Integrating model-driven and data-driven methods for under-frequency load shedding control

IF 3.3 3区 工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC Electric Power Systems Research Pub Date : 2024-10-15 DOI:10.1016/j.epsr.2024.111103
Binghui Li , Huaiyuan Wang , Jian Li , Guoqiang Lu
{"title":"Integrating model-driven and data-driven methods for under-frequency load shedding control","authors":"Binghui Li ,&nbsp;Huaiyuan Wang ,&nbsp;Jian Li ,&nbsp;Guoqiang Lu","doi":"10.1016/j.epsr.2024.111103","DOIUrl":null,"url":null,"abstract":"<div><div>With the access of a high percentage of new energy sources, power system frequency stability is challenged. Under-frequency load shedding (UFLS) is one of the primary measures to maintain frequency stability. Due to the mismatch between the amount of load shed by the traditional UFLS methods and the actual active power deficit, a new UFLS method needs to be designed. An approach utilizing a deep deterministic policy gradient (DDPG) algorithm for the problem is proposed. First, the DDPG algorithm is modified to adapt to the UFLS problem. Then, the idea of model-driven is introduced to improve the validity of the model. Thus, a novel UFLS method is proposed, which integrates data-driven and model-driven ideas. Furthermore, a structure called the dual experience pool is designed to accelerate training speed and improve stability. Based on the proposed method, a UFLS control framework is designed. Finally, the suggested methodology is validated using the IEEE-39 bus system and the Fujian power grid as test cases.</div></div>","PeriodicalId":50547,"journal":{"name":"Electric Power Systems Research","volume":"238 ","pages":"Article 111103"},"PeriodicalIF":3.3000,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Electric Power Systems Research","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S037877962400988X","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0

Abstract

With the access of a high percentage of new energy sources, power system frequency stability is challenged. Under-frequency load shedding (UFLS) is one of the primary measures to maintain frequency stability. Due to the mismatch between the amount of load shed by the traditional UFLS methods and the actual active power deficit, a new UFLS method needs to be designed. An approach utilizing a deep deterministic policy gradient (DDPG) algorithm for the problem is proposed. First, the DDPG algorithm is modified to adapt to the UFLS problem. Then, the idea of model-driven is introduced to improve the validity of the model. Thus, a novel UFLS method is proposed, which integrates data-driven and model-driven ideas. Furthermore, a structure called the dual experience pool is designed to accelerate training speed and improve stability. Based on the proposed method, a UFLS control framework is designed. Finally, the suggested methodology is validated using the IEEE-39 bus system and the Fujian power grid as test cases.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
整合模型驱动和数据驱动方法,实现欠频甩负荷控制
随着大量新能源的接入,电力系统的频率稳定性面临挑战。欠频甩负荷(UFLS)是维持频率稳定的主要措施之一。由于传统 UFLS 方法的甩负荷量与实际有功功率缺口不匹配,因此需要设计一种新的 UFLS 方法。本文提出了一种利用深度确定性策略梯度(DDPG)算法解决该问题的方法。首先,对 DDPG 算法进行修改,以适应 UFLS 问题。然后,引入模型驱动的思想来提高模型的有效性。因此,我们提出了一种融合了数据驱动和模型驱动思想的新型 UFLS 方法。此外,还设计了一种名为双经验池的结构,以加快训练速度并提高稳定性。根据提出的方法,设计了一个 UFLS 控制框架。最后,以 IEEE-39 总线系统和福建电网为测试案例,对所提出的方法进行了验证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Electric Power Systems Research
Electric Power Systems Research 工程技术-工程:电子与电气
CiteScore
7.50
自引率
17.90%
发文量
963
审稿时长
3.8 months
期刊介绍: Electric Power Systems Research is an international medium for the publication of original papers concerned with the generation, transmission, distribution and utilization of electrical energy. The journal aims at presenting important results of work in this field, whether in the form of applied research, development of new procedures or components, orginal application of existing knowledge or new designapproaches. The scope of Electric Power Systems Research is broad, encompassing all aspects of electric power systems. The following list of topics is not intended to be exhaustive, but rather to indicate topics that fall within the journal purview. • Generation techniques ranging from advances in conventional electromechanical methods, through nuclear power generation, to renewable energy generation. • Transmission, spanning the broad area from UHV (ac and dc) to network operation and protection, line routing and design. • Substation work: equipment design, protection and control systems. • Distribution techniques, equipment development, and smart grids. • The utilization area from energy efficiency to distributed load levelling techniques. • Systems studies including control techniques, planning, optimization methods, stability, security assessment and insulation coordination.
期刊最新文献
Electromechanical analysis of underbuilt wire use in transmission lines Optimal power flow solution via noise-resilient quantum interior-point methods Protection without current transformers for electrical installations with three-phase bus ducts Joint trading of energy and reserve considering microgrid agent fraudulent behaviors Aggregated vulnerability assessment of power transmission lines under operational and hurricane induced outages
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1