In the microgrid with high photovoltaic (PV) penetration, optimal sizing of battery energy storage system (BESS) has been a heated research topic in recent years. In the meanwhile, the high energy consumption of air-conditioned households is attracting more and more attention currently. In this paper, an optimal sizing method of BESS is developed for a smart microgrid with PV systems and air-conditioning resources. The proposed model is divided into two layers. In the first layer, the initial size of BESS is determined with consideration of photovoltaic output power and thermal buffering characteristics of air-conditioned households. In the second layer, the optimal size of BESS is proposed to minimize the system overall cost including BESS construction investment and microgrid system operation cost. The model is solved by differential evolutionary algorithm and iterative algorithms. Case studies demonstrate the effectiveness of the proposed method.

One of the key domains in smart cities is smart energy in which smart grid is a main focus. In recent years, with the development of smart grid, controllable air conditioning load participating in demand response projects and the application of renewable energy sources have drawn wide research interests. The integration of photovoltaic (PV) system and electric vehicles into the micro grid has also brought vitality to the stable operation of smart grids. In this paper, a novel control scheme is proposed to optimize the scheduling of building micro grid that integrate controllable air conditioner loads, PV panels and electric vehicles. The optimal operation problem is modeled and further converted into a mixed integer linear programming (MILP) problem whose objective function is minimizing the electricity cost of the building. The stochastic characteristics of electric vehicles are also considered in this paper to better model electric vehicle behaviors. Simulations are conducted on an office building micro grid and the simulation results verify the feasibility of proposed control strategy.