Multi-stage scheduling for a smart home with solar PV and battery energy storage — A case study

In this paper, a multi-stage optimal scheduling and controlling approach has been studied which performs the scheduling of household appliances and management of local energy resources with respect to conflicting objectives. Firstly, a compromisation between computational complexity vs parameters uncertainty by considering multistage scheduling. Second, a choice for scheduling its shiftable appliances either by home energy management system (HEMS) or by coordinating/negotiating with aggregator for further benefit and overall peak reduction by decomposing this from its local energy resources management. Third, coordination between day-ahead scheduling and real-time demand response (DR) by considering time receding optimization of these strategies. Fourth, consideration of physical based load models for assessment of DR potential and actions. A typical home energy management problem is synthesized by assuming a rooftop solar PV, battery storage and ability to buy/sell electricity from/to aggregator. Simulation results shows that applied evolutionary techniques and the proposed strategy not only reduces energy consumption costs by responding to DR signals but also alleviates peak-to-average ratio and ensures the comfort preferences.