一种基于两阶段遗传的机组投用优化方法

A. Eldin, M. El-Sayed, H. Youssef
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引用次数: 23

摘要

提出了一种求解机组投入优化问题的遗传算法。所提出的技术主要包括两个阶段。在第一阶段,对每个学习间隔(小时)进行经济调度。围绕之前的经济调度解决方案生成了几个解决方案(个体)。这些个体作为遗传算法初始种群的一部分被引入,作为第二阶段应用于最优识别单元承诺优化问题的解决方案。所提出的技术应用于10单元和26单元测试系统。
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A two-stage genetic based technique for the unit commitment optimization problem
A genetic based technique is presented for solving the unit commitment optimization problem. The proposed technique consists mainly of two stages. In the first stage, economic dispatch for each interval (hour) of study is executed. Several solutions (individuals) are generated around the previous economic dispatch solution. These individuals are introduced as a part of the initial population of the genetic algorithm which is applied as a second stage to optimally identify the solution of the unit commitment optimization problem. The proposed technique is applied to the 10 unit, and the 26 unit test systems.
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