Research on a Three-Stage Dynamic Reactive Power Optimization Decoupling Strategy for Active Distribution Networks with Carbon Emissions

Author:

Wu Yuezhong1ORCID,Xiong Yujie2ORCID,Peng Xiaowei3,Cai Cheng4,Zheng Xiangming5

Affiliation:

1. College of Railway Transportation, Hunan University of Technology, Zhuzhou 412007, China

2. College of Electrical and Information Engineering, Hunan University of Technology, Zhuzhou 412007, China

3. Hunan Kori Convertors Co., Ltd., Zhuzhou 412007, China

4. Hunan Fuze Information Technology Co., Ltd., Changsha 410205, China

5. College of Urban and Environmental Sciences, Hunan University of Technology, Zhuzhou 412007, China

Abstract

The reactive power optimization of an active distribution network can effectively deal with the problem of voltage overflows at some nodes caused by the integration of a high proportion of distributed sources into the distribution network. Aiming to address the limitations in previous studies of dynamic reactive power optimization using the cluster partitioning method, a three-stage dynamic reactive power optimization decoupling strategy for active distribution networks considering carbon emissions is proposed in this paper. First, a carbon emission index is proposed based on the carbon emission intensity, and a dynamic reactive power optimization mathematical model of an active distribution network is established with the minimum active power network loss, voltage deviation, and carbon emissions as the satisfaction objective functions. Second, in order to satisfy the requirement for the all-day motion times of discrete devices, a three-stage dynamic reactive power optimization decoupling strategy based on the partitioning around a medoids clustering algorithm is proposed. Finally, taking the improved IEEE33 and PG&E69-node distribution network systems as examples, the proposed linear decreasing mutation particle swarm optimization algorithm was used to solve the mathematical model. The results show that all the indicators of the proposed strategy and algorithm throughout the day are lower than those of other methods, which verifies the effectiveness of the proposed strategy and algorithm.

Funder

National Key R&D Program of China

Publisher

MDPI AG

Reference37 articles.

1. Technical characteristics of China’s new generation power system during energy transition;Zhou;Proc. CSEE,2018

2. Voltage regulation and power loss mitigation by optimal allocation of energy storage systems in distribution systems considering wind power uncertainty;ALAhmad;J. Energy Storage,2023

3. Deep reinforcement learning-based adaptive voltage control of active distribution networks with multi-terminal soft open point;Li;Int. J. Electr. Power Energy Syst.,2022

4. Reactive power optimization strategy of deep reinforcement learning for distribution network with multiple time scales;Hu;Proc. CSEE,2022

5. Intelligent coordinated configuration of reactive power compensation in distribution network integrating planning and operation;Zhu;Electr. Power Autom. Equip.,2019

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3