考虑风电消纳的热电联供微电网系统协同优化策略研究  

Strategy Study of Synergistic Optimization Considering Wind Energy Consumption for CHP Microgrids

作　　者：卢晓东 徐彤宇 王明伟 陈剑 杨玉龙[1] LU Xiaodong;XU Tongyu;WANG Mingwei;CHEN Jian;YANG Yulong(Northeast Electric Power University,Jilin 132012,China;State Grid Daxing′anling Power Supply Company,Daxing′anling 165000,China;State Grid Chengde Power Supply Company,Chengde 067000,China)

机构地区：[1]东北电力大学,吉林吉林132012 [2]国网大兴安岭供电公司,黑龙江大兴安岭165000 [3]国网承德供电公司,河北承德067000

出　　处：《吉林电力》2024年第2期1-4,19,共5页Jilin Electric Power

摘　　要：针对新能源的波动性和随机性使其在电力系统中的消纳存在困难,弃风、弃光现象频发,提出一种考虑风电消纳的热电联供微电网源-荷-储协同优化技术。以微网的运行总成本及风电消纳水平为优化目标,在调节热电联供机组出力的同时,结合蓄热式电锅炉储热系统及储能系统的灵活调节能力,进行微电网运行的协同优化。所提出模型通过非支配排序遗传算法(non-dominated sorting genetic algorithm,NSGA-Ⅱ)进行求解,并基于某园区微电网数据进行了验证,相较于单一灵活性资源的优化调度,所提的源-荷-储协同优化模型能够在兼顾成本的同时保证较高的风电消纳水平。The volatility and randomness of new energy sources make it difficult to consume them in power system.Therefore,the abandonment of wind/photovoltaic energy occurs frequently.A synergistic source-load-storage optimization considering the wind energy consumption for cogeneration microgrids is proposed in this paper.Taking the total cost of operation of the microgrid and the wind power consumption as the optimization objectives,the synergistic optimization of microgrid is carried out based on the cooperative control of cogeneration units,energy storage system and thermal storage system.The proposed model is solved by non-dominated sorting genetic algorithm(NSGA-Ⅱ)optimization algorithm and validated based on real data in an industrial microgrid.The proposed source-load-storage co-optimization model can ensure the wind power consumption in a reasonable running cost compared with the optimization model considering the single flexible resource.

关 键 词：新能源 风电消纳 热电联供 微电网 蓄热式电锅炉 NSGA-Ⅱ 

分 类 号：TM73[电气工程—电力系统及自动化]