Efficient buyer groups with prediction-of-use electricity tariffs

Valentin Robu, Meritxell Vinyals, Alex Rogers, Nicholas R. Jennings

Research output: Contribution to journalArticleScientificpeer-review

11 Citations (Scopus)

Abstract

Current electricity tariffs do not reflect the real costs that a customer incurs to a supplier, as units are charged at the same rate, regardless of the consumption pattern. In this paper, we propose a prediction-of-use (POU) tariff that better reflects the predictability cost of a customer. Our tariff asks customers to pre-commit to a baseline consumption, and charges them based on both their actual consumption and the deviation from the anticipated baseline. First, we study, from a cooperative game theory perspective, the cost game induced by a single such tariff, and show customers would have an incentive to minimize their risk, by joining together when buying electricity as a grand coalition. Second, we study the efficient (i.e., cost-minimizing) structure of buying groups for the more realistic setting when multiple, competing POU tariffs are available. We propose a polynomial time algorithm to compute the efficient buyer groups, and validate our approach experimentally, using a large-scale data set of domestic consumers in the U.K.

Original languageEnglish
Article number7835716
Pages (from-to)4468-4479
Number of pages12
JournalIEEE Transactions on Smart Grid
Volume9
Issue number5
DOIs
Publication statusPublished - Sep 2018
Externally publishedYes

Keywords

  • Coalition formation
  • Collective switching
  • Cooperative game theory
  • Demand forecasting
  • Electricity tariffs

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