Coordinated Optimization of EVs and Multiple Buildings with Renewable Energy

This paper focuses on the jointly optimization of a micro-grid comprising electric vehicles (EVs) and buildings equipped with photovoltaic (PV) on the roof. The optimization problem of EVs and multiple buildings with renewable energy is formulated as a stochastic mixed integer linear programming (MILP) problem, in which bidirectional integration of EVs, building's demand response (DR) flexibility caused by outside air temperature (OAT) and thermostat setpoint temperature adjustment, and the uncertainty in PV power generation are fully taking into account. Scenario based method is adopted to deal with the randomness of PV generation and stochastic capacity requirements of EVs. The performance of jointly optimization is discussed based on case studies. Numerical results show that the aggregated EVs modeled as virtual storage system could not only significantly reduce the system cost and add building DR flexibility, but also could compensate the intermittency of renewable energy generation through peak shaving and valley filling.