配),有功功率损耗和基于SCC(短路容量)的电压稳定性指标。开发了MPSO(改进的粒子群优化)算法,并将其用于此多目标MDEP优化。在提出的MPSO算法中,实现了一种新的变异方法,以提高全局搜索能力并抑制过早收敛到局部极小值。在典型的33总线测试系统上测试了该方法的有效性,并给出了结果。

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