Real-Time Pricing Method Based on Lyapunov for Stochastic and Electric Power Demand in Smart Grid

Real-time pricing in smart grid is an ideal power pricing mechanism, which has advantages such as peak shaving, energy saving, environmental protection, and the minimum cost of the power supply company. The rigid demand is not affected by the price, and the elastic demand is affected by the price. The elastic demand is random. Therefore, this paper is devoted to stochastic elasticity of electric demand in smart grid with real-time pricing algorithm. We adjust the user’s elastic demand through the real-time price, which also makes the grid load balancing, so as to achieve the grid utility maximization (GUM). We establish the stochastic elasticity of electric demand in smart grid model, design a subgradient dual decomposition algorithm based on Lyapunov to solve the problem. The simulation result shows that the algorithm is able to achieve the stable and load balancing of the power demand and queue and achieve the maximum utility of power grid.