Optimal power demand management by aggregators using matching theory

This paper addresses optimal power demand management in the electricity market. First, we model the behavior of players, consumers, aggregators, and the market. Each consumer entity acts to maximize its own profit. The aggregator decides how much individual consumer power demand should be reduced if total power demand exceeds power generation constraints. We propose a method for an aggregator to make this decision using mechanism design and matching theory. Finally, we show that an algorithm can manage power demand and improve consumers' profits using simulation results.