Economic optimal operation strategy for microgrids based on energy storage batteries and diesel generators

Abstract

Abstract: To improve the economic benefits of islanded microgrid with wind turbine, photovoltaic, diesel, and energy storage, an economic optimal operation strategy based on the dynamic alternate operation of two master power supplies, namely, the energy storage battery and the diesel generator, was proposed. First, based on the basic data such as renewable energy output forecast and load demand forecast, a reasonable operating mode is selected. A goal of minimizing the comprehensive operation cost of the system is established, incorporating factors such as fuel consumption cost, system operation and maintenance cost, and so on. Second, an economic operation optimization model for islanded microgrid is constructed, considering power balance constraints, and the distributed generation unit operation constraints. A model solution scheme based on the bald eagle search (BES) algorithm is proposed. Finally, the effectiveness of the optimal operation strategy proposed in this paper is verified by a case study, which can improve the economic benefits of the microgrid systems to a certain extent.

Key words: microgrid, operation strategy, economic optimization, bald eagle search algorithm

CLC Number:

TM73

LI Zhan-ming, WANG Ni-er. Economic optimal operation strategy for microgrids based on energy storage batteries and diesel generators[J]. Journal of Lanzhou University of Technology, 2025, 51(4): 72-80.

References

[1] 李晖,刘栋,姚丹阳.面向碳达峰碳中和目标的我国电力系统发展研判[J].中国电机工程学报,2021,41(18):6245-6259.
[2] 吕海鹏,希望·阿不都瓦依提,孟令鹏.计及源-荷预测不确定性的微电网双级随机优化调度[J].电力自动化设备,2022,42(9):70-78.
[3] 米师农,张建成,郭伟.基于改进FPA算法的互联微电网优化调度模型[J].高电压技术,2019,45(9):2849-2856.
[4] LOGENTHIRAN T,SRINIVASAN D,KHAMBADKONE A M.Multi-agent system for energy resource scheduling of integrated microgrids in a distributed system[J]. Electric Power Systems Research,2011,81(1):138-148.
[5] 赵鹏杰,吴俊勇,王燚.基于深度强化学习的微电网优化运行策略[J].电力自动化设备,2022,42(11):9-16.
[6] 赵波,李得民,吴在军,等.基于100%绿色能源供电目标的海岛微电网群容量优化配置[J].中国电机工程学报,2021,41(3):932-946.
[7] TORKAN R,ILINCA A,GHORBANZADEH M.A genetic algorithm optimization approach for smart energy management of microgrids[J].Renewable Energy,2022,197:852-863.
[8] 陈寒,唐忠,鲁家阳,等.基于CVaR量化不确定性的微电网优化调度研究[J].电力系统保护与控制,2021,49(5):105-115.
[9] PHOMMIXAY S,DOUMBIA M L,CUI Q S.Comparative analysis of continuous and hybrid binary-continuous particle swarm optimization for optimal economic operation of a microgrid[J].Process Integration and Optimization for Sustainability,2022,6:93-111.
[10] PROVATA E,KOLOKOTSA D,PAPANTONIOU,et al.Development of optimization algorithms for the Leaf Community microgrid[J].Renewable Energy,2015,74:782-795.
[11] 陈健,王成山,赵波,等.考虑储能系统特性的独立微电网系统经济运行优化[J].电力系统自动化,2012,36(20):25-31.
[12] 周永智,吴浩,李怡宁,等.基于MCS-PSO算法的邻近海岛多微网动态调度[J].电力系统自动化,2014,38(9):204-210.
[13] 刘畅,卓建坤,赵东明,等.利用储能系统实现可再生能源微电网灵活安全运行的研究综述[J].中国电机工程学报,2020,40(1):1-18.
[14] 李恒杰,巩旭,陈伟,等.基于改进粒子群算法的含电动汽车的微电网经济调度[J].兰州理工大学学报,2019,45(2):97-102.
[15] 米阳,李战强,吴彦伟,等.基于两级需求响应的并网微电网双层优化调度[J].电网技术,2018,42(6):1899-1906.
[16] 崔杨,刘柏岩,仲悟之,等.考虑积压惩罚机制的含BSS微网联合系统优化调度策略[J].电网技术,2020,44(10):3787-3793.
[17] FATHY A,REZK H,YOUSRI D,et al.Real-time bald eagle search approach for tracking the maximum generated power of wind energy conversion system[J].Energy,2022,249:123611.
[18] 肖浩,裴玮,孔力,等.考虑光伏余电上网的微网出力决策分析及经济效益评估[J].电力系统自动化,2014,38(10):10-16.