Heuristic Moment Matching based Scenario Generation for Regional Energy Network Planning considering the Stochastic Generation and Demands

Zhonghua Chen, Qiang Xu, Q. Hu, Xianqing Chen, Qiang Yang
{"title":"Heuristic Moment Matching based Scenario Generation for Regional Energy Network Planning considering the Stochastic Generation and Demands","authors":"Zhonghua Chen, Qiang Xu, Q. Hu, Xianqing Chen, Qiang Yang","doi":"10.1109/DCABES50732.2020.00027","DOIUrl":null,"url":null,"abstract":"In this paper, the Heuristic Moment Matching (HMM) is adopted and evaluated in the investigation of regional energy network planning considering the uncertainties introduced by the stochastic generation and demands. The adoption of the scenario generation solution can effectively include the uncertainties in the system planning process in the multi-energy networks, including wind turbines (WTs) and solar photovoltaic (PVs). The scenario generation approach is implemented and the effectiveness is validated through numerical experiments. Finally, the scenario generation approach is adopted through a 53 bus test network and the effectiveness is confirmed through comparison against the conventional planning solution.","PeriodicalId":351404,"journal":{"name":"2020 19th International Symposium on Distributed Computing and Applications for Business Engineering and Science (DCABES)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 19th International Symposium on Distributed Computing and Applications for Business Engineering and Science (DCABES)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DCABES50732.2020.00027","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

In this paper, the Heuristic Moment Matching (HMM) is adopted and evaluated in the investigation of regional energy network planning considering the uncertainties introduced by the stochastic generation and demands. The adoption of the scenario generation solution can effectively include the uncertainties in the system planning process in the multi-energy networks, including wind turbines (WTs) and solar photovoltaic (PVs). The scenario generation approach is implemented and the effectiveness is validated through numerical experiments. Finally, the scenario generation approach is adopted through a 53 bus test network and the effectiveness is confirmed through comparison against the conventional planning solution.
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
考虑随机发电和需求的启发式矩匹配区域能源网络规划情景生成
本文将启发式矩匹配(HMM)方法应用于考虑随机发电和需求带来的不确定性的区域能源网络规划研究,并对其进行了评价。采用场景生成方案可以有效地纳入多能源网络(包括风力发电机组和太阳能光伏发电机组)系统规划过程中的不确定性。实现了场景生成方法,并通过数值实验验证了该方法的有效性。最后,通过53总线测试网络采用场景生成方法,并与传统规划方案进行对比,验证了方案的有效性。
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
自引率
0.00%
发文量
0
期刊最新文献
Visible and infrared image fusion based on visual saliency detection Sponsors DCABES 2020 Computer Vision based Automatic Power Equipment Condition Monitoring and Maintenance: A Brief Review Heuristic Moment Matching based Scenario Generation for Regional Energy Network Planning considering the Stochastic Generation and Demands Some New Attempts to Process Biological Data
×
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