Dynamic data aggregator unit selection in smart grid: An evolutionary game theoretic approach

In this paper, the problem of dynamic data aggregator unit selection in smart grid is studied using a dynamic evolutionary game theoretical model. The smart meters at the customer-end form the entire population of evolutionary game. The strategy of each smart meter evolves by choosing a different data aggregator unit in order to communicate with the meter data management system. Using the proposed dynamic data aggregator unit selection (DARTS) scheme, there exists stable solution for evolutionary equilibrium. Using the proposed DARTS scheme, the delay in service improves 82.3% and the communication load to each DAU reduces 69.23% than using without any game theoretic approach.