基于遗传算法的多机组热电负荷分配优化研究  

Research on Multi-unit Heat and Power Loads Allocation Optimization Based on Genetic Algorithm

作　　者：贾振国 张月雷 管洪军 刘兴先 李宏伟[1] 刘为民 杨可 Jia Zhenguo;Zhang Yuelei;Guan Hongjun

机构地区：[1]胜利石油管理局有限公司胜利发电厂,山东东营257000

出　　处：《上海电气技术》2024年第4期21-25,20,共6页Journal of Shanghai Electric Technology

摘　　要：热电联产机组同时能生产热负荷和电负荷,得到广泛应用。为达到节约能源的目的,对热电联产机组进行热电负荷分配优化,是至关重要的问题。以胜利发电厂四台机组为研究对象,研究各台机组经济指标随电负荷、采暖供热量、工业供汽流量及其它相关因素的变化关系及规律,并提出基于遗传算法的多机组热电负荷分配优化方法。结果表明,优化后热耗明显降低,极大提高了全厂多机组在热电负荷分配时的准确度,并提高了运行经济性。Combined heat and power unit can simultaneously generate both heat and power loads,and has been widely applied.To achieve energy saving,optimizing the heat and power loads allocation of combined heat and power unit is a critical issue.Taking four units of Shengli Power Plant as the research object,the relationship and pattern of changes in the economic indicator of each unit with respect to power load,heating supply,industrial steam flow,and other related factors were studied.Additionally,a multi-unit heat and power loads allocation optimization method based on genetic algorithm was proposed.The result shows that after optimization,heat consumption is significantly reduced,greatly improving the accuracy of multi-unit heat and power loads allocation across the entire plant,and enhancing the operational economy.

关 键 词：遗传算法 热电联产 负荷 分配 优化 

分 类 号：TM621[电气工程—电力系统及自动化]