基于BAT优化算法的电压稳定增强和电压偏差最小化

I. Trivedi, Motilal Bhoye, Pradeep Jangir, Siddharth A. Parmar, Narottam Jangir, Arvind Kumar
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引用次数: 15

摘要

本文采用一种新颖的元启发式BAT优化算法(BOA)对现代电力系统中最常见的最优潮流(OPF)问题进行了优化。BOA的灵感来自于微型蝙蝠的回声定位能力。美国银行的收敛速度很快。为了解决最优潮流问题,采用标准的IEEE-30总线测试系统。为了解决所提出的问题,实现了BOA。OPF问题考虑的问题是降低燃料成本、减小电压偏差和提高电压稳定性。并将BOA算法的计算结果与花朵授粉算法(FPA)和粒子群优化算法(PSO)进行了比较。结果表明,与FPA和PSO相比,BOA给出了更好的优化值,证实了所提算法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Voltage stability enhancement and voltage deviation minimization using BAT optimization algorithm
In this work, the most common problem of the modern power system named optimal power flow (OPF) is optimized using the novel meta-heuristic BAT Optimization Algorithm (BOA). BOA is inspired by the echolocation capability of micro-bats. BOA has a fast convergence rate. In order to solve the optimal power flow problem, standard IEEE-30 bus test system is used. BOA is implemented for the solution of proposed problem. The problems considered in the OPF problem are Fuel Cost Reduction, Voltage Deviation Minimization, and Voltage Stability Improvement. The results obtained by BOA is compared with other techniques such as Flower Pollination Algorithm (FPA) and Particle Swarm Optimizer (PSO). Results shows that BOA gives better optimization values as compared with FPA and PSO that confirms the effectiveness of the suggested algorithm.
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