Optimal price signal generation for demand-side energy management

IF 5 Q2 ENERGY & FUELS Smart Energy Pub Date : 2025-02-01 Epub Date: 2025-01-24 DOI:10.1016/j.segy.2025.100173
Seyed Shahabaldin Tohidi, Henrik Madsen, Davide Calì, Tobias K.S. Ritschel
{"title":"Optimal price signal generation for demand-side energy management","authors":"Seyed Shahabaldin Tohidi,&nbsp;Henrik Madsen,&nbsp;Davide Calì,&nbsp;Tobias K.S. Ritschel","doi":"10.1016/j.segy.2025.100173","DOIUrl":null,"url":null,"abstract":"<div><div>Renewable Energy Sources play a key role in smart energy systems. To achieve 100% renewable energy, utilizing the flexibility potential on the demand side becomes the cost-efficient option to balance the grid. However, it is not trivial to exploit these available capacities and flexibility options profitably. The amount of available flexibility is a complex and time-varying function of the price signal and weather forecasts. In this work, we use a Flexibility Function to represent the relationship between the price signal and the demand and investigate optimization problems for the price signal computation. Consequently, this study considers the higher and lower levels in the hierarchy from the markets to appliances, households, and districts. This paper investigates optimal price generation via the Flexibility Function and studies its employment in controller design for demand-side management, its capability to provide ancillary services for balancing throughout the Smart Energy Operating System, and its effect on the physical level performance. Sequential and simultaneous approaches for computing the price signal, along with various cost functions are analyzed and compared. Simulation results demonstrate the generated price/penalty signal and its employment in a model predictive controller.</div></div>","PeriodicalId":34738,"journal":{"name":"Smart Energy","volume":"17 ","pages":"Article 100173"},"PeriodicalIF":5.0000,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Smart Energy","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2666955225000012","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/24 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
引用次数: 0

Abstract

Renewable Energy Sources play a key role in smart energy systems. To achieve 100% renewable energy, utilizing the flexibility potential on the demand side becomes the cost-efficient option to balance the grid. However, it is not trivial to exploit these available capacities and flexibility options profitably. The amount of available flexibility is a complex and time-varying function of the price signal and weather forecasts. In this work, we use a Flexibility Function to represent the relationship between the price signal and the demand and investigate optimization problems for the price signal computation. Consequently, this study considers the higher and lower levels in the hierarchy from the markets to appliances, households, and districts. This paper investigates optimal price generation via the Flexibility Function and studies its employment in controller design for demand-side management, its capability to provide ancillary services for balancing throughout the Smart Energy Operating System, and its effect on the physical level performance. Sequential and simultaneous approaches for computing the price signal, along with various cost functions are analyzed and compared. Simulation results demonstrate the generated price/penalty signal and its employment in a model predictive controller.

Abstract Image

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
需求侧能源管理的最优价格信号生成
可再生能源在智能能源系统中发挥着关键作用。为了实现100%的可再生能源,利用需求侧的灵活性潜力成为平衡电网的成本效益选择。然而,利用这些可用的能力和灵活性选项并不是一件容易的事情。可用灵活性的数量是价格信号和天气预报的复杂和时变函数。在这项工作中,我们使用灵活性函数来表示价格信号与需求之间的关系,并研究价格信号计算的优化问题。因此,本研究考虑了从市场到家电、家庭和地区的层次结构中的较高和较低层次。本文通过柔性函数研究了最优电价生成,并研究了其在需求侧管理控制器设计中的应用,其为整个智能能源操作系统提供辅助服务的能力,以及其对物理层性能的影响。顺序和同时计算价格信号的方法,以及各种成本函数进行了分析和比较。仿真结果验证了所生成的价格/惩罚信号及其在模型预测控制器中的应用。
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
Smart Energy
Smart Energy Engineering-Mechanical Engineering
CiteScore
9.20
自引率
0.00%
发文量
29
审稿时长
73 days
期刊最新文献
PreFlex — A new marketplace for distributed flexibility providers hedging wind producers: A case study of the Norwegian electricity market A decision support tool for waste heat to heat recovery technologies in industrial sectors A methodological framework for identifying District Heating Networks in Germany by utilizing the census data Forecasting day-ahead hydropower bids in the colombian electricity market: A two-stage machine learning framework Bridging theory and practice: Building a coordinated offshore grid in the North Sea and United States Eastern Seaboard
×
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:604180095
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