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Solution to security constrained unit commitment problem using genetic algorithm

机译:用遗传算法解决安全约束单位承诺问题

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In this paper Optimal Power Flow (OPF) with line flow constraint is incorporated in solving the Unit Commitment (UC) problem using Genetic Algorithm (GA). In this proposed approach the problem is solved in two phases. In the first phase unit commitment is solved with prevailing constraints, without line flow constraint by genetic algorithm. In the second phase the violations in the lines are minimized for a committed schedule using GA based OPF. The resulting solution minimizes line flow violations in the critical lines under unit's decommitted hours by adjusting the unit generations. In this paper, a 66-bus Indian utility system with 12 generating units and 93 transmission lines is considered to exhibit the effectiveness of the proposed approach.
机译:在本文中,采用线流约束的最优潮流(OPF)被用于解决使用遗传算法(GA)的机组承诺(UC)问题。在该提出的方法中,该问题分两个阶段解决。在第一阶段,通过遗传算法解决单元承诺问题,并具有主要约束条件,而没有线流量约束条件。在第二阶段,使用基于GA的OPF将行中的违规行为最小化,以确保已提交的计划。最终的解决方案通过调整机组发电量,最大限度地减少了机组退役小时内关键管线的管线流量违规情况。在本文中,具有12个发电机组和93条输电线路的66总线印度公用事业系统被认为可以显示出该方法的有效性。

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