Chaotic self adaptive particle swarm approach for solving economic dispatch problem with valve-point effect

C. Rani, D. Kothari, K. Busawon
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Abstract

This research work presents a Chaotic Self Adaptive Particle Swarm Optimization (CSAPSO) algorithm in order to solve the Economic Dispatch (ED) problem. The main purpose of the work is to derive a simple and effective method for optimum generation dispatch to minimize the generation cost power networks by considering several non-linear characteristics of the generator such as valve point effect, prohibited operating zones and ramp rate limits. A chaotic local search operator is introduced in the proposed algorithm to avoid premature convergence. Simulation studies are carried out, using MATLAB software, to show the effectiveness of the proposed optimization method. The applicability and high feasibility of the proposed method is validated on three different test systems. Results show that the CSAPSO is more powerful than other algorithms.
求解具有阀点效应的经济调度问题的混沌自适应粒子群方法
为了解决经济调度问题,提出了一种混沌自适应粒子群优化算法(CSAPSO)。本文的主要目的是通过考虑发电机的阀点效应、禁止运行区域和斜坡速率限制等非线性特性,推导出一种简单有效的优化发电调度方法,使电网发电成本最小化。为了避免算法过早收敛,在算法中引入了混沌局部搜索算子。利用MATLAB软件进行了仿真研究,验证了所提优化方法的有效性。在三个不同的测试系统上验证了该方法的适用性和高可行性。结果表明,该算法比其他算法更强大。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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