Minimization of fuel cost in solving the power economic dispatch problem including transmission losses by using modified Particle Swarm Optimization

J. Rizwana, R. Jeevitha, R. Venkatesh, K. Parthiban
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引用次数: 6

Abstract

Under normal operating conditions, the generation capacity is more than the total load demand and losses. The objective is to find the real power scheduling of each generator for an interconnected power system under testing condition to minimize the operating cost of the power plant. Hence the generators power are allowed to vary within the given limits to meet the particular load with minimum fuel cost which is called as optimal power flow problem. The objective function of this paper is to minimize the fuel cost of the power system for the various loads under consideration by solving the economic dispatch problem (EDP) of real power generation by using MPSO optimization algorithm. This paper compares the optimization techniques such as Particle Swarm Optimization, Modified Particle Swarm Optimization (MPSO) in a 3-unit generating system to show the effectiveness of the MPSO algorithm. Also by using the optimization technique the power losses of the considered power system were reduced.
利用改进粒子群算法求解包含输电损耗的电力经济调度问题中的燃料成本最小化
在正常运行条件下,发电容量大于负荷总需求和总损耗。目标是在测试状态下,找出互联电力系统中各发电机组的真实功率调度,以使电厂的运行成本最小。因此,允许发电机的功率在给定的范围内变化,以最小的燃料成本满足特定的负荷,称为最优潮流问题。本文的目标函数是通过MPSO优化算法求解实际发电的经济调度问题,使电力系统在考虑各种负荷时的燃料成本最小。本文将粒子群算法和改进粒子群算法(MPSO)在3单元发电系统中的应用进行了比较,证明了MPSO算法的有效性。同时利用优化技术降低了所考虑的电力系统的功率损耗。
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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