A scoring rule-based mechanism for aggregate demand prediction in the smart grid

This paper presents a novel scoring rule-based strictly dominant incentive compatible mechanism that encourages agents to produce costly estimates of future events and report them truthfully to a centre. Whereas prior work has assumed a fixed budget for payment towards agents, this work makes use of prior information held by the centre and assumes a budget that is determined by the savings made through the use of the agents' information over the centre's own prior information. This mechanism is compared to a simple benchmark mechanism wherein the savings are divided equally among all home agents, and a cooperative solution wherein agents act to maximise social welfare. Empirical analysis is performed in which the mechanism is applied to a simulation of the smart grid whereby an aggregator agent must use home agents' information to optimally purchase electricity. It is shown that this mechanism achieves up to 77% of the social welfare achieved by the cooperative solution.