Probabilistic Quantification of Potentially Flexible Residential Demand

Konstantinos Kouzelis, Iker Diaz de Cerio Mendaza, Birgitte Bak-Jensen

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

11 Citations (Scopus)

Abstract

The balancing of power systems with high penetration of renewable energy is a serious challenge to be faced in the near future. One of the possible solutions, recently capturing a lot of attention, is demand response. Demand response can only be achieved by power consumers holding loads which allow them to modify their normal power consumption pattern, namely flexible consumers. However flexibility, despite being constantly mentioned, is usually not properly defined and even rarer quantified. This manuscript introduces a methodology to identify and quantify potentially flexible demand of residential consumers. The procedure is based on non-flexible consumer clustering and subsequent statistical analysis. Consequently, the power consumption pattern of a flexible consumer is compared to a 3D probability distribution created by the previously referred methodology. The results show a strong relationship between the amount of potential flexibility and the probability of providing it. Finally, it is concluded that residential flexibility is most likely to be offered during transitions between summer and winter.
Original languageEnglish
Title of host publicationProceedings of the IEEE Power & Energy Society General Meeting, PES 2014
Number of pages5
PublisherIEEE Press
Publication date2014
ISBN (Print)9781479964161
ISBN (Electronic)9781479964147
DOIs
Publication statusPublished - 2014
EventIEEE Power & Energy Society General Meeting, PES 2014 - Washington, United States
Duration: 27 Jul 201431 Jul 2014

Conference

ConferenceIEEE Power & Energy Society General Meeting, PES 2014
Country/TerritoryUnited States
CityWashington
Period27/07/201431/07/2014

Keywords

  • Flexibility
  • Active Load
  • Heat Pump
  • Residential Demand
  • Demand Response.

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