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首页> 外文期刊>ETEP-European Transactions on Electrical Power >Optimal multiple distributed generation placement in microgrid system by improved reinitialized social structures particle swarm optimization
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Optimal multiple distributed generation placement in microgrid system by improved reinitialized social structures particle swarm optimization

机译：通过改进的重新初始化的社会结构，粒子群优化，在微电网系统中实现最佳的多分布式发电布置

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摘要

This paper proposes an improved reinitialized social structures particle swarm optimization (IRS-PSO) fornsolving optimal multiple distributed generations (DG) placement in a microgrid (MG) system. Thenmovement of each particle in IRS-PSO is pulled by an inertia term, a cognitive term (personal best),nand three social learning terms including global best, local best, and near neighbor best. The objective is tonminimize the real power loss within real and reactive power generation limits and voltage limits. Five typesnin a MG system are considered including MG with DG supplying real power only, MG with DG supplyingnreactive power only, MG with DG supplying real power and consuming reactive power, MG with DGnsupplying real power and reactive power, andMG with four different types of DG regulating the bus voltage.nFor a given number of DG units in each type, IRS-PSO can find better sizes and locations of multiple DGsnthan repetitive load flow, basic particle swarm optimization (BPSO), adaptive weight particle swarmnoptimization (APSO), and global best, local and near neighbor best particle swarmoptimization (GLN-PSO)non the 69-bus radial MG distribution system. Copyright # 2010 John Wiley & Sons, Ltd.
机译：本文提出了一种改进的重新初始化的社会结构粒子群优化算法（IRS-PSO），用于解决微电网（MG）系统中的最优多个分布式发电（DG）放置问题。然后，IRS-PSO中每个粒子的运动都被一个惯性项，一个认知项（个人最佳），以及三个社会学习项（包括全局最佳，局部最佳和近邻最佳）拉动。目的是在有功和无功发电极限和电压极限内最大程度地减少有功功率损耗。 MG系统中考虑了五种类型，包括仅带DG提供有功功率的MG，带DG仅提供无功功率的MG，带DG提供有功功率和无功功率的MG，带DGns提供有功功率和无功功率的MG，以及带四种不同类型DG的MG n对于每种类型的给定数量的DG单元，IRS-PSO可以找到多个DG更好的尺寸和位置，而不是重复负载流，基本粒子群优化（BPSO），自适应权重粒子群优化（APSO）和全局最佳，局部和近邻最佳非粒子群优化（GLN-PSO）非69总线径向MG分配系统。版权所有©2010 John Wiley＆Sons，Ltd.

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