Optimization configuration method of distributed photovoltaic energy storage systems based on NSGA-Ⅲ algorithm

doi:10.3969/j.issn.2097-0706.2025.01.004

Abstract

Abstract:

Under the context of the "dual high" scenario in the power system，where both high renewable energy penetration and rapid growth coexist，challenges arise for the stability of the distribution network. Research into the optimization and configuration of energy storage is crucial for improving the consumption capacity of distributed photovoltaic energy and ensuring the economic and reliable operation of the distribution network. To address the voltage support requirements and economic operation needs of the distribution network，a bi-level multi-objective optimization configuration method for distributed energy storage based on the NSGA-Ⅲ algorithm was proposed. In the outer-layer sitting and sizing model，the location and capacity of distributed energy storage were treated as decision variables，considering total energy storage costs，voltage deviation in the distribution network，and load fluctuations，to improve voltage stability and economic performance. In the inner-layer operational optimization model，the charge/discharge state of the energy storage system was the decision variable，considering the operational revenue after energy storage installation，to improve economic efficiency. The voltage stability index（VSI）was used to identify weak voltage nodes in the system as potential pre-siting nodes to improve solution efficiency. Case study analysis showed that the proposed energy storage configuration scheme and operation optimization strategy can achieve optimal energy storage investment benefits，effectively improve grid voltage quality and power stability，and enhance the operation level of the distribution network.

Key words: renewable energy, distributed energy storage, distribution network, bi-level optimization configuration model, NSGA-Ⅲ algorithm, voltage stability index, pre-siting

CLC Number:

TK01

XU Qiang. Optimization configuration method of distributed photovoltaic energy storage systems based on NSGA-Ⅲ algorithm[J]. Integrated Intelligent Energy, 2025, 47(1): 26-33.

Figures/Tables 7

Fig.1

Fig.2

Table 1

Simulation parameter settings

参数		数值
储能SOC参数	$S O C m i n$ ， $S O C m a x$	0.1，0.9
	η_cha，η_dis/%	95
	ρ/%	6.33
	μ/%	20
储能成本参数	C_INV/（美元·台^-1）	1×10⁶
储能成本参数	a/（美元·MW^-1）	1.37×10⁸

Table 1

Fig.3

Table 2

Fig.4

Fig.5

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方案	储能优化配置方案			内层优化结果C_R/元	外层优化结果
方案	位置节点	容量/（MW·h）	功率/MW	内层优化结果C_R/元	F₁/元	F₂（标幺值）	F₃/MW
1 2 3	（5，32）（5，29）	（0.762，0.509）（0.678，0.402）	（0.262，0.126）（0.122，0.045）	2.53×10⁵ 8.41×10⁵ 2.15×10⁶	1.6×10⁶ 1.2×10⁶ 6.9×10⁵	0.844 0.712 0.538	134.2 112.2 110.6