A robust optimization framework for energy management of CCHP users with integrated demand response in electricity market

被引:52
作者
Chen, Lingmin [1 ]
Tang, Huiling [2 ]
Wu, Jiekang [3 ]
Li, Changjie [4 ]
Wang, Yanan [5 ]
机构
[1] Guangdong Univ Technol, Dept Expt Teaching, Guangzhou, Peoples R China
[2] Guangdong Univ Technol, Sch Phys & Optoelect Engn, Guangzhou, Peoples R China
[3] Guangdong Univ Technol, Sch Automation, Guangzhou, Peoples R China
[4] CSG Power Generat Co LTD, Guangzhou, Peoples R China
[5] Chengdu Univ, Sch Elect Informat & Elect Engn, Chengdu, Peoples R China
基金
中国国家自然科学基金;
关键词
Electricity market; CCHP user; Energy management; Integrated demand response; Robust optimization; Column constraint generation algorithm; HEATING-SYSTEMS; MICROGRIDS; STORAGE; OPERATION; DISPATCH;
D O I
10.1016/j.ijepes.2022.108181
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Micro-energy grid for CCHP users can make full use of local renewable energy and integrated demand response (IDR) resources to meet the electric, cooling, heating and other load demands in electricity market. In this paper, aiming at the uncertainties of renewable energy output and electric, cooling and heating load in micro-energy grid, a mode of IDR resources flexibly participating in day-ahead scheduling and intra-day real-time regulation stage in micro-energy grid is established, and a two-stage robust scheduling optimization model with IDR considered is constructed. In the model, the cost and constraints of IDR resources participating in two-stages is considered, and the uncertain budget parameter is introduced for regulating economy and robustness of the system. In day-ahead stage, the day-ahead scheduling cost is taken as the goal to determine the output of each unit, energy storage and IDR resource response mode. Based on the optimization results of day-ahead stage, each regulation quantity of the system is determined with the goal of minimizing the real-time regulation cost within a day. Strong duality theory and column constraint generation algorithm is used to transform and solve the robust optimization problem of min-max-min structure. The results show that the robust optimization model can improve the system's ability to resist uncertain risks, and the integrated demand response can improve the economy of the robust optimization model and the self-sufficiency of micro-energy grid.
引用
收藏
页数:20
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