Non convex economic load dispatch problem by Efficient Biogeography Based Optimization algorithm

M. Vanitha, K. Thanushkodi
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引用次数: 3

Abstract

In this paper a new Efficient Biogeography Based Optimization (EBBO) algorithm is discussed and it is applied to solve the non convex Economic Load Dispatch (ELD) problem for the minimization of fuel cost. This EBBO uses the concept of Particle Swarm Optimization (PSO), mutation of Differential Evolution (DE) and migration of Biogeography Based Optimization (BBO). The conventional PSO is improved by using the mutation operators of DE and migration of BBO. Thus, the EBBO method gives a global optimal solution to the ELD problem and it also improves the computational time in comparison to other optimization methods. The combined methodology is applied to test the performance of the test system consisting of 40 thermal units. Fuel cost function takes into account the valve-point loading effects. The simulation result shows that this method has the capability to generate the best solution with better convergence speed.
基于高效生物地理优化算法的非凸经济负荷调度问题
本文讨论了一种新的基于高效生物地理的优化算法(EBBO),并将其应用于求解燃油成本最小化的非凸经济负荷调度问题。该算法采用了粒子群优化(PSO)、差分进化(DE)的突变和基于生物地理的迁移优化(BBO)的概念。利用DE的突变算子和BBO的迁移算子对传统粒子群算法进行了改进。因此,EBBO方法给出了ELD问题的全局最优解,并且与其他优化方法相比,该方法的计算时间大大缩短。采用该方法对40个热单元组成的测试系统进行了性能测试。燃料成本函数考虑了阀点负荷效应。仿真结果表明,该方法能够以较快的收敛速度生成最优解。
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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