Game-theoretic based scheduling for demand-side management in 5G smart grids

Abstract

This paper addresses a game-theoretic based distributed appliance scheduling approach for demand-side management in smart grid. The game is played by a utility company and its subscribed residential users. The company monitors electricity demand online, manipulates the price of electricity for different hours to shape users' consumption pattern, and advertises it through Smart Grid infrastructure. Monitoring the electricity price in the market, users independently react by optimally scheduling their shiftable appliances to minimise their electricity expenses. We study day-ahead and quadratic pricing tariffs and discuss the best strategic response of users to each of these strategies that achieves Nash Equilibrium. The game serves as a distributed optimisation tool to minimise load variation in the grid. That is, even if users selfishly minimise their electricity expenses, they will automatically contribute to minimise peak-to-average ratio (PAR) of the aggregate demand, too. Simulation results confirm that adopting quadratic pricing tariff by company and quadratic programming scheduling by users is a Pareto-optimal strategy profile that can achieve a drastic PAR shaving while cutting users electricity expenses by half.