Application of a game-theoretic energy management algorithm in a hybrid predictive-adaptive scenario

Demand response is considered as a technique to address Smart Grid requirements such as reduction of peak electricity production, improving stability and integration of renewable electricity. In this paper an automated DR mechanism is implemented by applying game-theoretic principles to the interaction and dependency of individual consumer requirements. Game theory has been used as an abstraction of consumer behavior to create an optimal load schedule in a day-ahead electricity market for a group of households. This abstraction is then taken further into a real-time scenario where automated home energy managing devices attempt to maintain Nash equilibrium under persistent varying unplanned electricity consumption.