Welfare Maximization under Real-time Pricing in Smart Grid Using PSO Algorithm

In this paper, we consider a smart power structure, include several residential and commercial subscribers whit an energy provider. Each subscriber is equipped with an energy consumption controller (ECC) unit as part of its smart meter. There is a two-way communication among smart meters and provider. This paper tries to propose a real-time pricing algorithm for smart grid. At the first, a value function for subscribers and a cost function for energy provider based on concepts of microeconomics are defined. Second, interactions among the ECC units and the energy provider are formulated as an optimization problem. Welfare function of the subscribers and the energy provider will be optimized using particle swarm optimization (PSO). The proposed real-time pricing algorithm manages the interactions among the subscribers and the energy provider, and finds the optimal energy consumption for each subscriber to maximize the aggregate welfare of all subscribers. Based on this proposed algorithm, each subscriber is eager to change his consumption pattern. In addition, a time of use (TOU) rate is considered for comparison.