Optimizing the capacity of photovoltaic resources and battery storage in smart homes considering impact of scheduling of appliances and grid availability

Environmental concerns caused by the consumption of fossil fuels in electricity production, the need to improve energy efficiency and the development of competitive markets have increased the penetration of production resources, especially renewable resources, along with storage systems in buildings. In this regard, the Home Energy Management System (HEMS) has provided the opportunity to schedule and control resources and appliance in Smart Homes (SHs). Also, the capacity of resources can affect the performance of smart homes, especially under such uncertainties like resource, marker price, and grid failure. Therefore, the scheduling of SHs must be considered when determining the optimal capacity of resources and storage systems. This paper proposes a new framework for determining the optimal capacity of Photovoltaic (PV) panels and Battery Energy Storage Systems (BESSs) in smart homes, taking into account the scheduling of electrical resources and appliances. The objective is to minimize the total annual cost, considering uncertainties associated with PV power production, electricity market prices, and grid failure. The problem is modeled as a Mixed Integer Linear Programming (MILP). Simulation results show that prioritizing PV integration (1 kW) over storage expansion (0.5 kWh BESS) achieves superior cost and grid independence, and better demand profile.