摘要
冷热电联供(combined cooling,heat and power,CCHP)系统的高效、经济运行取决于CCHP系统设备容量和运行策略的整体优化。为提高CCHP系统的实用性,文章提出了一种计及风光储的CCHP系统双层协同优化配置方法:外层优化配置以年化总成本最优和污染物排放量最低为目标函数,采用NSGAⅡ算法获得设备的容量配置;内层优化配置中采用对偶理论构建鲁棒模型,以考虑污染物排放和购能成本的总运行成本最优为目标函数,得到各设备的优化调度结果。最后,以某园区的CCHP系统为研究对象,采用所提双层协同优化配置方法对该系统进行优化配置,仿真结果验证了所提方法的有效性,能够兼顾经济性和环保性,有效实现系统的协同优化。
The efficient and economical operation of combined cooling,heat and power(CCHP)system depends on the overall optimization of the system’s equipment capacity and operating strategy.In order to improve the practicality of the CCHP,a two-layer collaborative optimization configuration method for the CCHP system considering wind power,solar power and energy storage is proposed.The optimized configuration of the outer layer aims at the best economic net present value and the lowest pollutant emissions as the objective function,and the NSGAⅡalgorithm is used to obtain the capacity configuration of the devices.The dual theory is used in the inner optimization configuration to build a robust model,and the optimal annual operating cost considering pollutant emissions and energy purchase costs is the objective function to obtain the optimal scheduling of each device.Finally,taking the CCHP system of a certain park as the research object,the double-layer collaborative optimization configuration method proposed in this paper is used to optimize the configuration of the system.The simulation results verify the effectiveness of the proposed method,which can effectively realize the collaborative optimization of the system with both economy and environmental protection.
作者
江卓翰
刘志刚
许加柱
伍敏
谢欣涛
侯益灵
JIANG Zhuohan;LIU Zhigang;XU Jiazhu;WU Min;XIE Xintao;HOU Yiling(Hunan Key Laboratory of Energy Internet Supply-Demand and Operation(State Grid Hunan Electric Power Company Limited Economic&Technical Research Institute),Changsha 410004,China;College of Electrical and Information Engineering,Hunan University,Changsha 410082,China)
出处
《电力建设》
CSCD
北大核心
2021年第8期71-80,共10页
Electric Power Construction
基金
国网湖南省电力有限公司科技项目(5216A2200009)
湖南省科技创新平台与人才计划(2019TP1053)。