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基于APSO算法的水火电力系统模糊多目标优化调度 被引量:4

Multi-objective fuzzy optimal scheduling for hydro-thermal power system based on anti-predatory particle swarm algorithm
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摘要 建立了以火电厂运行成本最低、污染气体排放最小和水电厂发电效益最大为目标的水火电短期多目标优化调度模型,以3个火电厂与4个梯级水电厂的组成的水火电系统相关数据为实际算例,采用基于反捕食粒子群算法的交互式模糊满意度多目标决策方法,建立不同的决策模型将多目标问题转化为单目标求解,决策者可根据不同的主观效益诉求得到满意的调度方案,避免了人为选取目标权重的随意性,决策计算过程简单实用。算例结果表明,所建模型的正确性和该方法的可行性。 This paper build a multi-objective optimal daily active power load dispatching model in which the lowest thermal power plants operational costs, least emission of polluted gas and maximized generation benefits of hydroelectric power stations are taken as optimal objectives. The composition practical example related data of hydrothermal systems contains three thermal power plants and four cascade hydropower plants. An interactive multi-objective decision-making method based on anti-predatory particle swarm algorithm was proposed in this paper, and the solution of multi-objective problem was transformed into those of single objective problems by means of establishing different decision-making mod- els. According to different subjective benefits aspirations, decision makers were satisfied with the scheduling program, thus the arbitrariness of artificially choosing objective weight can be avoided, and it makes the proposed method easy to operate and apply. Results of calculation example prove that the presented model is correct and the feasibility of the method.
出处 《华北电力大学学报(自然科学版)》 CAS 北大核心 2012年第4期65-71,共7页 Journal of North China Electric Power University:Natural Science Edition
关键词 水火电力系统 优化调度 模糊多目标 反捕食粒子群算法 hydro-thermal power systems optimal dispatch fuzzy multi-objective anti-predatory particle swarm algorithm
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