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A novel short-term generation scheduling technique of thermal units using ant colony sea rch algorithms

机译:基于蚁群算法的火力单元短期发电调度新技术

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This paper presents a novel co-operative agents approach, ant colony search algorithm (ACSA)-based scheme, for solving a short-term generation scheduling problem of thermal power systems. The main purpose of this paper is to investigate the applicability of an alternative intelligent search method in power system optimisation, particularly in short-term generation scheduling problems. The ACSA is derived from the theoretical biology of the topic of ant trail formation and foraging methods. A set of co-operating agents, ants, co-operate to find a good solution for the short-term generation scheduling problem of thermal units. In the ACSA, the state transition rule, global and local updating rules are also introduced to ensure the optimal solution. Once all the ants have completed their tours, a global pheromone-updating rule is then applied and the process is iterated until the stop condition is satisfied. The effectiveness of the proposed scheme has been demonstrated on the daily generation scheduling problem of model power systems.
机译:本文提出了一种基于蚁群搜索算法(ACSA)的新型合作代理方法,用于解决火电系统的短期发电调度问题。本文的主要目的是研究替代智能搜索方法在电力系统优化中的适用性,特别是在短期发电调度问题中。 ACSA源自蚂蚁踪迹形成和觅食方法这一主题的理论生物学。一组协作代理,蚂蚁协作找到热单元短期发电调度问题的良好解决方案。在ACSA中,还引入了状态转换规则,全局和本地更新规则以确保最佳解决方案。一旦所有蚂蚁都完成了巡视,便会应用全局信息素更新规则,并重复该过程,直到满足停止条件为止。该方案的有效性已在模型电力系统的日发电调度问题上得到了证明。

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