计及高渗透率分布式电源的韧性配电网数据驱动鲁棒规划方法

doi:10.12204/j.issn.1000-7229.2023.06.009

电力建设 ›› 2023, Vol. 44 ›› Issue (6): 79-90.doi: 10.12204/j.issn.1000-7229.2023.06.009

计及高渗透率分布式电源的韧性配电网数据驱动鲁棒规划方法

黄梦旗¹(), 李勇汇¹(), 曾海燕², 陈艳², 王宣², 王东旭², 杨军¹

1.武汉大学电气与自动化学院,武汉市 430072
2.国网武汉供电公司,武汉市 430014

收稿日期:2022-09-16 出版日期:2023-06-01 发布日期:2023-05-25
通讯作者: 李勇汇(1973),男,博士,副教授,主要研究方向为电力系统运行控制,E-mail:whusee2006@yahoo.com。
作者简介:黄梦旗(1999),男,硕士研究生,主要研究方向为高比例电力系统调度运行,E-mail:hmq007@whu.edu.cn;
曾海燕(1979),女,硕士,高级工程师,主要研究方向为配电网规划、改造与建设;
陈艳(1973),女,硕士,高级工程师,主要研究方向为电力规划;
王宣(1988),女,硕士,高级工程师,主要研究方向为配电网规划管理;
王东旭(1984),男,博士,高级工程师,主要研究方向为配电网规划;
杨军(1977),男,博士,教授,博士生导师,主要研究方向为电动汽车、电力系统调度运行。
基金资助:
国家自然科学基金项目(51977154)

Data-Driven Robust Planning Method for Resilient Distribution Networks Considering High-Permeability Distributed Generation

HUANG Mengqi¹(), LI Yonghui¹(), ZENG Haiyan², CHEN Yan², WANG Xuan², WANG Dongxu², YANG Jun¹

1. School of Electrical Engineering and Automation, Wuhan University, Wuhan 430072, China
2. State Grid Wuhan Electric Power Supply Company, Wuhan 430014, China

Received:2022-09-16 Online:2023-06-01 Published:2023-05-25
Supported by:
National Natural Science Foundation of China(51977154)

摘要/Abstract

摘要：

考虑高渗透率分布式电源(distributed generation,DG)接入给配电网带来的影响,提出了一种计及配电网韧性的数据驱动鲁棒规划方法。首先提出了含高渗透率分布式电源的韧性综合评价体系;接着将三阶段规划模型转换成二阶段数据驱动鲁棒规划模型,完成对线路加固方案以及分布式电源位置和容量的最优配置;采用基于极限场景法的改进列约束生成算法(column-and-constraint generation,C&CG)对鲁棒模型进行求解。最后,通过算例分析所提韧性提升措施的效果。结果表明,所提方法能够有效量化配电网韧性,进而为含高渗透率分布式电源的韧性配电网规划提供参考。

关键词: 高渗透率, 分布式电源(DG), 韧性, 数据驱动, 二阶段鲁棒规划

Abstract:

By considering the impact of high-permeability distributed generation access on distribution networks, a data-driven robust planning method that accounts for the resilience of a distribution network is proposed. First, a comprehensive resilience evaluation system with high-permeability distributed generation is proposed. The three-stage planning model is then transformed into a two-stage data-driven robust planning model to complete the decision-making of the line-reinforcement scheme and the optimal allocation of distributed generation location capacity. An improved column and constraint generation algorithm based on the limit scenario method is used to solve the robust model. Finally, an example is provided to analyze the effects of the proposed resilience improvement measures. The results show that the proposed method can effectively quantify the resilience of a distribution network and provide a reference for resilient distribution network planning with high-permeability distributed generation.

Key words: high permeability, distributed generation (DG), resilience, data driven, two stage robust programming

中图分类号:

TM73

黄梦旗, 李勇汇, 曾海燕, 陈艳, 王宣, 王东旭, 杨军. 计及高渗透率分布式电源的韧性配电网数据驱动鲁棒规划方法[J]. 电力建设, 2023, 44(6): 79-90.

HUANG Mengqi, LI Yonghui, ZENG Haiyan, CHEN Yan, WANG Xuan, WANG Dongxu, YANG Jun. Data-Driven Robust Planning Method for Resilient Distribution Networks Considering High-Permeability Distributed Generation[J]. ELECTRIC POWER CONSTRUCTION, 2023, 44(6): 79-90.

图/表 18

图1 韧性指标评价体系

Fig.1 Resilience index evaluation system

图2 配电网系统功能曲线

Fig.2 Distribution network system function curve

表1 不确定问题处理模型

Table 1 Uncertain problem processing model

图3 三阶段规划模型

Fig.3 Three stage programming model

图4 区间不确定集及椭球不确定集

Fig.4 Interval uncertain sets and ellipsoidal uncertain sets

图5 数据驱动鲁棒规划模型求解流程

Fig.5 Solution process of data-driven robust planning model

图6 改进的IEEE 33节点配电系统

Fig.6 Adapted IEEE-33 node distribution system

图7 各节点基准负荷

Fig.7 Reference load of each node

图8 备选加固线路集合

Fig.8 Set of alternative reinforcement lines

表2 各段线路故障率

Table 2 Failure rate of each line

图9 DG备选接入位置

Fig.9 DG alternative connection points

图10 场景1规划结果

Fig.10 Scenario 1 planning results

图11 场景2规划结果

Fig.11 Scenario 2 planning results

图12 场景3规划结果

Fig.12 Scenario 3 planning results

表3 韧性指标数值

Table 3 Resilience index value

表4 标准化数值

Table 4 Normalized value

表5 各场景最终得分

Table 5 Final score of each scheme

表6 不同渗透率下DG容量

Table 6 DG capacity under different permeability

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计及高渗透率分布式电源的韧性配电网数据驱动鲁棒规划方法

Data-Driven Robust Planning Method for Resilient Distribution Networks Considering High-Permeability Distributed Generation

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