Decarbonizing all-electric communities via carbon-responsive control of behind-the-meter resources

IF 13 Q1 ENERGY & FUELS Advances in Applied Energy Pub Date : 2023-06-01 DOI:10.1016/j.adapen.2023.100139
Jing Wang, Rawad El Kontar, Xin Jin, Jennifer King
{"title":"Decarbonizing all-electric communities via carbon-responsive control of behind-the-meter resources","authors":"Jing Wang,&nbsp;Rawad El Kontar,&nbsp;Xin Jin,&nbsp;Jennifer King","doi":"10.1016/j.adapen.2023.100139","DOIUrl":null,"url":null,"abstract":"<div><p>The progression of electrification in the building and transportation sectors brings new opportunities for energy decarbonization. With higher dependence on the grid power supply, the variation of the grid carbon emission intensity can be utilized to reduce the carbon emissions from the two sectors. Existing coordinated control methods for buildings with distributed energy resources (DERs) either consider electricity price or renewable energy generation as the input signal, or adopt optimization in the decision-making, which is difficult to implement in the real-world environment. This paper aims to propose and validate an easy-to-deploy rule-based carbon responsive control framework that facilitates coordination between all-electric buildings and electric vehicles (EVs). The signals of the grid carbon emission intensity and the local photovoltaics (PV) generation are used for shifting the controllable loads. Extensive simulations were conducted using a model of an all-electric mixed-use community in a cold climate to validate the control performance with metrics such as emissions, energy consumption, peak demand, and EV end-of-day state-of-charge (SOC). Our study identifies that 4.5% to 27.1% of annual emission reduction can be achieved with limited impact on energy costs, peak demand, and thermal comfort. Additionally, up to 32.7% of EV emission reduction can be obtained if the EV owners reduce the target SOC by less than 21.2%.</p></div>","PeriodicalId":34615,"journal":{"name":"Advances in Applied Energy","volume":"10 ","pages":"Article 100139"},"PeriodicalIF":13.0000,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advances in Applied Energy","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2666792423000185","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
引用次数: 0

Abstract

The progression of electrification in the building and transportation sectors brings new opportunities for energy decarbonization. With higher dependence on the grid power supply, the variation of the grid carbon emission intensity can be utilized to reduce the carbon emissions from the two sectors. Existing coordinated control methods for buildings with distributed energy resources (DERs) either consider electricity price or renewable energy generation as the input signal, or adopt optimization in the decision-making, which is difficult to implement in the real-world environment. This paper aims to propose and validate an easy-to-deploy rule-based carbon responsive control framework that facilitates coordination between all-electric buildings and electric vehicles (EVs). The signals of the grid carbon emission intensity and the local photovoltaics (PV) generation are used for shifting the controllable loads. Extensive simulations were conducted using a model of an all-electric mixed-use community in a cold climate to validate the control performance with metrics such as emissions, energy consumption, peak demand, and EV end-of-day state-of-charge (SOC). Our study identifies that 4.5% to 27.1% of annual emission reduction can be achieved with limited impact on energy costs, peak demand, and thermal comfort. Additionally, up to 32.7% of EV emission reduction can be obtained if the EV owners reduce the target SOC by less than 21.2%.

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
通过对仪表后资源的碳响应控制实现全电力社区脱碳
建筑和交通领域电气化的发展为能源脱碳带来了新的机遇。由于对电网供电的依赖程度较高,可以利用电网碳排放强度的变化来减少这两个部门的碳排放。现有的分布式能源建筑协调控制方法要么以电价或可再生能源发电作为输入信号,要么在决策中采用优化方法,这些方法在现实环境中难以实现。本文旨在提出并验证一个易于部署的基于规则的碳响应控制框架,促进全电动建筑和电动汽车(ev)之间的协调。利用电网碳排放强度和局部光伏发电信号进行可控负荷的转移。在寒冷气候下,使用全电动混合用途社区模型进行了大量模拟,以验证排放、能耗、峰值需求和电动汽车日末充电状态(SOC)等指标的控制性能。我们的研究表明,在对能源成本、峰值需求和热舒适影响有限的情况下,可以实现4.5%至27.1%的年减排。此外,如果电动汽车车主将目标SOC降低21.2%以下,则可获得高达32.7%的电动汽车减排。
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
Advances in Applied Energy
Advances in Applied Energy Energy-General Energy
CiteScore
23.90
自引率
0.00%
发文量
36
审稿时长
21 days
期刊最新文献
Digitalization of urban multi-energy systems – Advances in digital twin applications across life-cycle phases Multi-scale electricity consumption prediction model based on land use and interpretable machine learning: A case study of China Green light for bidirectional charging? Unveiling grid repercussions and life cycle impacts Hydrogen production via solid oxide electrolysis: Balancing environmental issues and material criticality MANGOever: An optimization framework for the long-term planning and operations of integrated electric vehicle and building energy systems
×
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