Utilizing renewable energy resources by adopting DSM techniques and storage facilities

A common assumption in the existing literature on energy consumption scheduling in smart grid is that users are aware in advance of their daily energy consumption needs. Therefore, most existing studies along this line of research have been inherently deterministic, e.g., see [1]-[3]. However, this assumption may not hold in practice. In particular, the energy consumption scheduling (ECS) devices may face load uncertainty. If a user is equipped with a behind-the-meter renewable generator, then the optimal operation of ECS devices becomes even more challenging due to combined load and supply uncertainties. Therefore, in this paper, we formulate a stochastic optimization problem to operate an ECS device in a residential unit that is equipped with a behind-the-meter renewable generator and a local battery bank. In our problem formulation, we consider different sets of must-run and controllable appliances. Our design only requires knowledge of some estimates of the users' future demand. To reduce computational complexity, we approximate the expected load in the upcoming time slots by adopting the certainty equivalent approximation technique. Simulation results show that the proposed energy consumption scheduling algorithm can tackle the uncertainties in load and supply and it can benefit both users and the utility companies.