Cooperative energy and reserve trading strategies for multiple integrated energy systems based on asymmetric nash bargaining theory

IF 9 1区 工程技术 Q1 ENERGY & FUELS
Biao Wu, Shaohua Zhang, Chenxin Yuan, Xian Wang, Fei Wang, Shengqi Zhang
{"title":"Cooperative energy and reserve trading strategies for multiple integrated energy systems based on asymmetric nash bargaining theory","authors":"Biao Wu,&nbsp;Shaohua Zhang,&nbsp;Chenxin Yuan,&nbsp;Xian Wang,&nbsp;Fei Wang,&nbsp;Shengqi Zhang","doi":"10.1016/j.energy.2024.133703","DOIUrl":null,"url":null,"abstract":"<div><div>To tackle the issues of cooperative energy and reserve trading as well as fair cooperative benefit allocation among multiple integrated energy systems (IESs), this paper proposes a two-stage cooperative energy and reserve trading model for multiple integrated energy systems (MIESs). Specifically, at day-ahead stage, MIESs aim to maximize their overall profit through cooperative electricity and heat trading. At real-time stage, MIESs trade demand response (DR) reserve to minimize the overall wind power deviation compensation cost. To reduce the complexity in model solution, we transform the model into two sub-problems. In sub-problem 1, we determine the energy and DR reserve trading volumes. Here, distributionally robust optimization (DRO) is utilized to manage the severe uncertainties in wind power distribution. In sub-problem 2, based on the outcomes from sub-problem 1, we settle the energy and DR reserve trading prices. To ensure the fairness of benefit allocation, asymmetric Nash bargaining theory is applied to assess each IES's contributions in trading volumes and profit growth. Interval adaptive alternating direction method of multipliers (IA-ADMM) is used to preserve each IES's privacy. Finally, simulation results demonstrate that, compared with independent operation, cooperative trading among MIESs increases profits for all IESs, thereby motivating their participation in cooperative trading.</div></div>","PeriodicalId":11647,"journal":{"name":"Energy","volume":"313 ","pages":"Article 133703"},"PeriodicalIF":9.0000,"publicationDate":"2024-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Energy","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0360544224034819","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
引用次数: 0

Abstract

To tackle the issues of cooperative energy and reserve trading as well as fair cooperative benefit allocation among multiple integrated energy systems (IESs), this paper proposes a two-stage cooperative energy and reserve trading model for multiple integrated energy systems (MIESs). Specifically, at day-ahead stage, MIESs aim to maximize their overall profit through cooperative electricity and heat trading. At real-time stage, MIESs trade demand response (DR) reserve to minimize the overall wind power deviation compensation cost. To reduce the complexity in model solution, we transform the model into two sub-problems. In sub-problem 1, we determine the energy and DR reserve trading volumes. Here, distributionally robust optimization (DRO) is utilized to manage the severe uncertainties in wind power distribution. In sub-problem 2, based on the outcomes from sub-problem 1, we settle the energy and DR reserve trading prices. To ensure the fairness of benefit allocation, asymmetric Nash bargaining theory is applied to assess each IES's contributions in trading volumes and profit growth. Interval adaptive alternating direction method of multipliers (IA-ADMM) is used to preserve each IES's privacy. Finally, simulation results demonstrate that, compared with independent operation, cooperative trading among MIESs increases profits for all IESs, thereby motivating their participation in cooperative trading.
基于非对称纳什讨价还价理论的多综合能源系统能源和储备合作交易策略
为了解决多个综合能源系统(IES)之间的能源和储备合作交易以及公平的合作利益分配问题,本文提出了一个多综合能源系统(MIES)两阶段能源和储备合作交易模型。具体来说,在日前阶段,MIES 通过电力和热力的合作交易实现整体利益最大化。在实时阶段,MIES 交易需求响应储备,以最小化整体风电偏差补偿成本。为降低模型求解的复杂性,我们将模型转化为两个子问题。在子问题 1 中,我们确定能源和 DR 储备交易量。在此,利用分布式鲁棒优化(DRO)来管理风电分布中的严重不确定性。在子问题 2 中,根据子问题 1 的结果,我们确定能源和 DR 储备交易价格。为确保利益分配的公平性,我们采用非对称纳什讨价还价理论来评估每个 IES 在交易量和利润增长方面的贡献。采用区间自适应交替乘法(IA-ADMM)来保护每个 IES 的隐私。最后,模拟结果表明,与独立运营相比,MIES 之间的合作交易会增加所有 IES 的利润,从而激励它们参与合作交易。
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 求助全文
来源期刊
Energy
Energy 工程技术-能源与燃料
CiteScore
15.30
自引率
14.40%
发文量
0
审稿时长
14.2 weeks
期刊介绍: Energy is a multidisciplinary, international journal that publishes research and analysis in the field of energy engineering. Our aim is to become a leading peer-reviewed platform and a trusted source of information for energy-related topics. The journal covers a range of areas including mechanical engineering, thermal sciences, and energy analysis. We are particularly interested in research on energy modelling, prediction, integrated energy systems, planning, and management. Additionally, we welcome papers on energy conservation, efficiency, biomass and bioenergy, renewable energy, electricity supply and demand, energy storage, buildings, and economic and policy issues. These topics should align with our broader multidisciplinary focus.
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信