摘要
对传统意义下负荷调度模型进行修正,同时考虑最小化燃料费用和污染排放量,提出了火电站多目标负荷调度模型;并将强度Pareto进化算法(SPEA2)与并行遗传算法(PGA)相结合对其求解.结果表明:该算法求得的Pareto最优解分布均匀、收敛速度快、寻优能力强,决策者可根据不同的侧重点在Pareto解集中选择最终的满意解.应用该算法对某电厂进行多目标负荷调度,验证了其可行性和有效性.
The traditional model of established, which is intended to load dispatch is modified, and a multi-objective load dispatch model is minimize the fuel cost as well as pollution emission. Strength Pareto evolutionary algorithm （SPEA2） and parallel genetic algorithm （PGA） are combined to gain the final solution. Results indicate that this method can obtain uniformly distributed Pareto-optimal solutions. And it has good convergence and powerful optimization capability. The satisfactory solution can be selected in Pareto optimum set according to different emphases. Finally the feasibility and validity of this algorithm are proved by a case study on a real power plant.
出处
《动力工程》
EI
CSCD
北大核心
2008年第3期404-407,共4页
Power Engineering
基金
国家自然科学基金重点资助项目(90612018)
重大资助项目(50595410)
关键词
自动控制技术
火电站
多目标负荷调度
强度Pareto进化算法
并行遗传算法
PARETO最优解
automatic control technology
thermal power plant
multi-objective load dispatch
strength Pareto evolutionary algorithm
parallel genetic algorithm（PGA）
Pareto-optimal solution
