Data-Driven Modelling and Optimal Control of Domestic Electric Water Heaters for Demand Response

Xingji Yu*, Shi You, Hanmin Cai, Laurent Georges, Peder Bacher

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Abstract

Electric water heater (EWH) is widely used to provide reliable and long-lasting domestic hot water to occupants in residential buildings. EWH has been widely recognized as an important source of building energy flexibility, which could benefit both the building occupants and the power system operators through various demand response (DR) programs. DR programs applied to EWHs are investigated in this paper. Optimal control strategies are developed to operate a portfolio of EWHs in order to reduce energy costs. A control-based model of EWH is developed using the data from field experiments and a statistical grey-box modelling approach (here using the CSTM-R package). The results show that the aggregated EWHs can optimize their heating schedule in order to reduce the overall cost without compromising the comfort of occupants.

Original languageEnglish
Title of host publicationProceedings of the 11th International Symposium on Heating, Ventilation and Air Conditioning : Buildings and Energy
EditorsZhaojun Wang, Fang Wang, Peng Wang, Chao Shen, Jing Liu, Yingxin Zhu
Volume3
PublisherSpringer
Publication date1 Jan 2020
Pages77-86
ISBN (Print)9789811395277
DOIs
Publication statusPublished - 1 Jan 2020
Event11th International Symposium on Heating, Ventilation and Air Conditioning - Harbin Institute of Technology, Harbin, China
Duration: 12 Jul 201915 Jul 2019
Conference number: 11

Conference

Conference11th International Symposium on Heating, Ventilation and Air Conditioning
Number11
LocationHarbin Institute of Technology
Country/TerritoryChina
CityHarbin
Period12/07/201915/07/2019
SeriesEnvironmental Science and Engineering
ISSN1863-5520

Keywords

  • Aggregation
  • Electric water heater
  • Experiment
  • Flexibility
  • Optimization

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