Optimal household appliances scheduling under day-ahead pricing and load-shaping demand response strategies

N.G. Paterakis, O. Erdinç, A.G. Bakirtzis, J.P.S. Catalao

Research output: Contribution to journalArticleAcademicpeer-review

180 Citations (Scopus)
6 Downloads (Pure)

Abstract

In this paper, a detailed home energy management system structure is developed to determine the optimal dayahead appliance scheduling of a smart household under hourly pricing and peak power-limiting (hard and soft power limitation)-based demand response strategies. All types of controllable assets have been explicitly modeled, including thermostatically controllable (air conditioners and water heaters) and nonthermostatically controllable (washing machines and dishwashers) appliances, together with electric vehicles (EVs). Furthermore, an energy storage system (ESS) and distributed generation at the end-user premises are taken into account. Bidirectional energy flow is also considered through advanced options for EV and ESS operation. Finally, a realistic test-case is presented with a sufficiently reduced time granularity being thoroughly discussed to investigate the effectiveness of the model. Stringent simulation results are provided using data gathered from real appliances and real measurements.

Original languageEnglish
Article number7114268
Pages (from-to)1509-1519
Number of pages11
JournalIEEE Transactions on Industrial Informatics
Volume11
Issue number6
DOIs
Publication statusPublished - 1 Dec 2015

Keywords

  • Demand response (DR)
  • Distributed generation (DG)
  • Electric vehicles (EVs)
  • Energy storage system (ESS)
  • Home energy management
  • Smart household

Fingerprint Dive into the research topics of 'Optimal household appliances scheduling under day-ahead pricing and load-shaping demand response strategies'. Together they form a unique fingerprint.

Cite this