Research on the optimal allocation of energy storage in distribution network based on multi-objective particle swarm optimization algorithm

doi:10.3969/j.issn.2097-0706.2023.06.002

Abstract

Abstract:

The energy storage technology has the ability to adjust power and the time of energy，so as to effectively improve the output characteristics and shedulability of renewable energy. Thus， it is important to study the energy storage optimized configurations under different scenarios.Taking the technical and economic indicators into consideration comprehensively， an energy storage allocation method based on multi-objective particle swarm optimization（MOPSO）algorithm is proposed. The multi-objective energy storage configuration model can be solved by MOPSO， and the adaptive mutation strategy is introduced in the population updating process to improve the exploration capability of particles and ensure the population diversity and the late convergence. The global optimal solution for energy storage comprehensively optimizes the technical and economic indicators. The feasibility and superiority of the proposed method are verified by Matlab simulation， and the research results have theoretical and engineering value for the optimal configurations of energy storage systems in distribution network.

Key words: distribution network, optimal configuration of energy storage, multi-objective particle swarm optimization, new power system, renewable energy, large-scale grid connection, carbon neutrality

CLC Number:

TK01：TM715

LIU Ziqi, SU Tingting, HE Jiayang, WANG Yu. Research on the optimal allocation of energy storage in distribution network based on multi-objective particle swarm optimization algorithm[J]. Integrated Intelligent Energy, 2023, 45(6): 9-16.

Figures/Tables 10

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参数及变量	取值
最大迭代次数/次	50
种群规模/个	50
档案库规模/个	200
惯性权重范围	0.5~0.9
储能电量（SOC）范围/%	20~90
充放电效率η/%	90
学习因子c₁, c₂	1.7,1.8
储能单位功率成本α/(万元·MW^-1)	0.12
储能单位容量成本β/(万元·MW^-1)	0.18
储能年运维成本C_y/(万元·MW^-1)	5

场景	储能接入位置及容量/(MW·h)	f₁	f₂/万元	f₃/MW
1	—	1.083 6	—	1.706 9
2	10(0.987 3)，12(1.104 5)	1.165 6	0.903 1	1.580 2
	10(0.965 5)，14(0.940 7)	1.158 6	0.879 3	1.601 0
	12(1.011 5)，14(1.114 8)	1.150 5	0.840 9	1.617 0
	平均值	1.158 2	0.874 4	1.599 4
3	10(0.941 9)，12(1.051 5)	1.235 0	0.844 5	1.499 7
	10(0.911 0)，14(0.897 2)	1.220 6	0.821 2	1.501 0
	12(0.971 3)，14(1.069 6)	1.219 0	0.799 6	1.528 6
	平均值	1.224 9	0.821 8	1.509 8