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Optimal Sizing and Placement of Multiple Distributed Generators using Teaching Learning Based Optimization Algorithm in Radial Distributed Network

机译:径向分布式网络中基于教学学习的优化算法的分布式发电机优化选型与布置

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Distributed Generation (DG) plays significant role in improvement of radial distribution network (RDN). Optimal sizing and placement of DGs in RDN can improve the voltage profile and minimize real and reactive power losses. In this paper, the impact of placement of multiple DGs has been addressed to assess the performance of RDN. Teaching Learning Based Optimization Algorithm (TLBO) has been applied to determine both sizing and location of multiple DGs with an objective to minimize real power losses. It is shown that optimal sizing and placement of multiple DGs are better as compared to that of single DG placement. The simulations are carried out on standard 33 nodes RDN for comparative analysis.
机译:分布式发电(DG)在改善径向配电网(RDN)中起着重要作用。在RDN中优化DG的大小和放置可以改善电压曲线并最大程度地减少有功和无功损耗。在本文中,已解决了放置多个DG的影响,以评估RDN的性能。教学基于学习的优化算法(TLBO)已用于确定多个DG的大小和位置,目的是最大程度地减少实际功率损耗。结果表明,与单个DG放置相比,多个DG的最佳尺寸和放置效果更好。仿真在标准的33个节点RDN上进行以进行比较分析。

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