经济负荷调度问题中不同粒子群算法的比较分析

K. Kalita, A. Rai, Kunal Pandey, Rachana Garg
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引用次数: 0

摘要

在电力平衡和发电约束的限制下,互联电力系统中各发电机组以尽可能低的成本确定最优发电量的问题被称为经济负荷调度问题。本文比较了粒子群算法在ELD问题上的应用。各种方法包括传统粒子群算法、基于模拟退火的粒子群算法(SA-PSO)、时变加速度常数粒子群算法(PSO- tvac)和自适应粒子群算法(APSO)。这些方法在一个六台发电机的电力系统上进行了测试。在给出最优解和收敛性的基础上,对所有这些方法进行了比较分析
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Comparative Analysis of different Variants of Particle Swarm Optimization for Economic Load Dispatch Problem
The determination of optimal power generation by generating units in an interconnected power system at the least possible cost, subject to power balance and limits of generation constraints, is called Economic Load Dispatch (ELD) problem. Different variants of Particle Swarm Optimization (PSO) applied on the problem of ELD are compared in this paper. The various methods viz - Conventional PSO, Simulated Annealing based PSO (SA-PSO), PSO with Time-Varying Acceleration Constant (PSO-TVAC) and Adaptive PSO (APSO). These methods are tested on a six-generator electrical power system. A comparative analysis of all these methods has been done on the basis of their ability to give an optimum solution, convergence
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