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Search space reduction strategies for unit commitment problem

机译:搜索空间减少策略以解决单元承诺问题

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In electricity markets, independent system operators solve the unit commitment (UC) problem to determine the on/off status of generating units with respect to the day-ahead load forecast. However, as the size of power systems grows, computational complexity of the UC problem drastically increases. In this paper, based on the greedy adaptive search procedure (GRASP) technique, we propose a novel heuristic algorithm to reduce the number of variables and constraints in the day-ahead unit commitment problem. Once the size of the problem is reduced, we employ a state-of-the-art mixed integer programing method to solve the problem. The numerical results show the effectiveness of the proposed algorithm.
机译:在电力市场中,独立的系统运营商可以解决机组承诺(UC)问题,从而根据日间负荷预测确定发电机组的开/关状态。但是,随着电力系统规模的扩大,UC问题的计算复杂度急剧增加。在本文中,基于贪婪自适应搜索过程(GRASP)技术,我们提出了一种新颖的启发式算法,以减少提前预定单元承诺问题中的变量和约束数量。一旦问题的大小减小了,我们将采用最新的混合整数编程方法来解决该问题。数值结果表明了该算法的有效性。

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