A Dynamic Energy Trading and Management Algorithm for the Elastic End-User in Smart Grids

The smart grid, as the next-generation of electricity grid, is characterized with new features, such as dynamic electricity price distributed renewable energy sources, and two-way energy transmission between users and the grid. Technically, it offers an opportunity for end-users to make profits by purchasing/selling energy from/to the grid in low/high electricity prices. In this paper, we investigate the profit maximization problem for an elastic end-user equipped with renewable energy devices and a battery, which allow energy demands to be met within a certain delay time. First, we establish a novel two-way energy trading model, by considering the reduction of the number of battery charge and discharge cycles to extend the battery lifetime. Then, a dynamic energy trading and management algorithm is proposed based on the Lyapunov optimization. In theory, the proposed algorithm can achieve optimal performance without any prior knowledge of the energy demand, the energy harvesting, and the energy arrival process. Meanwhile it ensures that the maximum delay of energy demand cannot exceed a given value. Finally, simulations are carried out and results demonstrate that the proposed algorithm is superior to direct trading and inelastic energy demand trading. The benefits of different battery capacities to the end-user are also analyzed to enable choosing a battery size depending on their cost requirements.