Self-decomposition Method for Power Generators’ Medium- and Long-term Contract Based on Conditional Robust Profit

Han Qin, Shuai Liu, Jingwen Jiang, Shaohua Zhang
{"title":"Self-decomposition Method for Power Generators’ Medium- and Long-term Contract Based on Conditional Robust Profit","authors":"Han Qin, Shuai Liu, Jingwen Jiang, Shaohua Zhang","doi":"10.1109/ICPST56889.2023.10165215","DOIUrl":null,"url":null,"abstract":"Under the requirement of time linkage between contract trading and market trading, power generators’ medium- and long-term contracted electricity must be decomposed to a short time scale. To address this problem, a self-decomposition model for a generator’s medium- and long-term contracted energy based on conditional robust profit is proposed, taking into consideration the uncertainty of spot market prices. This model aims to maximize the generator’s conditional robust profit in the spot market, and the generator’s operation and contract decomposition constraints are considered. In addition, an auxiliary variable is employed to transform the model into a tractable formulation. Finally, the effectiveness of the model is verified by numerical examples. It is shown that the proposed model can accommodate the risk preferences of the generator, which means sound strategies can be formulated according to the different levels of risk aversion.","PeriodicalId":231392,"journal":{"name":"2023 IEEE International Conference on Power Science and Technology (ICPST)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 IEEE International Conference on Power Science and Technology (ICPST)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICPST56889.2023.10165215","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Under the requirement of time linkage between contract trading and market trading, power generators’ medium- and long-term contracted electricity must be decomposed to a short time scale. To address this problem, a self-decomposition model for a generator’s medium- and long-term contracted energy based on conditional robust profit is proposed, taking into consideration the uncertainty of spot market prices. This model aims to maximize the generator’s conditional robust profit in the spot market, and the generator’s operation and contract decomposition constraints are considered. In addition, an auxiliary variable is employed to transform the model into a tractable formulation. Finally, the effectiveness of the model is verified by numerical examples. It is shown that the proposed model can accommodate the risk preferences of the generator, which means sound strategies can be formulated according to the different levels of risk aversion.
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
基于条件稳健利润的发电企业中长期合同自分解方法
在合同交易与市场交易时间联动的要求下,发电企业中长期合同用电必须分解为短时间尺度。为解决这一问题,考虑现货市场价格的不确定性,提出了一种基于条件稳健利润的发电机组中长期合同能源自分解模型。该模型以发电商在现货市场上的条件稳健利润最大化为目标,考虑了发电商的运行约束和合同分解约束。此外,采用辅助变量将模型转化为易于处理的公式。最后,通过数值算例验证了模型的有效性。研究表明,所提出的模型能够适应发电商的风险偏好,这意味着可以根据不同的风险厌恶程度制定合理的策略。
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
Multi- agent Collaborative Optimal Operation Strategy of Microgrid Based on Master-Slave Game Bi-level Programming of Siting and Sizing for Shared Electric Bike Based on Niche Particle Swarm Algorithm Enhancement of External Insulation Performance for Vacuum Interrupters by External Shields Simulation Analysis of Thermal Runaway Characteristics of Lithium-Ion Batteries Marine Predators Algorithm Based Optimal Multicore Cable Topology
×
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