Distributed and Risk-Averse ADP Algorithm for Stochastic Economic Dispatch of Power System with Multiple Offshore Wind Farms

IF 6.9 2区 工程技术 Q2 ENERGY & FUELS CSEE Journal of Power and Energy Systems Pub Date : 2023-06-27 DOI:10.17775/CSEEJPES.2022.03890
Xiangyong Feng;Shunjiang Lin;Yutao Liang;Guansheng Fan;Mingbo Liu
{"title":"Distributed and Risk-Averse ADP Algorithm for Stochastic Economic Dispatch of Power System with Multiple Offshore Wind Farms","authors":"Xiangyong Feng;Shunjiang Lin;Yutao Liang;Guansheng Fan;Mingbo Liu","doi":"10.17775/CSEEJPES.2022.03890","DOIUrl":null,"url":null,"abstract":"With more and more offshore wind power being increasingly connected to power grids, fluctuations in offshore wind speeds result in risks of high operation costs. To mitigate this problem, a risk-averse stochastic economic dispatch (ED) model of power system with multiple offshore wind farms (OWFs) is proposed in this paper. In this model, a novel GlueVaR method is used to measure the tail risk of the probability distribution of operation cost. The weighted sum of the expected operation cost and the GlueVaR is used to reflect the risk of operation cost, which can consider different risk requirements including risk aversion and risk neutrality flexibly by adjusting parameters. Then, a risk-averse approximate dynamic programming (ADP) algorithm is designed for solving the proposed model, in which multi-period ED problem is decoupled into a series of single-period ED problems. Besides, GlueVaR is introduced into the approximate value function training process for risk aversion. Finally, a distributed and risk-averse ADP algorithm is constructed based on the alternating direction method of multipliers, which can further decouple single-period ED between transmission system and multiple OWFs for ensuring information privacy. Case studies on the modified IEEE 39-bus system with an OWF and an actual provincial power system with four OWFs demonstrate correctness and efficiency of the proposed model and algorithm.","PeriodicalId":10729,"journal":{"name":"CSEE Journal of Power and Energy Systems","volume":null,"pages":null},"PeriodicalIF":6.9000,"publicationDate":"2023-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10165662","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"CSEE Journal of Power and Energy Systems","FirstCategoryId":"5","ListUrlMain":"https://ieeexplore.ieee.org/document/10165662/","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
引用次数: 0

Abstract

With more and more offshore wind power being increasingly connected to power grids, fluctuations in offshore wind speeds result in risks of high operation costs. To mitigate this problem, a risk-averse stochastic economic dispatch (ED) model of power system with multiple offshore wind farms (OWFs) is proposed in this paper. In this model, a novel GlueVaR method is used to measure the tail risk of the probability distribution of operation cost. The weighted sum of the expected operation cost and the GlueVaR is used to reflect the risk of operation cost, which can consider different risk requirements including risk aversion and risk neutrality flexibly by adjusting parameters. Then, a risk-averse approximate dynamic programming (ADP) algorithm is designed for solving the proposed model, in which multi-period ED problem is decoupled into a series of single-period ED problems. Besides, GlueVaR is introduced into the approximate value function training process for risk aversion. Finally, a distributed and risk-averse ADP algorithm is constructed based on the alternating direction method of multipliers, which can further decouple single-period ED between transmission system and multiple OWFs for ensuring information privacy. Case studies on the modified IEEE 39-bus system with an OWF and an actual provincial power system with four OWFs demonstrate correctness and efficiency of the proposed model and algorithm.
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
多海上风电场电力系统随机经济调度的分布式风险规避 ADP 算法
随着越来越多的海上风电接入电网,海上风速的波动导致了高运营成本的风险。为缓解这一问题,本文提出了一种具有多个海上风电场(OWFs)的电力系统风险规避随机经济调度(ED)模型。在该模型中,使用了一种新颖的 GlueVaR 方法来衡量运行成本概率分布的尾部风险。采用预期运营成本与 GlueVaR 的加权和来反映运营成本的风险,通过调整参数,可灵活考虑不同的风险要求,包括风险规避和风险中性。然后,设计了一种风险规避近似动态程序设计(ADP)算法来求解所提出的模型,将多期 ED 问题解耦为一系列单期 ED 问题。此外,在近似值函数训练过程中引入了 GlueVaR 以规避风险。最后,基于乘法交替方向法构建了分布式风险规避 ADP 算法,该算法可进一步解耦传输系统与多个 OWF 之间的单周期 ED,从而确保信息隐私。对带有一个 OWF 的改进型 IEEE 39 总线系统和带有四个 OWF 的实际省级电力系统进行的案例研究证明了所提模型和算法的正确性和高效性。
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
CiteScore
11.80
自引率
12.70%
发文量
389
审稿时长
26 weeks
期刊介绍: The CSEE Journal of Power and Energy Systems (JPES) is an international bimonthly journal published by the Chinese Society for Electrical Engineering (CSEE) in collaboration with CEPRI (China Electric Power Research Institute) and IEEE (The Institute of Electrical and Electronics Engineers) Inc. Indexed by SCI, Scopus, INSPEC, CSAD (Chinese Science Abstracts Database), DOAJ, and ProQuest, it serves as a platform for reporting cutting-edge theories, methods, technologies, and applications shaping the development of power systems in energy transition. The journal offers authors an international platform to enhance the reach and impact of their contributions.
期刊最新文献
Transient Voltage Support Strategy of Grid-Forming Medium Voltage Photovoltaic Converter in the LCC-HVDC System Front Cover Contents PFL-DSSE: A Personalized Federated Learning Approach for Distribution System State Estimation Front Cover
×
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