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Optimal distributed generation planning considering reliability, cost of energy and power loss

机译:考虑可靠性,能源成本和功率损耗的最佳分布式发电计划

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This paper suggests a Pareto based Multi-objective Optimization Algorithm (MOA) called Strength Pareto Evolutionary Algorithm (SPEA) for Distributed Generation (DG) planning in distribution networks. As opposed to conventional multi-objective optimization techniques that correlate different objective functions by utilizing of weighting coefficients and create one single objective function, in SPEA, each objective function is optimized separately. Since the objective functions are in conflict with each other, the SPEA produces a set of optimum solutions instead of one single optimum one. Three different objective functions are considered in this study: (1) minimization of power generation cost (2) minimization of active power loss (3) maximization of reliability level. The goal is to optimize each objective function. The site and size of DG units are assumed as design variables. The results are discussed and compared with those of traditional distribution planning and also with Partial Swarm Optimization (PSO).
机译:本文提出了一种基于帕累托的多目标优化算法(MOA),称为强度帕累托进化算法(SPEA),用于配电网络中的分布式发电(DG)规划。与传统的多目标优化技术不同,该技术通过利用加权系数关联不同的目标函数并创建一个目标函数,而在SPEA中,每个目标函数都是分别进行优化的。由于目标函数相互冲突,因此SPEA会生成一组最优解,而不是一个最优解。在这项研究中考虑了三个不同的目标函数:(1)最小化发电成本(2)最小化有功功率损耗(3)最大化可靠性水平。目标是优化每个目标功能。 DG单元的位置和大小假定为设计变量。对结果进行了讨论,并将其与传统分配计划的结果以及部分群优化(PSO)的结果进行了比较。

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