Collaborative Demand Response Optimization of Electric Vehicles and Storage Space Heating for Residential Peak Shaving

Residential Demand Response (DR) is believed to be a feasible tool for increasing the power system operational flexibility and efficiency. In this paper, we develop a demand response methodology for residential peak load shaving. We present an optimal demand response model for scheduling the EV and storage space heating load in tandem. Realistic case studies based on Finnish household data is performed to showcase the effectiveness of the proposed methodology and the results are thoroughly compared with business as usual case. The simulation result suggests that proposed methodology can bring economic savings to the customers and reduce the peak power problem as well.