基于多目标双层优化的台区分布式电源选址定容方法

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基于多目标双层优化的台区分布式电源选址定容方法

Siting and Sizing of Distributed Generation in Distribution Transformer Areas Using Multi-objective Bi-level Optimization

基于多目标双层优化的台区分布式电源选址定容方法

Siting and Sizing of Distributed Generation in Distribution Transformer Areas Using Multi-objective Bi-level Optimization

基于多目标双层优化的台区分布式电源选址定容方法

Siting and Sizing of Distributed Generation in Distribution Transformer Areas Using Multi-objective Bi-level Optimization

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doi:10.11930/j.issn.1004-9649.202505080

中国电力 ›› 2025, Vol. 58 ›› Issue (10): 136-146.DOI: 10.11930/j.issn.1004-9649.202505080

• 低碳高可靠配电网的灵活运行与规划 • 上一篇下一篇

王德顺¹(), 雷洁¹(), 胡安平¹(), 王冰², 冯鑫振¹, 王志辉²

1. 国网上海能源互联网研究院有限公司，江苏南京　210003
2. 国网河北省电力有限公司，河北石家庄　050022

收稿日期:2025-05-08 发布日期:2025-10-23 出版日期:2025-10-28
作者简介:
王德顺（1982），男，硕士，高级工程师（教授级），从事新能源与储能技术研究，E-mail：wangdeshun@epri.sgcc.com.cn
雷洁（1995），女，通信作者，硕士，工程师，从事新能源与储能技术研究，E-mail：leijie@epri.sgcc.com.cn
胡安平（1985），男，博士，高级工程师（教授级），从事新能源与储能技术研究，E-mail：huanping@epri.sgcc.com.cn
基金资助:
国家电网有限公司科技项目（低压分布式光伏分层分级调控及消纳关键技术研究及应用，5400-202313567A-3-2-ZN）。

WANG Deshun¹(), LEI Jie¹(), HU Anping¹(), WANG Bing², FENG Xinzhen¹, WANG Zhihui²

1. State Grid Shanghai Energy Internet Research Institute Co., Ltd., Nanjing 210003, China
2. State Grid Hebei Electric Power Co., Ltd., Shijiazhuang 050022, China

Received:2025-05-08 Online:2025-10-23 Published:2025-10-28
Supported by:
This work is supported by Science and Technology Project of SGCC (Research and Application of Key Technologies for Hierarchical Control and Consumption in Low-Voltage Distributed Photovoltaic Systems, No.5400-202313567A-3-2-ZN).

摘要：

近年来，随着国家能源局“整县推进”屋顶光伏开发政策的持续推进，中国分布式光伏接入规模持续扩大，提升了可再生能源利用率。但是，低压配电网末端接入的大量光伏用户引发了局部电压越限和网损异常等问题，降低了系统的运行安全性，且经济性较低。针对以上问题，提出一种基于二阶锥规划松弛的分布式电源选址定容双层优化配置方法。首先，兼顾系统运行安全性与经济性，在考虑分布式储能老化、维护成本及运行安全等因素的基础上，构建以系统日综合运行成本最低和光伏利用率最高为目标的双层优化模型；然后，使用二阶锥规划松弛技术转换潮流模型，将原有非凸模型转换为凸模型以降低运算规模，并使用多目标粒子群算法求解模型；最后，以改进的IEEE 33节点及河北实际台区为算例，与传统规划方法对比，验证所提方法优越性。结果表明，所提方法能在保证经济性的同时，提高电能质量并降低网损，增加分布式光伏消纳能力。

关键词: 分布式电源, 电压越限, 二阶锥规划, 多目标双层优化, 分布式光伏

Abstract:

In recent years, with the continuous implementation of the "county-wide rooftop distributed photovoltaic (DPV) development program" promoted by the National Energy Administration, the integration scale of PV in China has steadily expanded, enhancing the utilization efficiency of renewable energy. However, the large-scale integration of PV users, particularly at the ends of low-voltage distribution networks. has led to issues such as localized voltage violations and abnormal power losses, thereby compromising power system's operational security and economic efficiency. To address the aforementioned issues, this paper proposes a bi-level optimal allocation method for distributed generation siting and sizing based on second-order cone programming relaxation. Firstly, to balance system's operational security and economic efficiency, a bi-level optimization model is established with the dual objectives of minimizing the system's daily comprehensive operating cost and maximizing PV utilization, which takes account such factors as the aging, maintenance costs and operational safety of distributed energy storage systems. Then, the second-order cone programming relaxation technique is employed to transform the power flow model, converting the original non-convex model into a convex one to reduce computational complexity, and the multi-objective particle swarm optimization algorithm is used to solve the model. Finally, using the improved IEEE 33-bus system and an actual distribution network in Hebei for case study, a comparison with the traditional planning approaches is conducted to verify the superiority of the proposed method. The results indicate that the proposed method can enhance power quality, reduce network losses, and increase the DPV hosting capacity while ensuring economic efficiency of distribution networks.

Key words: distributed generation, voltage violation, second-order cone programming, multi-objective bi-level optimization, distributed photovoltaic

王德顺, 雷洁, 胡安平, 王冰, 冯鑫振, 王志辉. 基于多目标双层优化的台区分布式电源选址定容方法[J]. 中国电力, 2025, 58(10): 136-146.

WANG Deshun, LEI Jie, HU Anping, WANG Bing, FENG Xinzhen, WANG Zhihui. Siting and Sizing of Distributed Generation in Distribution Transformer Areas Using Multi-objective Bi-level Optimization[J]. Electric Power, 2025, 58(10): 136-146.

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链接本文: https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.202505080

https://www.electricpower.com.cn/CN/Y2025/V58/I10/136

图 1 DERs选址定容模型框架

Fig.1 Model framework for DERs siting and sizing

图 2 支路等效电路模型

Fig.2 Branch equivalent circuit model

图 3 双层模型求解流程

Fig.3 Bi-level model solution flowchart

图 4 源-荷典型场景

Fig.4 Typical source-load scenario

图 5 IEEE 33节点网络拓扑

Fig.5 IEEE 33-bus network topology

图 6 渗透率对节点电压的影响

Fig.6 The impact of penetration rate on node voltage

图 7 多种渗透率对电压的影响

Fig.7 The impact of penetration rate on node voltage

图 8 并网节点对电压的影响

Fig.8 The impact of grid-connected nodes on voltage

表 1 台区A的DPV最优配置结果

Table 1 Optimal DPV configuration results for distribution transformer area A

方案	接入节点	配置容量/kW	经济成本/元	光伏利用率/%
一	2，8，16，32，20	40，60，60，70，40	192	73.3
二	2，6，15，21，31	50，50，70，60，40	189	74.9

图 9 各支路网损对比

Fig.9 Changes in branch network losses before and after DPV integration

图 10 DPV接入前后各节点电压变化

Fig.10 Changes in bus voltages before and after DPV integration

表 2 DES最优配置结果

Table 2 Optimal configuration results of DES

表 3 DES规划指标

Table 3 DES Planning Indicators

方案	日均成本/元	线损率/%	光伏利用率/%	电压合格率/%
一	67.19	0.87	88.6	100
二	62.99	0.75	89.3	100

图 11 A台区拓扑分布

Fig.11 Topology distribution of Area A

图 12 B台区拓扑分布

Fig.12 Topology distribution of Area B

表 4 规划前的A、B台区基本信息

Table 4 Basic information of distribution transformer areas A and B before planning

台区	光伏利用率/%	线损率/%	电压合格率/%
A	71.1	3.92	79.17
B	65.9	9.32	6.94

图 13 储能规划前光伏大发日的台区电压分布

Fig.13 Voltage distribution of distribution transformer areas on a PV peak generation day before energy storage planning

表 5 A、B台区DES最优配置结果

Table 5 Optimal configuration results of DES for distribution transformer areas A and B

台区	接入节点	配置容量/(kV·A)
A	6，10，12	50，70，10
B	5，12，17，22，27	30，50，50，20，50

表 6 A、B台区DES规划指标

Table 6 DES planning indicators for distribution transformer areas A and B

台区	日均投资成本/元	日均运行维护成本/元	线损率/ %	光伏利用率/%	电压合格率/%
A	48.59	5.31	1.26	82.1	100
B	74.75	9.48	3.72	79.5	100

1	陈维江, 靳晓凌, 吴鸣, 等. 双碳目标下我国配电网形态快速演进的思考[J]. 中国电机工程学报, 2024, 44 (17): 6811- 6818.
	CHEN Weijiang, JIN Xiaoling, WU Ming, et al. Thinking on the rapid evolution of distribution network form under the carbon peaking and carbon neutrality goals[J]. Proceedings of the CSEE, 2024, 44 (17): 6811- 6818.
2	王雯沁, 高红均, 王仁浚, 等. 考虑分布式电源支撑与农业设施协调的配电网分布鲁棒优化[J]. 电力系统自动化, 2023, 47 (21): 89- 98. DOI
	WANG Wenqin, GAO Hongjun, WANG Renjun, et al. Distributionally robust optimization of distribution network considering distributed generator support and agricultural facility coordination[J]. Automation of Electric Power Systems, 2023, 47 (21): 89- 98. DOI
3	魏旭, 刘东, 高飞, 等. 双碳目标下考虑源网荷储协同优化运行的新型电力系统发电规划[J]. 电网技术, 2023, 47 (9): 3648- 3661.
	WEI Xu, LIU Dong, GAO Fei, et al. Generation expansion planning of new power system considering collaborative optimal operation of source-grid-load-storage under carbon peaking and carbon neutrality[J]. Power System Technology, 2023, 47 (9): 3648- 3661.
4	郑亚先, 杨争林, 冯树海, 等. 碳达峰目标场景下全国统一电力市场关键问题分析[J]. 电网技术, 2022, 46 (1): 1- 20.
	ZHENG Yaxian, YANG Zhenglin, FENG Shuhai, et al. Key issue analysis in national unified power market under target scenario of carbon emission peak[J]. Power System Technology, 2022, 46 (1): 1- 20.
5	张宇, 魏新迟, 冯凯辉, 等. 计及分布式光伏承载力的配电网侧独立储能充放电策略[J]. 中国电力, 2024, 57 (4): 111- 117. DOI
	ZHANG Yu, WEI Xinchi, FENG Kaihui, et al. Charging and discharging strategies of independent energy storage for distribution grid side considering distributed PV carrying capacity[J]. Electric Power, 2024, 57 (4): 111- 117. DOI
6	MONTOYA O D, GRISALES-NOREÑA L F, GIL-GONZÁLEZ W. Simultaneous siting and sizing of PVs and D-STATCOMs in medium-voltage grids using the Cauchy-based distribution optimizer[J]. Results in Engineering, 2025, 25, 104407. DOI
7	欧奕昊, 姜彤, 张一航, 等. 考虑变流器无功调节特性的含高比例分布式光伏配电网电压控制方法[J]. 电力系统保护与控制, 2024, 52 (20): 105- 118.
	OU Yihao, JIANG Tong, ZHANG Yihang, et al. Voltage regulation method for a distribution network with high-penetration of distributed photovoltaic energy considering a converter's reactive power regulation characteristics[J]. Power System Protection and Control, 2024, 52 (20): 105- 118.
8	张颖, 寇凌峰, 季宇, 等. 计及储能与分布式电源协同的配电网分层分区优化控制[J]. 中国电力, 2021, 54 (2): 104- 112. DOI
	ZHANG Ying, KOU Lingfeng, JI Yu, et al. Hierarchical and partitioned optimal control of distribution networks considering the coordination between energy storage and distributed generation systems[J]. Electric Power, 2021, 54 (2): 104- 112. DOI
9	SUN W T, GE Y, LIU G J, et al. Siting and sizing method of GFM converters based on genetic algorithm[J]. Inventions, 2025, 10 (1): 13. DOI
10	陈众, 徐翼, 吴辅朝, 等. 基于光伏消纳能力模拟评估的配电网最优消纳方案规划选择[J]. 电网技术, 2023, 47 (3): 1179- 1188.
	CHEN Zhong, XU Yi, WU Fuchao, et al. Selection of optimal distribution planning based on simulation of photovoltaic absorption capacity[J]. Power System Technology, 2023, 47 (3): 1179- 1188.
11	尚博阳, 许寅, 王颖, 等. 参与辅助服务的用户侧储能优化配置及经济分析[J]. 中国电力, 2023, 56 (2): 164- 170, 178. DOI
	SHANG Boyang, XU Yin, WANG Ying, et al. Optimal configuration and economic analysis of user-side energy storage participating in auxiliary services[J]. Electric Power, 2023, 56 (2): 164- 170, 178. DOI
12	唐雅洁, 李俊豪, 林达, 等. 考虑分布式光伏高效消纳与负荷损失最小的区域配电网应急资源协同配置策略[J]. 电力自动化设备, 2024, 44 (7): 78- 85.
	TANG Yajie, LI Junhao, LIN Da, et al. Coordinated allocation strategy of emergency resource for regional distribution network considering distributed photovoltaic efficient absorption and minimum load loss[J]. Electric Power Automation Equipment, 2024, 44 (7): 78- 85.
13	陈韵含, 许寅, 王颖, 等. 考虑潜在恢复需求的城市配电网移动应急资源灾前布点[J]. 电力系统自动化, 2023, 47 (14): 105- 113. DOI
	CHEN Yunhan, XU Yin, WANG Ying, et al. Pre-disaster positioning of mobile emergency resources for urban distribution network considering potential restoration demand[J]. Automation of Electric Power Systems, 2023, 47 (14): 105- 113. DOI
14	白望望, 杨德州, 李万伟, 等. 基于HC-MOPSO的储能电站两阶段选址定容方法[J]. 中国电力, 2024, 57 (12): 148- 156. DOI
	BAI Wangwang, YANG Dezhou, LI Wanwei, et al. A two-stage site selection and capacity determination method for energy storage power stations based on HC-MOPSO[J]. Electric Power, 2024, 57 (12): 148- 156. DOI
15	王枭, 何怡刚, 马恒瑞, 等. 考虑规模化储能的配电网电压分布式控制[J]. 电力自动化设备, 2022, 42 (2): 25- 30, 55.
	WANG Xiao, HE Yigang, MA Hengrui, et al. Distributed voltage control of distribution network considering large-scale energy storage[J]. Electric Power Automation Equipment, 2022, 42 (2): 25- 30, 55.
16	CHATZIGEORGIOU N G, THEOCHARIDES S, MAKRIDES G, et al. A review on battery energy storage systems: Applications, developments, and research trends of hybrid installations in the end-user sector[J]. Journal of Energy Storage, 2024, 86, 111192. DOI
17	陈奇芳, 李若凡, 夏明超, 等. 计及多维性能评估的新型配电网光伏选址定容方法[J]. 中国电力, 2024, 57 (10): 172- 178, 207. DOI
	CHEN Qifang, LI Ruofan, XIA Mingchao, et al. Photovoltaic site selection and capacity determination method for new distribution network considering multidimensional performance evaluation[J]. Electric Power, 2024, 57 (10): 172- 178, 207. DOI
18	庞广明, 王鹏飞, 田超, 等. 基于ICOA算法的配电网分布式电源选址定容方法[J]. 太阳能学报, 2024, 45 (10): 211- 219.
	PANG Guangming, WANG Pengfei, TIAN Chao, et al. Location and capacity determination method of distributed generation in distribution network based on icoa algorithm[J]. Acta Energiae Solaris Sinica, 2024, 45 (10): 211- 219.
19	TIAN Z, LI X Y, NIU J D, et al. Enhancing operation flexibility of distributed energy systems: a flexible multi-objective optimization planning method considering long-term and temporary objectives[J]. Energy, 2024, 288, 129612. DOI
20	张振芳, 撖奥洋, 刘同同, 等. 基于多策略改进SSA算法的分布式光伏选址定容规划[J]. 电气工程学报, 2024, 19 (4): 347- 356.
	ZHANG Zhenfang, HAN Aoyang, LIU Tongtong, et al. Optimal sizing and siting of distributed PV based on multi-strategy improved SSA algorithm[J]. Journal of Electrical Engineering, 2024, 19 (4): 347- 356.
21	胡泽春, 蔡福霖, 冯建洲. 兼顾新能源消纳与频率电压支撑的电池储能系统优化规划[J]. 电力自动化设备, 2024, 44 (7): 3- 12.
	HU Zechun, CAI Fulin, FENG Jianzhou. Optimal planning of battery energy storage system considering renewable energy consumption and frequency and voltage support[J]. Electric Power Automation Equipment, 2024, 44 (7): 3- 12.
22	安东, 杨德宇, 武文丽, 等. 基于改进多目标蜉蝣算法的配网电池储能系统最优选址定容[J]. 电力系统保护与控制, 2022, 50 (10): 31- 39.
	AN Dong, YANG Deyu, WU Wenli, et al. Optimal location and sizing of battery energy storage systems in a distribution network based on a modified multi-objective mayfly algorithm[J]. Power System Protection and Control, 2022, 50 (10): 31- 39.
23	TWAISAN K, BARıŞÇı N. Integrated distributed energy resources (DER) and microgrids: modeling and optimization of DERs[J]. Electronics, 2022, 11 (18): 2816. DOI
24	杨博, 俞磊, 王俊婷, 等. 基于自适应蝠鲼觅食优化算法的分布式电源选址定容[J]. 上海交通大学学报, 2021, 55 (12): 1673- 1688.
	YANG Bo, YU Lei, WANG Junting, et al. Optimal sizing and placement of distributed generation based on adaptive manta ray foraging optimization[J]. Journal of Shanghai Jiao Tong University, 2021, 55 (12): 1673- 1688.
25	林国灏, 唐巍, 文钥棋. 基于多智能体的中低压交直流混合配电网优化调度[J]. 供用电, 2024, 41 (9): 2- 11.
	LIN Guohao, TANG Wei, WEN Yueqi. Optimal scheduling method of medium and low voltage AC/DC hybrid distribution network based on multi-agent[J]. Distribution & Utilization, 2024, 41 (9): 2- 11.
26	吴璐阳, 辛洁晴, 王承民. 计入用户从众心理的分布式光伏装机容量预测[J]. 电力系统自动化, 2022, 46 (14): 83- 92. DOI
	WU Luyang, XIN Jieqing, WANG Chengmin. Installed capacity forecasting for distributed photovoltaic considering herd mentality of users[J]. Automation of Electric Power Systems, 2022, 46 (14): 83- 92. DOI
27	GIANNELOS S, ZHANG T, PUDJIANTO D, et al. Investments in electricity distribution grids: strategic versus incremental planning[J]. Energies, 2024, 17 (11): 2724. DOI
28	陈娟, 高江梅. 基于演化博弈的户用光伏整县开发协同机制及仿真[J]. 电网技术, 2023, 47 (2): 669- 684.
	CHEN Juan, GAO Jiangmei. Coordination mechanism and simulation of household photovoltaic county development based on evolutionary game[J]. Power System Technology, 2023, 47 (2): 669- 684.
29	曹振其, 彭敏放, 沈美娥. 考虑源荷不确定性的分布式电源选址定容[J]. 电力系统及其自动化学报, 2021, 33 (2): 59- 65.
	CAO Zhenqi, PENG Minfang, SHEN Meie. Siting and sizing of distributed generations considering uncertainties in source and load[J]. Proceedings of the CSU-EPSA, 2021, 33 (2): 59- 65.

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[12]	凡鹏飞, 李宝琴, 侯江伟, 李嵘, 宋崇明, 林凯骏. 配电网分布式电源经济可承载力评估[J]. 中国电力, 2024, 57(7): 196-202.
[13]	王家武, 赵佃云, 刘长锋, 陈康, 张玉敏. 基于目标级联法的多主体主动配电网自治协同优化[J]. 中国电力, 2024, 57(7): 214-226.
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[15]	刘韵艺, 汤渊, 苏盛, 吴裕宙, 王晓倩. 基于STL-Bayesian时空模型的分布式光伏系统异常检测[J]. 中国电力, 2024, 57(5): 222-231.

配置容量/(kW·h)

配置容量/(kW·h)