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Application of the ant colony search algorithm to short-term generation scheduling problem of thermal units

机译:蚁群搜索算法在火电机组短期发电调度中的应用

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This paper presents a new co-operative agents approach, the Ant Colony Search Algorithm (ACSA), for solving a short-term generation scheduling problem of thermal power system. One of the main goals of this paper is to investigate the applicability of an alternative intelligent search method in power system optimisation. The ACSA derived from the theoretical biology on the topic of ant trail formation and foraging methods. In the ACSA, a set of co-operating agents called ants co-operate to find good solution to short-term generation scheduling problem of thermal units. The effectiveness of the proposed scheme has been demonstrated on the daily scheduling problem of a model power system and the results are compared with those obtained by a conventional scheduling method.
机译:本文提出了一种新的合作代理方法,即蚁群搜索算法(ACSA),用于解决火电系统的短期发电调度问题。本文的主要目标之一是研究替代智能搜索方法在电力系统优化中的适用性。 ACSA起源于关于蚂蚁踪迹形成和觅食方法的理论生物学。在ACSA中,一组称为蚂蚁的合作代理进行合作,以找到热单元短期发电调度问题的良好解决方案。在模型电力系统的日常调度问题上证明了该方案的有效性,并将结果与​​常规调度方法获得的结果进行了比较。

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