Efficient mechanism for aggregate demand prediction in the smart grid

Péter Egri, József Váncza

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

This paper studies an aggregate demand prediction problem relevant in smart grids. In our model, an aggregator agent is responsible for eliciting the demand forecasts of a number of self-interested home agents and purchasing electricity for them. Forecasts are given in form of probability distributions, and generating them incurs costs proportional to their precision. The paper presents a novel scoring rule based mechanism which not only makes the agents interested in reporting truthfully, but also inspires them to achieve the socially optimal forecast precision. Hence, the aggregator agent is then able to optimise the total expected cost of electricity supply. Therefore the mechanism becomes efficient, contrarily to prior works in this field. Empirical studies show that it is beneficial to join to the mechanism compared to purchasing electricity directly from the market, even if the mechanism consists only of a few agents.

Original languageEnglish
Title of host publicationMultiagent System Technologies - 11th German Conference, MATES 2013, Proceedings
Pages250-263
Number of pages14
DOIs
Publication statusPublished - Oct 9 2013
Event11th German Conference on Multiagent System Technologies, MATES 2013 - Koblenz, Germany
Duration: Sep 16 2013Sep 20 2013

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8076 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other11th German Conference on Multiagent System Technologies, MATES 2013
CountryGermany
CityKoblenz
Period9/16/139/20/13

Keywords

  • Smart grid
  • distributed optimisation
  • information aggregation
  • mechanism design
  • scoring rules

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Egri, P., & Váncza, J. (2013). Efficient mechanism for aggregate demand prediction in the smart grid. In Multiagent System Technologies - 11th German Conference, MATES 2013, Proceedings (pp. 250-263). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8076 LNAI). https://doi.org/10.1007/978-3-642-40776-5-22