Optimal scheduling method of regenerative electric heating for emergency residential building heating: An affine arithmetic-based model predictive control approach

IF 1.6 Q4 ENERGY & FUELS IET Energy Systems Integration Pub Date : 2022-10-17 DOI:10.1049/esi2.12082
Jiarui Zhang, Yunfei Mu, Zeqing Wu, Zhe Liu, Yi Gao, Hongjie Jia, Hairun Li
{"title":"Optimal scheduling method of regenerative electric heating for emergency residential building heating: An affine arithmetic-based model predictive control approach","authors":"Jiarui Zhang,&nbsp;Yunfei Mu,&nbsp;Zeqing Wu,&nbsp;Zhe Liu,&nbsp;Yi Gao,&nbsp;Hongjie Jia,&nbsp;Hairun Li","doi":"10.1049/esi2.12082","DOIUrl":null,"url":null,"abstract":"<p>Residential heating faces the challenge of heating interruption when an electric power outage occurs. As a promising heating electrification form, regenerative electric heating (REH) equipped with thermal energy storage (TES) has the flexibility of maintaining the building indoor temperature within the desired range during power outages and reducing the operation cost during normal operation states. However, the allocation and scheduling of the limited thermal energy in TES for the above two purposes is impacted by many uncertainties, for example, outdoor temperature, irradiation, and duration of power outages. Overestimation of the thermal energy required for power outages in the TES can improve the heating supply reliability, but it will also increase the REH operation cost to some extent, and vice versa. To address this problem, an affine arithmetic-based model predictive control approach (AA-MPC) for an optimal REH scheduling method is proposed to balance the heating supply reliability during power outages and operation economy of REH at the same time. An REH-based residential building energy system model is developed to describe the building thermal load associated with the outdoor temperature and irradiation. Then, the required thermal energy for emergency building heating provided by the hot water tank (HWT) is determined using the minimum thermal demand of residents during a power outage, which is constrained by the minimum comfort temperature threshold. Based on this, an AA-MPC approach that takes the thermal energy for emergency building heating as a time-varying constraint of the HWT is developed to determine the optimal REH scheduling that considers emergency residential building heating under the above uncertainties. Numerical studies show that the proposed method can maintain minimum thermal demand for at least 2 h when a power outage occurs under uncertainties. At the same time, it can reduce the impact of uncertainties on the operation cost and reduce economic problems caused by emergency heating to a certain extent. Compared to the interval arithmetic-based model predictive control approach, the operation cost intervals of the proposed method are reduced by 57.3%, 0.3%, and 32.5% under low, middle, and high prediction error levels respectively.</p>","PeriodicalId":33288,"journal":{"name":"IET Energy Systems Integration","volume":null,"pages":null},"PeriodicalIF":1.6000,"publicationDate":"2022-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/esi2.12082","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IET Energy Systems Integration","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1049/esi2.12082","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
引用次数: 2

Abstract

Residential heating faces the challenge of heating interruption when an electric power outage occurs. As a promising heating electrification form, regenerative electric heating (REH) equipped with thermal energy storage (TES) has the flexibility of maintaining the building indoor temperature within the desired range during power outages and reducing the operation cost during normal operation states. However, the allocation and scheduling of the limited thermal energy in TES for the above two purposes is impacted by many uncertainties, for example, outdoor temperature, irradiation, and duration of power outages. Overestimation of the thermal energy required for power outages in the TES can improve the heating supply reliability, but it will also increase the REH operation cost to some extent, and vice versa. To address this problem, an affine arithmetic-based model predictive control approach (AA-MPC) for an optimal REH scheduling method is proposed to balance the heating supply reliability during power outages and operation economy of REH at the same time. An REH-based residential building energy system model is developed to describe the building thermal load associated with the outdoor temperature and irradiation. Then, the required thermal energy for emergency building heating provided by the hot water tank (HWT) is determined using the minimum thermal demand of residents during a power outage, which is constrained by the minimum comfort temperature threshold. Based on this, an AA-MPC approach that takes the thermal energy for emergency building heating as a time-varying constraint of the HWT is developed to determine the optimal REH scheduling that considers emergency residential building heating under the above uncertainties. Numerical studies show that the proposed method can maintain minimum thermal demand for at least 2 h when a power outage occurs under uncertainties. At the same time, it can reduce the impact of uncertainties on the operation cost and reduce economic problems caused by emergency heating to a certain extent. Compared to the interval arithmetic-based model predictive control approach, the operation cost intervals of the proposed method are reduced by 57.3%, 0.3%, and 32.5% under low, middle, and high prediction error levels respectively.

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
住宅紧急采暖蓄热优化调度方法:基于仿射算法的模型预测控制方法
住宅供暖面临着停电时供热中断的挑战。蓄热式电采暖(REH)作为一种很有前途的采暖电气化形式,具有在停电时将建筑室内温度保持在理想范围内的灵活性,同时在正常运行状态下降低运行成本。然而,为了上述两种目的,在TES中有限的热能的分配和调度受到许多不确定因素的影响,例如室外温度、辐射、停电时间等。在TES中过高估计停电所需热能可以提高供热可靠性,但也会在一定程度上增加REH运行成本,反之亦然。针对这一问题,提出了一种基于仿射算法的REH优化调度方法(AA-MPC),以平衡REH在停电时的供热可靠性和运行经济性。建立了基于reh的住宅建筑能源系统模型,描述了建筑热负荷与室外温度和辐照的关系。然后,在最小舒适温度阈值的约束下,利用居民在停电时的最小热需求来确定热水箱(HWT)提供的应急建筑采暖所需的热能。在此基础上,提出了将建筑应急采暖热能作为HWT的时变约束的AA-MPC方法,以确定上述不确定性下考虑住宅应急采暖的REH最优调度。数值研究表明,该方法可以在不确定停电情况下保持至少2 h的最小热需求。同时可以减少不确定因素对运行成本的影响,在一定程度上减少应急供热带来的经济问题。与基于区间算法的模型预测控制方法相比,该方法在低、中、高预测误差水平下的运行成本区间分别缩短了57.3%、0.3%和32.5%。
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
IET Energy Systems Integration
IET Energy Systems Integration Engineering-Engineering (miscellaneous)
CiteScore
5.90
自引率
8.30%
发文量
29
审稿时长
11 weeks
期刊最新文献
Experimental and model analysis of the thermoelectric characteristics of serial arc in prismatic lithium‐ion batteries Low‐carbon economic operation of multi‐energy microgrid based on multi‐level robust optimisation Anti‐interference lithium‐ion battery intelligent perception for thermal fault detection and localization A reinforcement learning method for two-layer shipboard real-time energy management considering battery state estimation Estimation and prediction method of lithium battery state of health based on ridge regression and gated recurrent unit
×
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