A methodology for modeling the behavior of electricity prosumers within the smart grid

I. Lampropoulos, G.M.A. Vanalme, W.L. Kling

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

74 Citations (Scopus)
607 Downloads (Pure)

Abstract

Currently, there is a deep discussion going on among the power system society about the architecture of the future system. In practice, the smart grid concept is expected to be applied in various different forms and there will be a need for significant investments in both existing and new infrastructures. In this drastically evolving environment, policy makers and electric utilities are finding themselves in challenging positions to plan and prioritize methodologies and initiatives for future developments. Among others, decentralized power generation is gaining significance in liberalized electricity markets, and small size electricity consumers become also producers (prosumers). The scope of this paper is to map those factors (and their interactions) that influence the load profile, and provide a methodology for modeling the behavior of electricity prosumers. Simulations provide a time and cost effective way to vision the future power system and promote the most efficient solutions. The importance of including the behavior of a large amount of small size prosumers in power system simulations will be outlined, and this concept will be illustrated through an example of modeling car drivers' behavior in order to assess the grid impact of electric vehicles charging in Dutch residential areas.
Original languageEnglish
Title of host publicationProceedings of the 2010 IEEE PES Conference on Innovative Smart Grid Technologies Conference Europe (ISGT Europe ), 11-13 October 2010, Gothenburg, Sweden
Place of PublicationPiscataway
PublisherInstitute of Electrical and Electronics Engineers
Pages1-8
ISBN (Print)978-1-4244-8509-3
DOIs
Publication statusPublished - 2010

Fingerprint Dive into the research topics of 'A methodology for modeling the behavior of electricity prosumers within the smart grid'. Together they form a unique fingerprint.

Cite this