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基于多准则决策分析的新型电力系统配电网自平衡能力评估方法

余光正 张俊杰 陈甜甜 刘婧 杨楠

电力系统保护与控制2025,Vol.53Issue(11):30-40,11.
电力系统保护与控制2025,Vol.53Issue(11):30-40,11.DOI:10.19783/j.cnki.pspc.241037

基于多准则决策分析的新型电力系统配电网自平衡能力评估方法

A multi-criteria decision analysis-based method for assessing self-balancing capability in new power distribution networks

余光正 1张俊杰 1陈甜甜 2刘婧 2杨楠3

作者信息

  • 1. 上海电力大学电气工程学院,上海 200090
  • 2. 国网上海市电力公司电力科学研究院,上海 200437
  • 3. 三峡大学电气与新能源学院,湖北 宜昌 443002
  • 折叠

摘要

Abstract

With the large-scale integration of distributed new energy and flexible loads into new power systems,traditional approaches for balancing electric power supply and demand are increasingly inadequate in addressing the complexity characteristics of generation and load,as well as the evolving supply-demand relationships.This presents significant challenges to the coordinated operation of such systems.To harness the regulatory potential of flexible resources within distribution networks and enhance self-balancing capability of power grids,a self-balancing capability assessment method for new power systems is proposed based on multi-criteria decision analysis.First,an evaluation index system is established to quantitively assess the self-balancing level of the distribution network.Then,a self-balancing capability assessment method based on multi-criteria decision analysis is developed by constructing a evaluation model based on preference order structure.Finally,the effectiveness of the proposed method is verified by example analysis and historical data.The assessment results can guide the construction of flexible resources such as new energy and demand-side response to meet the needs of new power systems across various time scale and application scenarios.

关键词

新型电力系统/自平衡能力评估/多准则决策/偏好顺序结构评估法

Key words

new power system/self-balancing capability assessment/multi-criteria decision analysis/preference ranking structure evaluation method

引用本文复制引用

余光正,张俊杰,陈甜甜,刘婧,杨楠..基于多准则决策分析的新型电力系统配电网自平衡能力评估方法[J].电力系统保护与控制,2025,53(11):30-40,11.

基金项目

This work is supported by the National Natural Science Foundation of China(No.52207121). 国家自然科学基金项目资助(52207121) (No.52207121)

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