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This paper proposes a fully distributed Demand-Side Management system forSmart Grid infrastructures, especially tailored to reduce the peak demand ofresidential users. In particular, we use a dynamic pricing strategy, whereenergy tariffs are function of the overall power demand of customers. Weconsider two practical cases: (1) a fully distributed approach, where eachappliance decides autonomously its own scheduling, and (2) a hybrid approach,where each user must schedule all his appliances. We analyze numerically thesetwo approaches, showing that they are characterized practically by the sameperformance level in all the considered grid scenarios. We model the proposedsystem using a non-cooperative game theoretical approach, and demonstrate thatour game is a generalized ordinal potential one under general conditions.Furthermore, we propose a simple yet effective best response strategy that isproved to converge in a few steps to a pure Nash Equilibrium, thusdemonstrating the robustness of the power scheduling plan obtained without anycentral coordination of the operator or the customers. Numerical results,obtained using real load profiles and appliance models, show that thesystem-wide peak absorption achieved in a completely distributed fashion can bereduced up to 55%, thus decreasing the capital expenditure (CAPEX) necessary tomeet the growing energy demand.

A Distributed Demand-Side Management Framework for the Smart Grid