Analysis of optimal configuration of energy storage in wind-solar micro-grid based on improved gray wolf optimization

被引:2
作者
Huang, Qian [1 ]
Huang, Dengke [1 ]
Cai, Li [1 ]
Xu, Qingshan [2 ]
机构
[1] Chongqing Three Gorges Univ, Sch Elect & Informat Engn, Chongqing, Peoples R China
[2] Southeast Univ, Sch Elect Engn, Nanjing, Peoples R China
关键词
Micro-grid; Improved Gray Wolf Optimization (IGWO); Optimize operation; Double-layer optimization model; Energy storage capacity configuration;
D O I
10.2516/stet/2024070
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
To make full use of the electric power system based on energy storage in a wind-solar microgrid, it is necessary to optimize the configuration of energy storage to ensure the stability of a multi-energy system. This paper analyses the structure and function of the microgrid system, establishes the mathematical model, and analyzes the output characteristics. A double-layer optimization model of energy storage system capacity configuration and wind-solar storage micro-grid system operation is established to realize PV, wind power, and load variation configuration and regulate energy storage economic operation. The mathematical model of the improved gray wolf optimization is constructed, and the typical landscape resource data of a residential district. Comparing the difference between energy storage without an installation and energy storage with improved algorithm, it is shown that the energy storage configuration of the improved gray wolf optimization improves the economy, efficient energy use, and revenue of the whole system.
引用
收藏
页数:12
相关论文
共 19 条
[1]   A comparative study between racking systems for photovoltaic power systems [J].
Barbon, A. ;
Fortuny Ayuso, P. ;
Bayon, L. ;
Silva, C. A. .
RENEWABLE ENERGY, 2021, 180 :424-437
[2]   The Development and Future of Lithium Ion Batteries [J].
Blomgren, George E. .
JOURNAL OF THE ELECTROCHEMICAL SOCIETY, 2017, 164 (01) :A5019-A5025
[3]  
[程浩忠 Cheng Haozhong], 2019, [电力系统自动化, Automation of Electric Power Systems], V43, P2
[4]   Review and Techno-Economic Analysis of Emerging Thermo-Mechanical Energy Storage Technologies [J].
Gautam, Khem Raj ;
Andresen, Gorm Brunn ;
Victoria, Marta .
ENERGIES, 2022, 15 (17)
[5]   Optimal planning and design of a renewable energy based supply system for micro-grids (vol 45, pg 7, 2012) [J].
Hafez, Omar ;
Bhattacharya, Kankar .
RENEWABLE ENERGY, 2021, 165 :127-127
[6]  
Igiri CP, 2020, Recent Advances in Computer Science and Communications, V13, P5, DOI [10.2174/2213275912666190101120202, 10.2174/ 2213275912666190101120202, DOI 10.2174/2213275912666190101120202]
[7]   Multi-objective energy planning for China's dual carbon goals [J].
Jia, Xiaoping ;
Zhang, Yanmei ;
Tan, Raymond R. ;
Li, Zhiwei ;
Wang, Siqi ;
Wang, Fang ;
Fang, Kai .
SUSTAINABLE PRODUCTION AND CONSUMPTION, 2022, 34 :552-564
[8]  
Li Z.W., 2024, Sci. Technol. Energy Storage, P1, DOI [10.19799/j.cnki.2095-4239.2024.0165, DOI 10.19799/J.CNKI.2095-4239.2024.0165]
[9]   Energy Storage Data Reporting in Perspective-Guidelines for Interpreting the Performance of Electrochemical Energy Storage Systems [J].
Mathis, Tyler S. ;
Kurra, Narendra ;
Wang, Xuehang ;
Pinto, David ;
Simon, Patrice ;
Gogotsi, Yury .
ADVANCED ENERGY MATERIALS, 2019, 9 (39)
[10]   The defect of the Grey Wolf optimization algorithm and its verification method [J].
Niu, Peifeng ;
Niu, Songpeng ;
Liu, Nan ;
Chang, Lingfang .
KNOWLEDGE-BASED SYSTEMS, 2019, 171 :37-43