基于数据驱动的高比例新能源配电网规划模型

doi:10.11930/j.issn.1004-9649.202405121

摘要/Abstract

摘要：

为应对电网形式的转变，促进分布式资源就近消纳，基于数据驱动提出了高比例新能源配电网3层规划模型。决策层采用改进的K-means算法确定负荷中心和分布式电源中心，基于源荷平衡关系划分配电网网格。规划层以综合投资成本最低为目标，对网格内分布式电源和网架结构的修建提出配置方案。运行层模型以综合运行成本最低为目标，促进网格内资源良好互动、网格间资源互济。3层规划模型结合配电网的规划和运行，充分挖掘电源、负荷等多源信息，实现配电网资源上多元联动、空间上网格互动，并通过改进的粒子群算法验证了所提策略的有效性。

关键词: 分布式资源, 数据驱动, 三层规划

Abstract:

In response to the transformation of the power grid form and to promote the local consumption of distributed resources, a three-layer planning model for highportion new energy distribution networks based on data-driven is proposed. The decision-making layer uses an improved K-means algorithm to determine the load center and the distributed power source, and divides the distribution network grid based on the source-load balance relationship. The planning layer aims to minimize the comprehensive investment cost and proposes a configuration scheme for the construction distributed power sources and the network structure within the grid. The operation layer model aims to minimize the comprehensive operation cost, promote the good interaction of resources within the grid, the mutual assistance of resources between grids. The three-layer planning model combines the planning and operation of the distribution network, fully mines multi-source information such as power sources and, and realizes multi-dimensional linkage of distribution network resources in the resource space and grid interaction in the spatial space. The effectiveness of the proposed strategy is verified through an improved swarm optimization algorithm.

Key words: distributed energy resource, data-driven, three-layer planning

王杰, 郑飞, 张鹏城, 陈露东, 高华, 蒙镜蓉. 基于数据驱动的高比例新能源配电网规划模型[J]. 中国电力, 2025, 58(3): 175-182.

Jie WANG, Fei ZHENG, Pengcheng ZHANG, Ludong CHEN, Hua GAO, Jingrong MENG. Model of High-Proportion New Energy Distribution Network Planning Based on Data-Driven Approach[J]. Electric Power, 2025, 58(3): 175-182.

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链接本文: https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.202405121

https://www.electricpower.com.cn/CN/Y2025/V58/I3/175

图/表 11

图 1 配电网格划分层次

Fig.1 Distribution grid division level

图 2 配电网格分层控制体系

Fig.2 Distribution grid hierarchical control system

图 3 新型配电网三层规划模型

Fig.3 Three-layer planning model of new distribution network

图 4 新型配电网3层规划模型求解流程

Fig.4 Solution flow of three-layer planning model for new distribution network

图 5 配电网网格划分结果

Fig.5 Distribution grid division results

图 6 典型日负荷和风光出力场景

Fig.6 Typical daily load and wind/PV output scene

表 1 配电网规划方案

Table 1 Distribution network planning scheme

类型		节点
风机		2;11;28
光伏		4;13;31
储能		3;12;30
燃气机组		21,24;8,17;27,32
燃料电池		19;9;26
修建线路		25-26;12-30

图 7 供电网格1典型日运行情况

Fig.7 Power grid 1 typical daily operation

图 8 供电网格2典型日运行情况

Fig.8 Power grid 2 typical daily operation

图 9 供电网格3典型日运行情况

Fig.9 Power grid 3 typical daily operation

图 10 不同方案规划结果对比

Fig.10 Comparison of planning results of different schemes

参考文献 23

1	祝士焱, 许寅, 和敬涵, 等. 基于多微电网投影的配电系统协调恢复方法[J]. 中国电力, 2024, 57 (9): 224- 230.
	ZHU Shiyan, XU Yin, HE Jinghan, et al. A restoration method for distribution system based on projection of multiple microgrids[J]. Electric Power, 2024, 57 (9): 224- 230.
2	周洋, 黄德志, 李培栋, 等. 考虑平衡端点相位不对称及光伏接入的低压配电网三相潮流模型[J]. 中国电力, 2024, 57 (10): 190- 198.
	ZHOU Yang, HUANG Dezhi, LI Peidong, et al. A three-phase power flow model for low-voltage distribution networks considering balanced bus phase asymmetry and photovoltaic access[J]. Electric Power, 2024, 57 (10): 190- 198.
3	龚俊祥, 徐有琳, 张菁, 等. 新型电力系统下配电网网络结构研究[J]. 山东电力技术, 2024, 51 (1): 45- 51.
	GONG Junxiang, XU Youlin, ZHANG Jing, et al. Research on the network structure of new power system distribution network[J]. Shandong Electric Power, 2024, 51 (1): 45- 51.
4	肖勇, 肖小兵, 金鑫, 等. 含储能和分布式光伏的配电网系统计及静态电压稳定性的多目标优化[J]. 广东电力, 2024, 37 (4): 24- 32. DOI
	XIAO Yong, XIAO Xiaobing, JIN Xin, et al. Multi-objective optimization of distribution network system with energy storage and distributed photovoltaic considering static voltage stability[J]. Guangdong Electric Power, 2024, 37 (4): 24- 32. DOI
5	张艳丽, 王争冕, 薛成, 等. 考虑新能源接入的配电网两阶段有功无功协调降损方法[J]. 电网与清洁能源, 2023, 39 (12): 121- 129. DOI
	ZHANG Yanli, WANG Zhengmian, XUE Cheng, et al. A two-stage active and reactive power coordinated loss reduction method for distribution networks integrated with new energy[J]. Power System and Clean Energy, 2023, 39 (12): 121- 129. DOI
6	刘志宏, 邵振通, 丛鹏, 等. 基于节点可靠性重要度评估的配网侧储能鲁棒规划方法[J]. 电网与清洁能源, 2023, 39 (2): 33- 39, 45. DOI
	LIU Zhihong, SHAO Zhentong, CONG Peng, et al. A robust planning method for distribution-level energy storage based on nodal reliability importance assessment[J]. Power System and Clean Energy, 2023, 39 (2): 33- 39, 45. DOI
7	黄四亮, 孟湛博, 邢晓敏, 等. 考虑灾前预防和灾时响应状态下的弹性配电网提升策略研究[J]. 东北电力大学学报, 2023, 43 (4): 82- 89.
	HUANG Siliang, MENG Zhanbo, XING Xiaomin, et al. Consider the research on the improvement strategy of resilient distribution network under pre-disaster prevention and disaster response[J]. Journal of Northeast Electric Power University, 2023, 43 (4): 82- 89.
8	闫丽梅, 丁泽华. 基于谱聚类的主动配电网多时间尺度无功优化策略[J]. 浙江电力, 2024, 43 (2): 58- 68.
	YAN Limei, DING Zehua. A multi-timescale reactive power optimization strategy for active distribution net-works based on spectral clustering[J]. Zhejiang Electric Power, 2024, 43 (2): 58- 68.
9	徐芮, 刘俊勇, 刘友波, 等. 考虑负荷聚类分区与分布式发电接入的配电网主次网架规划方法[J]. 电力自动化设备, 2016, 36 (6): 48- 55.
	XU Rui, LIU Junyong, LIU Youbo, et al. Primary and subordinate distribution network planning considering load clustering partition and DG integration[J]. Electric Power Automation Equipment, 2016, 36 (6): 48- 55.
10	汤波, 杨鹏, 余光正, 等. 基于负荷峰谷耦合特性的中压配电网供区优化方法[J]. 中国电机工程学报, 2022, 42 (19): 7051- 7062.
	TANG Bo, YANG Peng, YU Guangzheng, et al. Power supply area optimization method of medium voltage distribution network based on load peak valley coupling characteristics[J]. Proceedings of the CSEE, 2022, 42 (19): 7051- 7062.
11	韩俊, 谈健, 黄河, 等. 基于改进K-means聚类算法的供电块划分方法[J]. 电力自动化设备, 2015, 35 (6): 123- 129.
	HAN Jun, TAN Jian, HUANG He, et al. Power-supplying block partition based on improved K-means clustering algorithm[J]. Electric Power Automation Equipment, 2015, 35 (6): 123- 129.
12	葛少云, 蔡期塬, 刘洪, 等. 考虑负荷特性互补及供电单元划分的中压配电网实用化自动布线[J]. 中国电机工程学报, 2020, 40 (3): 790- 802.
	GE Shaoyun, CAI Qiyuan, LIU Hong, et al. Practical automatic planning for MV distribution network considering complementation of load characteristic and power supply unit partitioning[J]. Proceedings of the CSEE, 2020, 40 (3): 790- 802.
13	陈哲, 王主丁, 黄河, 等. 中压配电网规划中计及多因素影响的供电分区划分方法[J]. 电网技术, 2020, 44 (12): 4636- 4643.
	CHEN Zhe, WANG Zhuding, HUANG He, et al. Power supply area division method with multiple factors' influence for medium voltage distribution network planning[J]. Power System Technology, 2020, 44 (12): 4636- 4643.
14	任泓宇, 王主丁, 张超, 等. 高压配电网网格化规划优化模型和方法[J]. 电力系统自动化, 2019, 43 (14): 151- 158. DOI
	REN Hongyu, WANG Zhuding, ZHANG Chao, et al. Optimization model and method for mesh planning for high-voltage distribution network[J]. Automation of Electric Power Systems, 2019, 43 (14): 151- 158. DOI
15	梅笑妍, 郝思鹏, 嵇天烨. 基于改进k-means算法的有源配电网网格化规划方法[J]. 机械与电子, 2023, 41 (9): 18- 21, 26. DOI
	MEI Xiaoyan, HAO Sipeng, JI Tianye. Grid planning method of active distribution network based on improved k-means algorithm[J]. Machinery & Electronics, 2023, 41 (9): 18- 21, 26. DOI
16	刘昭睿, 王凯, 王新建, 等. 提升末端区域电网供电能力的调控方案及稳控策略研究[J]. 内蒙古电力技术, 2024, 42 (3): 52- 60.
	LIU Zhaorui, WANG Kai, WANG Xinjian, et al. Research on regulation scheme and stability control strategy for enhancing power supply capacity of end-region power grid[J]. Inner Mongolia Electric Power, 2024, 42 (3): 52- 60.
17	林湘宁, 王伟名, 随权, 等. 主动配电网-充换电站群-智慧社区群分层优化调度策略[J]. 广东电力, 2024, 37 (10): 25- 37. DOI
	LIN Xiangning, WANG Weiming, SUI Quan, et al. Hierarchical optimal scheduling strategy for active power distribution network, charging and switching station cluster and smart community cluster[J]. Guangdong Electric Power, 2024, 37 (10): 25- 37. DOI
18	刘曌煜, 戴攀, 李家桐, 等. 基于图论的配电网网格化供电单元自动划分策略[J]. 浙江电力, 2023, 42 (7): 66- 75.
	LIU Zhaoyu, DAI Pan, LI Jiatong, et al. An auto division strategy for grid-based power supply unit of distribution networks based on graph theory[J]. Zhejiang Electric Power, 2023, 42 (7): 66- 75.
19	马成廉, 李闯, 薛冰, 等. 含高比例光伏配电网分区电压协调控制策略[J]. 东北电力大学学报, 2024, 44 (4): 77- 85.
	MA Chenglian, LI Chuang, XUE Bing, et al. Voltage coordination control strategy for zoning in distribution network with high proportion of photovoltaic[J]. Journal of Northeast Dianli University, 2024, 44 (4): 77- 85.
20	杨晓峰, 方逸航, 赵鹏臻, 等. 基于K-means和BPNN的风机状态识别[J]. 中国电力, 2023, 56 (6): 158- 166, 175.
	YANG Xiaofeng, FANG Yihang, ZHAO Pengzhen, et al. State recognition of wind turbines based on K-means and BPNN[J]. Electric Power, 2023, 56 (6): 158- 166, 175.
21	杨彪, 颜伟, 莫静山. 考虑源荷功率随机性和相关性的主导节点选择与无功分区方法[J]. 电力系统自动化, 2021, 45 (11): 61- 67.
	YANG Biao, YAN Wei, MO Jingshan. Pilot-bus selection and network partitioning method considering randomness and correlation of source-load power[J]. Automation of Electric Power Systems, 2021, 45 (11): 61- 67.
22	杨冬晗, 李志强, 吴希, 等. 基于最小权和模板匹配的Oracle线路优化[J]. 量子电子学报, 2024, 41 (1): 151- 160. DOI
	YANG Donghan, LI Zhiqiang, WU Xi, et al. Optimization of Oracle circuits based on minimum weight and template matching[J]. Chinese Journal of Quantum Electronics, 2024, 41 (1): 151- 160. DOI
23	张少明, 盛四清. 基于改进粒子群算法的微网优化运行[J]. 中国电力, 2020, 53 (5): 24- 31.
	ZHANG Shaoming, SHENG Siqing. Optimal operation of microgrid based on improved particle swarm optimization algorithm[J]. Electric Power, 2020, 53 (5): 24- 31.

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