综合能源系统中多能源协同优化方法研究  

Research on Multi-energy Collaborative Optimization Method in Integrated Energy System

作　　者：武志宏[1] 杨永标 李熙 李泽斌 张卫国[5] WU Zhihong;YANG Yongbiao;LI Xi;LI Zebin;ZHANG Weiguo(State Grid Shanxi Electric Power Company,Taiyuan 030000,Shanxi,China;School of Electrical and Engineering,Southeast University,Nanjing 210096,Jiangsu,China;State Grid Shanxi Integrated Energy Service Co.,Ltd.,Taiyuan 030000,Shanxi,China;State Grid Taiyuan Power Supply Company,Taiyuan 030000,Shanxi,China;NARI Technology Co.,Ltd.,Nanjing 210008,Jiangsu,China)

机构地区：[1]国网山西省电力公司,山西太原030000 [2]东南大学电气工程学院,江苏南京210096 [3]国网山西省综合能源服务有限公司,山西太原030000 [4]国网太原供电公司,山西太原030000 [5]国电南瑞科技股份有限公司,江苏南京210008

出　　处：《电气传动》2022年第2期67-73,共7页Electric Drive

基　　金：国家电网公司科技项目(2016YFB0901100)。

摘　　要：针对当前多能源协同优化相关研究成果减排和可靠性待优化等问题,提出基于混沌蛙跳算法的综合能源系统中多能源协同优化方法。以系统总费用最低、可靠性最强、减排率最高等为目标函数,以可靠性、热量均衡、设备运行、储能、需求响应等方面为约束条件,构建多能源协同优化模型。引入混沌蛙跳算法对目标模型进行求解,利用混沌蛙跳算法具备的快速寻优性能逐渐向理论最优解逼近,根据自适应网格密度法对最优解规模进行动态维护,同时采用自适应混沌优化方式优化最优解集合多样性,最后通过最优解选取方案为蛙群选取最佳的更新粒子,当满足得到最优解或达到最大迭代次数条件时,算法停止运行,并输出最优解,得到符合目标模型的多能源协同优化方案。实验表明,该方法能够有效提高系统可靠性,且在减排环保方面也有很强的鲁棒性。Aiming at the problems of current multi-energy collaborative optimization related research results reduction and reliability to be optimized,a multi-energy collaborative optimization method based on chaotic leapfrog algorithm for integrated energy systems was proposed. Taking the lowest total system cost,the strongest reliability and the highest emission reduction rate as the objective function,the multi-energy collaborative optimization model was constructed with the constraints of reliability,heat balance,equipment operation,energy storage and demand response. The chaotic frog leaping algorithm was introduced to solve the target model. The fast optimization performance of the chaotic frog leaping algorithm was gradually approached to the theoretical optimal solution. The optimal solution scale was dynamically maintained according to the adaptive mesh density method. The chaos optimization method optimized the optimal solution set diversity. Finally,the optimal update particle was selected for the frog group by the optimal solution selection scheme. When the optimal solution or the maximum number of iterations was satisfied,the algorithm stopped running and the output was optimal solution,a multi-energy collaborative optimization scheme that meets the target model was obtained. Experiments show that this method can effectively improved system reliability and has strong robustness in reducing environmental protection.

关 键 词：综合能源系统 多能源 协同优化 

分 类 号：TK01[动力工程及工程热物理]