改进遗传算法在复杂CHP系统负荷优化调度中的应用  

Application of Improved Genetic Algorithm in Load Optimal Scheduling of Complex CHP System

作　　者：白天宇 杨宇[2] 郑莆燕 程云瑞 封康 罗添 赵航 BAI Tianyu;YANG Yu;ZHENG Puyan;CHENG Yunrui;FENG Kang;LUO Tian;ZHAO Hang(Shanghai University of Electric Power,Shanghai 200090,China;Shanghai Power Equipment Research Institute,Shanghai 200240,China)

机构地区：[1]上海电力大学,上海200090 [2]上海发电设备成套设计研究院,上海200240

出　　处：《上海电力大学学报》2022年第5期478-482,共5页Journal of Shanghai University of Electric Power

基　　金：上海市科委节能减排专项--上海市热交换系统节能工程技术中心项目(17DZ2282800)。

摘　　要：多台热电联产机组组成的复杂热电联产(CHP)系统优化过程中会使得搜索域增大,优化收敛速度变慢。针对这一问题。通过借鉴内点法将原搜索范围进行离散、组合,从而将搜索范围进行合理收缩,提高了算法在寻优过程中的收敛速度,并使优化结果更接近全局最优。将改进遗传算法应用于某石化企业自备电厂的复杂CHP系统,并通过仿真模拟对优化结果进行验证。结果表明,改进遗传算法可以有效提高遗传算法的收敛速度和优化结果。In the process of optimization of complex combined heat and power(CHP)system composed of several combined heat and power units,the search area will be enlarged and the convergence speed will be slow.To solve this problem,the search area of genetic algorithm is optimized.By using interior point method for reference,the original search range is discretized and combined,and the search range is reduced reasonably,so as to improve the convergence speed of the algorithm in the process of optimization and make the optimization result closer to the global optimum.The improved algorithm is applied to the complex CHP system of a petrochemical enterprise’s own power plant and the optimization results are verified by simulation.The results show that the improved genetic algorithm can effectively improve the convergence speed and optimization results of the genetic algorithm.

关 键 词：改进遗传算法 负荷优化调度 热电联产 复杂系统 优化搜索域 

分 类 号：TK267[动力工程及工程热物理—动力机械及工程]