基于改进多目标粒子群算法的储能电站定容选址优化配置研究

doi:10.19799/j.cnki.2095-4239.2023.0689

摘要/Abstract

摘要：

电化学储能电站在高比例新能源电网中逐步得到了规模化应用，其优化配置策略很大程度上决定了其辅助电网调频调压的效果。为实现电化学储能电站的最优化配置，首先研究了高比例新能源下储能参与电力系统调频调压的控制策略，提出了基于变系数有功无功下垂控制方法。随后，建立了高比例新能源电网下储能系统参与电网调频调压的多目标优化配置模型。该模型以调频综合指标、调压综合指标和系统成本为优化目标，采用了改进型多目标粒子群算法对控制参数配置和储能系统选址定容结果进行优化配置。为避免数据的主观性，采用熵权法对所得到的多目标解集选出最优方案。最后，采用某市区域电网实际算例对储能进行优化配置，区域电网调压综合指标降低了9.2%，调频综合指标降低了25.1%，区域电网节点电压偏差和频率偏差均显著降低，调压和调频效果得到了提升，验证了本文所提出储能定容选址配置方法的有效性和优越性。

关键词: 储能, 高比例新能源, 多目标, 优化配置

Abstract:

The electrochemical energy storage power station has been gradually applied on a large scale in a high proportion of the new energy power grid, and its optimal configuration strategy largely determines the effectiveness of frequency and voltage regulation in its auxiliary power grid. To realize the optimal configuration of the electrochemical energy storage power station, this study first examines the control strategy of energy storage participating in the frequency and voltage regulation of the power system under a high proportion of new energy. It proposes a control method based on the variable coefficient frequency-voltage sag. Then, the multi-objective optimal configuration model for the energy storage system participating in the frequency and voltage regulation of the power grid under a high proportion of the new energy grid is established. The model considers the comprehensive indices of frequency modulation, voltage regulation, and system cost as optimization objectives. The improved multi-objective particle swarm optimization algorithm is employed to optimize the configuration of control parameters and the location and capacity of the energy storage system. To address subjectivity in the data, the entropy weight method is used to select the optimal scheme from the obtained multi-objective solution set. Finally, a practical example of a regional power grid of a city is used to optimize the allocation of energy storage. The comprehensive indices of regional power grid voltage regulation and frequency modulation were reduced by 9.2% and 25.1%, respectively. The voltage and frequency deviation of regional power grid nodes was considerably reduced, improving the effect of voltage regulation and frequency modulation. This verifies the effectiveness and superiority of the proposed energy storage fixed capacity location allocation method.

Key words: energy storage, new energy with high proportion, multi-objective, optimized configuration

中图分类号:

TM 712

肖厦颖, 范传光, 郭峰, 杨天鑫, 王栋, 黄云辉. 基于改进多目标粒子群算法的储能电站定容选址优化配置研究[J]. 储能科学与技术, 2024, 13(2): 503-514.

Xiaying XIAO, Chuanguang FAN, Feng GUO, Tianxin YANG, Dong WANG, Yunhui HUANG. Optimal allocation of energy storage power station based on improved multi-objective particle swarm optimization[J]. Energy Storage Science and Technology, 2024, 13(2): 503-514.

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参数类型	取值	参数类型	取值
S_min	0.1	S₀	0.5
S_max	0.9	C_P /(元/MW)	150×10³
K_G /pu	12	C_E /(元/MWh)	250×10³
K_E /(MW/Hz)	10	K_M /(元/MWh)	70
∆f_{db_u} /Hz	-0.033	β	0.03
∆f_{db_h} /Hz	0.033	α_c /(元/MWh)	0.72
η_bc /%	90	α_f /(元/MWh)	0.314

典型解	储能1			储能2
典型解	位置	容量/MWh	额定功率/MW	位置	容量/MWh	额定功率/MW
最优解	4	0.81	2.18	39	1.6	2.03
边界解1	19	0.49	1.98	26	0.71	1.76
边界解2	4	2.9	2.51	31	0.79	1.96
边界解3	31	0.32	1.83	4	0.36	1.63

典型解	调压综合指标	频率偏差均方根值/Hz	储能净成本/元
最优解	0.240	0.0389	1256645
边界解1	0.238	0.0391	853679
边界解2	0.257	0.0382	1678087
边界解3	0.247	0.0394	778966

最优解编号	S_min	S_max	r	n
1	0.293	0.437	1656	18
2	0.318	0.639	2103	21
3	0.437	0.746	1663	11
平均值	0.349	0.607	1807	17

控制策略	调压综合指标	调频综合指标/Hz	储能经济指标/元
线性变系数控制策略	0.255	0.0407	1517846
本文所提控制策略	0.236	0.0383	1346561