Short-term hydrothermal scheduling using particle swarm optimization with constriction Factor and Inertia Weight Approach

Koustav Dasgupta, Sumit Banerjee
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引用次数: 6

Abstract

The paper presents Particle Swarm Optimization with Constriction Factor and Inertia Weight Approach which is applied to determine the optimal hourly schedule of power generation in a hydrothermal power system. The objective of the hydrothermal scheduling problem is to find out the discharge of hydro plants and power generation of thermal plants to minimize the total fuel cost at a schedule horizon while satisfying various constraints. In the present work, the effects of valve point loading in the fuel cost function of the thermal plants are also considered. The developed algorithm is illustrated for a test system consisting of four hydro plants and three thermal plants. It is found that proposed particle swarm optimization with constriction factor and inertia weight factor approach (PSOCFIWA) appears to be the powerful to minimize fuel cost.
基于收缩因子和惯性权重的粒子群优化短期热液调度
提出了基于收缩因子和惯性权重的粒子群优化方法,并将其应用于水热发电系统的最佳小时发电计划的确定。热液调度问题的目标是在满足各种约束条件的情况下,找出水电厂的排放量和火电厂的发电量,以使总燃料成本在一个调度水平上最小。本文还考虑了阀点负荷对热电厂燃料成本函数的影响。以一个由四个水电厂和三个火电厂组成的测试系统为例说明了所开发的算法。结果表明,结合收缩因子和惯性权重因子的粒子群优化方法(PSOCFIWA)能够有效地降低燃油成本。
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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