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Optimal Allocation and Sizing of Capacitors by BPSO Algorithm with Consideration of Annual Load Profile: A Real Case Study

机译:BPSO算法考虑年负荷概况的最佳分配和大小尺寸:真正的案例研究

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In the present work, a swarm search optimization-based approach as known Binary Particle Swarm Optimization (BPSO) has been developed to find the optimal capacitor placement on the Meshkinshahr distribution network. Harmonic distortion of voltage sources in network caused a double harmonic current injection, increasing network losses and incidence of resonance phenomenon. Moreover, the optimal capacitor placement problem of radial distribution system for variable load level is considered as a non-linear optimization problem with a non-differentiable objective function due to the fact that the costs of the capacitor vary in a discrete manner and the system load also varies continuously throughout the day. Therefore, BPSO is proposed to minimize harmonic distortion effects in the distribution network based on optimal capacitor placement. To check the feasibility, the proposed framework is applied on real distribution network. Numerical experiments are included to demonstrate that the proposed method can obtain better quality solution than many existing techniques as view of minimizing the power loss and improving of voltage profile.
机译:在本作工作中,已经开发出一种基于群搜索优化的方法,以找到已知的二进制粒子群优化(BPSO),以找到MeshkinShahR分配网络上的最佳电容器放置。网络中电压源的谐波失真导致双谐波电流注入,增加网络损耗和共振现象的发生率。此外,由于电容器的成本以离散方式和系统负载变化的事实,因此认为可变负载水平的径向分布系统的最佳电容器放置问题被认为是非线性优化问题。整天也不断变化。因此,提出了基于最佳电容器放置的分配网络中的谐波失真效应来最小化BPSO。要检查可行性,所提出的框架适用于实际分配网络。包括数值实验以证明所提出的方法可以比现有技术获得更好的质量解决方案,视图最小化电力损耗和改善电压分布。

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