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Impact of Optimum Allocation of Distributed Generations on Distribution Networks Based on Multi-Objective Different Optimization Techniques

机译:基于多目标不同优化技术的分布式发电最优分配对配电网的影响

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A number of different optimization algorithms namely, Moth Swarm Algorithm (MSA), and Particle Swarm Optimization (PSO) algorithm are presented and compared in this paper. Different optimization techniques are used to determine the optimum allocation of distributed generation (DG) in radial distribution systems during reduction of single and multi-objective function namely, (total network power losses, voltage deviation, and total operating cost). The multi objective function is formed by using the weighted sum method. In this paper, multiple-DG units have been analyzed under two load power factors (i.e., unity and optimal). The proposed algorithms have been tested on the 33-bus radial distribution network. The performance of the different optimization algorithms has been compared with other evolutionary optimization technique under different system operating conditions. The simulation results observed the impact of integrating the proper size of DG at the suitable placement based on different techniques.
机译:本文提出并比较了许多不同的优化算法,分别是蛾群算法(MSA)和粒子群优化(PSO)算法。在减少单目标功能和多目标功能(网络总功耗,电压偏差和总运行成本)的过程中,使用了不同的优化技术来确定径向分布系统中分布式发电(DG)的最佳分配。多目标函数是通过使用加权和方法形成的。在本文中,已经在两个负载功率因数(即统一和最优)下分析了多个DG装置。所提出的算法已在33总线的径向配电网络上进行了测试。在不同的系统操作条件下,已经将不同优化算法的性能与其他进化优化技术进行了比较。仿真结果观察到了基于不同技术在适当位置集成适当大小的DG的影响。

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