Sliding window games for cooperative building temperature control using a distributed learning method

2017, Volume 4, Issue 3

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Frontiers of Engineering Management >> 2017, Volume 4, Issue 3 doi: 10.15302/J-FEM-2017045

Sliding window games for cooperative building temperature control using a distributed learning method

. Viterbi School of Engineering, University of Southern California, Los Angeles, CA 90089, USA.. Department of Electrical and Computer Engineering, University of Alberta, Edmonton, AB T6G 1H9 , Canada.. Viterbi School of Engineering, University of Southern California, Los Angeles, CA 90089, USA; The Chinese University of Hong Kong, Shenzhen 518172, China

Accepted: 2017-09-26 Available online: 2017-10-30

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Abstract

In practice, an energy consumer often consists of a set of residential or commercial buildings, with individual units that are expected to cooperate to achieve overall optimization under modern electricity operations, such as time-of-use price. Global utility is decomposed to the payoff of each player, and each game is played over a prediction horizon through the design of a series of sliding window games by treating each building as a player. During the games, a distributed learning algorithm based on game theory is proposed such that each building learns to play a part of the global optimum through state transition. The proposed scheme is applied to a case study of three buildings to demonstrate its effectiveness.

Keywords

game theory ; demand response ; HVAC control ; multi-building system

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