基于启发式算法的含BESS配电网线损最小化策略研究

doi:10.19799/j.cnki.2095-4239.2023.0511

储能科学与技术 ›› 2023, Vol. 12 ›› Issue (11): 3406-3413.doi: 10.19799/j.cnki.2095-4239.2023.0511

基于启发式算法的含BESS配电网线损最小化策略研究

邢子涯¹(), 刘玮¹, 耿俊成¹, 周兴华², 夏越³()

^1.国网河南省电力公司电力科学研究院，河南郑州 450052
^2.北京中恒博瑞数字电力科技有限公司，北京 100085
^3.中国农业大学信息与电气工程学院，北京 100083

收稿日期:2023-07-28 修回日期:2023-08-22 出版日期:2023-11-05 发布日期:2023-11-16
通讯作者: 夏越 E-mail:liuwenjuan@hzzh.com;yue.xia@cau.edu.cn
作者简介:邢子涯（1983—），男，硕士，高级工程师，从事电力数字化技术应用研究，E-mail：liuwenjuan@hzzh.com；
基金资助:
国家重点研发计划(2022YFE0105200)

Line-loss minimization strategy of a distribution network with battery energy storage systems based on heuristic algorithm

Ziya XING¹(), Wei LIU¹, Juncheng GENG¹, Xinghua ZHOU², Yue XIA³()

^1.State Grid Henan Electric Power Research Institute, Zhengzhou 450052, Henan, China
^2.Beijing Join Bright Digital Power Technology Co. , Ltd. , Beijing 100085, China
^3.College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China

Received:2023-07-28 Revised:2023-08-22 Online:2023-11-05 Published:2023-11-16
Contact: Yue XIA E-mail:liuwenjuan@hzzh.com;yue.xia@cau.edu.cn

摘要/Abstract

摘要：

分布式能源大规模并网加剧了电力系统的不确定性、波动性和随机性。本文提出了一种基于模拟退火(simulated annealing，SA)的启发式算法，以及结合了建筑能源模拟Energy Plus软件/模拟配网的Matpower软件的协同仿真框架，实现了配电网负载均衡和损耗最小化问题的公式化，在配网层面研究了应对线路故障(如断线)的负荷均衡和功率损耗最小化策略。基于需求响应(demand response，DR)信号实现了分布式用户的电池储能系统(battery energy storage systems，BESS)的合理调度。本工作采用一个9节点网络进行仿真验证，并赋予模型不同权重系数。研究结果表明，所提算法对分布式能源接入配电网的负载均衡和线损最小化具有准确性和可拓展性，研究结果对分布式能源接入配电网有重要的现实意义。

关键词: 分布式能源, 启发式算法, 电池储能系统, 线损

Abstract:

The large-scale integration of distributed energy aggravates the uncertainty, volatility, and randomness of the power system. This study proposes a heuristic algorithm based on simulated annealing and a collaborative simulation framework that combines building-energy simulation with Energy Plus/Matpower software simulating distribution network to realize the formulation of load balancing and loss minimization in the distribution network. The load-balancing and power-loss minimization strategies used for solving line faults (such as disconnection) are studied at the distribution network level. Based on the demand response signal, this study realizes reasonable scheduling of battery energy storage systems for distributed users. Finally, based on a nine-node network, the accuracy and scalability of the proposed algorithm for load balancing and line-loss minimization of the distributed energy-access distribution network are analyzed by simulating and verifying the model with different weight coefficients. The research results have important practical significance for distributed energy-access distribution network.

Key words: distributed energy source, heuristic algorithm, battery energy storage systems, line loss

中图分类号:

TM 911

邢子涯, 刘玮, 耿俊成, 周兴华, 夏越. 基于启发式算法的含BESS配电网线损最小化策略研究[J]. 储能科学与技术, 2023, 12(11): 3406-3413.

Ziya XING, Wei LIU, Juncheng GENG, Xinghua ZHOU, Yue XIA. Line-loss minimization strategy of a distribution network with battery energy storage systems based on heuristic algorithm[J]. Energy Storage Science and Technology, 2023, 12(11): 3406-3413.

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用户状态	负荷调整比例	节点动作
充电	101%～200%	增加节点负荷
平衡	100%	保持节点负荷
放电	0～99%	减少节点负荷

节点	负荷平衡 α =1	损耗最小 α =0	综合 α =0.5
2	0	0	0
3	50	0	20
4	80	160	100
5	200	130	50
6	100	110	130
7	190	70	180
8	40	20	90
9	180	0	60

参数	公式	α	基值	断线	最优解	差值
LP	16	0	0.72	1	0.06	-0.94
C_b	15		0.03	1	0.24	-0.76
Obj_cos_t	17		0.72	1	0.06	-0.94
LP	16	1	0.7	1	0.28	-0.72
C_b	15		0.03	1	0.26	-0.74
Obj_cos_t	17		0.03	1	0.26	-0.74
LP	16	0.5	0.7	1	0.1	-0.9
C_b	15		0.03	1	0.3	-0.7
Obj_cos_t	17		0.36	1	0.2	-0.8

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基于启发式算法的含BESS配电网线损最小化策略研究

Line-loss minimization strategy of a distribution network with battery energy storage systems based on heuristic algorithm

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参考文献 13

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节点	负荷平衡 α =1	损耗最小 α =0	综合 α =0.5
2	0	0	0
3	50	0	20
4	80	160	100
5	200	130	50
6	100	110	130
7	190	70	180
8	40	20	90
9	180	0	60

节点	负荷平衡 α =1	损耗最小 α =0	综合 α =0.5
2	0	0	0
3	50	0	20
4	80	160	100
5	200	130	50
6	100	110	130
7	190	70	180
8	40	20	90
9	180	0	60

节点	负荷平衡 α =1	损耗最小 α =0	综合 α =0.5
2	0	0	0
3	50	0	20
4	80	160	100
5	200	130	50
6	100	110	130
7	190	70	180
8	40	20	90
9	180	0	60