极端天气下智能配电网的弹性评估

李振坤; 王法顺; 郭维一; 米阳; 季亮

doi:10.7500/AEPS20190418008

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极端天气下智能配电网的弹性评估

学术研究 | 更新时间：2025-06-16

- 极端天气下智能配电网的弹性评估
- Resilience Evaluation of Smart Distribution Network in Extreme Weather
- 电力系统自动化-方正平台 2020年44卷第9期页码：60-68
- 作者机构：
  
  上海电力大学电气工程学院，上海市 200090
- 作者简介：
  
  李振坤(1982—)，男，通信作者，博士，副教授，硕士生导师，主要研究方向：配电网规划及运行控制、分布式电源并网及微电网、主动配电网技术等。E-mail：lzk021@163.com
  王法顺(1995—)，男，硕士研究生，主要研究方向：弹性配电网评估及规划。E-mail：1498776160@qq.com
  郭维一(1995—)，男，硕士研究生，主要研究方向：能源互联网的优化规划。E-mail：573701467@qq.com
- 基金信息：
  
  国家自然科学基金资助项目(51407113)
- DOI：10.7500/AEPS20190418008
  中图分类号：
- 收稿日期：2019-04-18，
  
  修回日期：2019-08-04，
  
  网络出版日期：2020-03-24，
  
  纸质出版日期：2020-05-10
- 稿件说明：
移动端阅览
李振坤,王法顺,郭维一等.极端天气下智能配电网的弹性评估[J].电力系统自动化,2020,44(9):60-68.

LI Zhenkun,WANG Fashun,GUO Weiyi,et al.Resilience Evaluation of Smart Distribution Network in Extreme Weather[J].Automation of Electric Power Systems,2020,44(9):60-68.
李振坤,王法顺,郭维一等.极端天气下智能配电网的弹性评估[J].电力系统自动化,2020,44(9):60-68. DOI： 10.7500/AEPS20190418008.

LI Zhenkun,WANG Fashun,GUO Weiyi,et al.Resilience Evaluation of Smart Distribution Network in Extreme Weather[J].Automation of Electric Power Systems,2020,44(9):60-68. DOI： 10.7500/AEPS20190418008.

摘要

近年来受极端天气的影响，配电网大范围停电事故率不断上升，能够防御自然灾害、减小停电事故影响的弹性配电网引起了人们的重视。为了更好地评估配电网应对极端灾害的弹性，文中提出了一种智能配电网弹性评估方法。首先，建立了极端天气下的故障模型用以量化极端天气对配电网的影响。其次，针对极端天气的随机性，文中通过蒙特卡洛法模拟极端天气场景并采用

-means聚类算法对场景进行缩减，根据脆弱性曲线可以得到配电网各支路的时变故障率。考虑到负荷、可再生能源出力的不确定性，采用拉丁超立方抽样抽取负荷、可再生能源出力和配电网故障场景对配电网进行弹性评估。然后，为了全面准确地反映含分布式电源的配电网弹性，将配电网遭受自然灾害时分为防灾和减灾2个阶段，并基于此构建了包括配电网防御时间、弹性恢复系数、孤岛可持续时间覆盖率和重要负荷平均中断时间在内的弹性评估指标体系。最后，对一包含2条馈线的实际配电系统的弹性进行仿真评估，并考虑了电力线路类型、光伏渗透率和联络线对配电网弹性的影响，验证了所提评估方法的有效性。

Abstract

In recent years

due to the influence of extreme weather

the rate of large-scale blackouts in distribution network continues to rise

and the resilient distribution network that can resist natural disasters and reduce the impact of power failure accidents has attracted more attention. In order to better evaluate the resilience of distribution network to extreme disasters

a method for evaluating the resilience of smart distribution network is proposed. Firstly

a fault model in extreme weather is established to quantify the influence of extreme weather on the distribution network. Secondly

in view of the randomness of extreme weather

Monte Carlo simulation of extreme weather scenarios is adopted and

-means clustering algorithm is applied for scenarios reduction. Time-varying failure rate of each branch of distribution network can be obtained according to the vulnerability curve. Considering the uncertainty of load and renewable energy

Latin hypercube sampling is adopted to extract load

renewable energy and distribution network fault scenarios to evaluate the resilience of distribution network. Then

in order to fully and accurately reflect the resilience of distribution network with distribution generator

the distribution network is divided into two stages of disaster prevention and reduction while suffering from natural disaster. Based on this

the index system of resilience evaluation is constructed including defense time of distribution network

coefficient of resilience recovery

coverage rate of island sustainable time and mean interruption time of critical load. Finally

the simulation evaluation of the resilience of an actual distribution system with two feeders is carried out

and the influence of power line type

photovoltaic permeability rate and tie lines on the resilience of the distribution network is considered

which verifies the effectiveness of the proposed evaluation method.

关键词

Keywords

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