基于人工生态系统优化(AEO)算法的最优DG集成

Djedidi Imene, Naimi Djemai, Salhi Ahmed, Bouhanik Anes
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引用次数: 0

摘要

本文提出了一种基于人工生态系统优化(AEO)算法的新型高效优化方法,用于解决径向配电系统中分布式发电(dg)的最佳选址和规模问题。其目标是以恒定和瞬时的方式满足波动的需求,同时尊重在相等和不相等约束下减少功率损耗、最小化运行成本和改善电压分布的要求。利用IEEE-33总线径向配电网测试系统,对该方法在求解质量和收敛特性方面的鲁棒性进行了评价。仿真结果与文献中对同一测试系统采用的其他方法进行了比较。实验结果表明,本文提出的AEO方法能够在较短的计算时效性内获得较高质量的解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimal DG Integration Using Artificial Ecosystem-Based Optimization (AEO) Algorithm
This paper presents a novel and efficient optimization approach based on the Artificial Ecosystem Optimization (AEO) algorithm to solve the problem of finding optimal location and sizing of Distributed Generation (DGs) in radial distribution systems. The objective is to satisfy a fluctuating demand in a constant and instantaneous way while respecting the requirements of power loss reduction, operating cost minimization and voltage profile improvement within the equality and inequality constraints. The robustness of the proposed technique in terms of solution quality and convergence characteristics is evaluated using the IEEE-33 bus radial distribution network test system. The simulation results are compared with those of other methods recently used in the literature for the same test system. The experimental outcomes show that the proposed AEO approach is comparatively able to achieve a higher quality solution within a timeliness of computation.
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