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考虑SOP与智能负载特性的配电网灵活性提升方法

王天宇 李晓露 柳劲松 林顺富

电力建设2024,Vol.45Issue(6):47-57,11.
电力建设2024,Vol.45Issue(6):47-57,11.DOI:10.12204/j.issn.1000-7229.2024.06.005

考虑SOP与智能负载特性的配电网灵活性提升方法

A Method for Improving the Flexibility of Distribution Networks Considering Soft Open Point and Smart Load Characteristics

王天宇 1李晓露 1柳劲松 2林顺富1

作者信息

  • 1. 上海电力大学电气工程学院,上海市 200090
  • 2. 国网上海市电力公司电力科学研究院,上海市 200437
  • 折叠

摘要

Abstract

The integration of new high-permeability distributed energy into the power grid has increased the demand for flexibility in the distribution network owing to the randomness and volatility of its output. A method for improving the flexibility of distribution networks that considers the complementary characteristics of soft open point (SOP) and smart load (SL) is proposed. First,the flexibility characteristics and mathematical models of the SOP,SL,controllable DG,and flexibility evaluation indicators were established from two aspects:node flexibility adaptability and the load margin of lines containing the SOP. Second,we constructed an objective function that considers the operating costs,voltage quality,and flexibility indicators,striving to achieve optimal economic performance while minimizing flexibility gaps and voltages exceeding the limits. Simultaneously,a reconstruction whale optimization algorithm (Re-WOA) was proposed to solve the optimization model,and two improved search predator strategies were introduced in the algorithm. The SL load balancing degree during the search phase was balanced using the SL capacity margin index. Finally,the optimization effect of the model on the distribution network and the effectiveness of the proposed Re-WOA were verified using an improved IEEE33 node system.

关键词

智能软开关/灵活性评估/智能负载/改进鲸鱼优化算法/负载均衡度

Key words

soft open point/flexibility assessment/smart load/reconstructed whale optimization algorithm/load balancing

分类

信息技术与安全科学

引用本文复制引用

王天宇,李晓露,柳劲松,林顺富..考虑SOP与智能负载特性的配电网灵活性提升方法[J].电力建设,2024,45(6):47-57,11.

基金项目

国家自然科学基金项目(51907114)This work is supported by the National Natural Science Foundation of China(No.51907114). (51907114)

电力建设

OA北大核心CSTPCD

1000-7229

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