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An efficient hybrid method for solving the optimal sitting and sizing problem of DG and shunt capacitor banks simultaneously based on imperialist competitive algorithm and genetic algorithm

机译:基于帝国竞争算法和遗传算法的同时解决分布式发电和并联电容器组最优坐放尺寸问题的有效混合方法

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摘要

Nowadays due to development of distribution systems and increase in electricity demand, the use of distributed generation (DG) sources and capacitors banks in parallel are increased. Determining the installation location and capacity are two significant factors affecting network loss reduction and improving network performance. This paper, proposes an efficient hybrid method based on Imperialist Competitive Algorithm (ICA) and genetic algorithm (GA) which can greatly envisaged with problems for optimal placement and sizing of DG sources and capacitor banks simultaneously. The objective function is power loss reduction, improving system voltage profile, increasing voltage stability index, load balancing and transmission and distribution relief capacity for both utilities and the customers. The proposed method is implemented on IEEE 33 bus and 69 bus radial distribution systems and the results are compared with GA/Particle swarm optimization (PSO) method. Test results show that the proposed method is more effective and has higher capability in finding optimum solutions.
机译:如今,由于配电系统的发展和电力需求的增加,并联使用分布式发电(DG)源和电容器组的情况有所增加。确定安装位置和容量是影响减少网络损耗和提高网络性能的两个重要因素。本文提出了一种基于帝国主义竞争算法(ICA)和遗传算法(GA)的有效混合方法,该方法可以极大地考虑到同时优化DG源和电容器组的位置和尺寸的问题。目标功能是降低功率损耗,改善系统电压曲线,提高电压稳定性指标,负载平衡以及公用事业和客户的输配电能力。该方法在IEEE 33总线和69总线径向分布系统上实现,并与GA /粒子群优化(PSO)方法进行了比较。测试结果表明,该方法更有效,并且具有较高的寻优能力。

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