Research on a Bi-Level Collaborative Optimization Method for Planning and Operation of Multi-Energy Complementary Systems

被引:6
|
作者
Liu, Changrong [1 ,2 ]
Wang, Hanqing [1 ,3 ]
Liu, Zhiqiang [1 ]
Wang, Zhiyong [2 ]
Yang, Sheng [1 ]
机构
[1] Cent South Univ, Sch Energy Sci & Engn, Changsha 410083, Peoples R China
[2] Hunan Univ Technol, Sch Civil Engn, Zhuzhou 412007, Peoples R China
[3] Cent South Univ Forestry & Technol, Sch Civil Engn, Changsha 410004, Peoples R China
基金
中国国家自然科学基金;
关键词
multi-energy complementary system; bi-level; single-level; multi-objective optimization; NSGA-III; DISTRIBUTED ENERGY SYSTEM; STORAGE;
D O I
10.3390/en14237930
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Multi-energy complementary systems (MCSs) are complex multilevel systems. In the process of system planning, many aspects-such as power planning, investment cost, and environmental impact-should be considered. However, different decision makers tend to have different levels of control objectives, and the multilevel problems of the system need to be solved effectively with comprehensive judgment. Therefore, based on the terminal MCS energy structure model, the optimization method of MCS planning and operation coordination, considering the influence of planning and operation in the system's life cycle, is studied in this paper. Consequently, the research on the collaborative optimization strategy of MCS construction and operation was carried out based on the bi-level multi-objective optimization theory in this paper. Considering the mutual restraint and correlation between system construction and operation in practical engineering, a bi-level optimization model for collaborative optimization of MCS construction and operation was constructed. To solve the model effectively, the existing non-dominated sorting genetic algorithm III (NSGA-III) was improved by the authors on the basis of previous research, which could enhance the global search ability and convergence speed of the algorithm. To effectively improve and strengthen the reliability of energy supply, and increase the comprehensive energy utilization of the system, the effects of carbon transaction cost and renewable energy penetration were considered in the optimization process. Based on an engineering example, the bi-level model was solved and analyzed. It should be noted that the optimization results of the model were verified to be applicable and effective by comparison with the single-level multi-objective programming optimization. The findings of this paper could provide theoretical reference and practical guidance for the planning and operation of MCSs, making them significant for social application.
引用
收藏
页数:20
相关论文
共 50 条
  • [1] Bi-level optimization configuration method for multi-energy microgrid considering chance constraints
    Zhang K.
    Feng P.
    Zhang G.
    Hou J.
    Xie T.
    Li M.
    [J]. Zhang, Gang (zhanggang3463003@163.com), 1600, Science Press (42): : 41 - 48
  • [2] Research on operation characteristics and optimization of a multi-energy complementary integrated system
    Li, Lan
    Liu, Zhiqiang
    Liu, Jiaxing
    [J]. Taiyangneng Xuebao/Acta Energiae Solaris Sinica, 2020, 41 (07): : 49 - 56
  • [3] Bi-Level Approach for Modeling Multi-Energy Players' Behavior in a Multi-Energy System
    Damavandi, Maziar Yazdani
    Bahramara, Salah
    Moghaddam, Mohsen Parsa
    Haghifam, Mahmoud-Reza
    Shafie-khah, Miadreza
    Catalao, Joao P. S.
    [J]. 2015 IEEE EINDHOVEN POWERTECH, 2015,
  • [4] Joint Optimization of Planning and Operation in User-side Multi-energy Systems
    Cui Q.
    Bai X.
    Dong W.
    Huang B.
    [J]. Zhongguo Dianji Gongcheng Xuebao/Proceedings of the Chinese Society of Electrical Engineering, 2019, 39 (17): : 4967 - 4981
  • [5] Including research on optimization planning of multi-energy complementary electric vehicle charging station
    Cai, Rong
    Huang, Kun
    Zheng, Shu
    Liang, Jiaben
    Dong, Xiaofeng
    [J]. ENERGY REPORTS, 2023, 9 : 1037 - 1047
  • [6] Including research on optimization planning of multi-energy complementary electric vehicle charging station
    Cai, Rong
    Huang, Kun
    Zheng, Shu
    Liang, Jiaben
    Dong, Xiaofeng
    [J]. ENERGY REPORTS, 2023, 9 : 1037 - 1047
  • [7] Decentralized bi-level stochastic optimization approach for multi-agent multi-energy networked micro-grids with multi-energy storage technologies
    Ahmadi, Seyed Ehsan
    Sadeghi, Delnia
    Marzband, Mousa
    Abusorrah, Abdullah
    Sedraoui, Khaled
    [J]. ENERGY, 2022, 245
  • [8] Optimal configuration and operation of multi-energy complementary distributed energy systems
    Guan, Tingting
    Lin, Haiyang
    Sun, Qie
    Wennersten, Ronald
    [J]. CLEANER ENERGY FOR CLEANER CITIES, 2018, 152 : 77 - 82
  • [9] Research on the Collaborative Optimization of Multi-Energy Flow Microgrids
    Wu, Fan
    Huang, Shangyuan
    Li, Rui
    Guo, Qinglai
    Sun, Hongbin
    Pan, Zhaoguang
    [J]. PROCEEDINGS OF RENEWABLE ENERGY INTEGRATION WITH MINI/MICROGRID (REM2016), 2016, 103 : 345 - 350
  • [10] Bi-level optimization of design, operation, and subsidies for standalone solar/diesel multi-generation energy systems
    Luo, Xi
    Liu, Jiaping
    Liu, Yanfeng
    Liu, Xiaojun
    [J]. SUSTAINABLE CITIES AND SOCIETY, 2019, 48