Multiple-Profile Prediction-of-Use Games

Andrew Perrault
Proceedings of the Twenty-sixth International Joint Conference on Artificial Intelligence (IJCAI-17), Melbourne, Australia(2017), pp. 2486-2493


Prediction-of-use (POU) games (Vinyals et al., 2017) address the mismatch between energy supplier costs and the incentives imposed on consumers by fixed-rate electricity tariffs. However, the framework does not address how consumers should coordinate to maximize social welfare. To address this, we develop MPOU games, an extension of POU games in which agents report multiple acceptable electricity use profiles. We show that MPOU games share many attractive properties with POU games attractive (e.g., convexity). Despite this, MPOU games introduce new incentive issues that prevent the consequences of convexity from being exploited directly, a problem we analyze and resolve. We validate our approach with experimental results using utility models learned from real electricity use data. Note: An extended version of this paper appears as Chapter 17 of Autonomous Agents and Multiagent Systems: AAMAS 2017 Workshops, Best Papers, São Paulo, Brazil, Revised Selected Papers, pp.275-295, Springer Lecture Notes in AI, 2017.