电站多目标负荷优化分配与决策指导

Multi-objective Load Optimal Dispatch and Decision-making Guidance of Power Plant

对传统意义下的厂级负荷优化分配模型进行修正,同时考虑全厂供电煤耗率、污染排全放和负荷调整时间3个目标,提出厂级负荷分配的多目标优化模型。将多目标优化方法和多属性决策结合使用,研究多目标优化指导的问题。针对非劣分层遗传算法(nondominated sorting genetic algorithmII,NSGA-II)易于局部收敛的特点,提出了并行的NSGA-II多目标优化结构,增加了Pareto前沿的多样性,为决策提供丰富的信息。引入基于基点和熵的多属性决策方法,对Pareto解集进行排序,得出最优解。对某火电厂进行实例分析,结果表明该方法能准确快速地完成多目标负荷分配优化,并给出正确的指导,具有一定的实用性。

The traditional model of load dispatch was modified, three objectives which include power coal consumption rate of the whole plant, pollution emission and load adjusting time were considered simultaneously and a multi-objective plant load dispatch model was established. The multi-objective optimization and decision guidance problem was studied through a hybrid approach which was combined multi-objective optimization algorithm with multiple attributes decision making method. According to the local convergence of nondominated sorting genetic algorithms-Ⅱ （NSGA-Ⅱ）, a new parallel NSGA-Ⅱ multi-objective optimization structure was proposed. The diversity of Pareto front was increased and more abundant information for decision-making was provided. The Pareto solution set was sorted and the optimal solution was obtained by introducing method of multi-object decisionmaking based on maximum deviations and entropy. A case study of a power plant was carried out. The result shows that this method is practical and it can accomplish multi-objective plant load dispatch accurately and quickly. Finally the correct guidance is provided.