Case studies of a distributed building energy system incorporating with EVs considering effects of random charging behaviors and time-of-use pricing in electricity

Abstract

Reaching carbon neutrality needs global actions in various industry sectors. Building energy systems and electric vehicles (EV) are two main contributors to the decarbonization in the energy and transportation sectors, and the distributed building energy system with EV charging driven by renewable energy can greatly reduce carbon emissions. However, in the research about distributed building energy systems with EVs, the time-of-use (TOU) pricing of the grid and uncertain EVs charging loads (caused by random daily miles, departure/return time, and charging modes) are not considered simultaneously, which will influence the performances of the system. In this research, a distributed building energy system with EV is studied under the uncertain EV charging behaviors and TOU pricing of electricity, and the corresponding operation strategy is designed. The economic, environment, renewable energy penetration, and power trading performances are analyzed, and the crucial parameters of the system are optimized with three goals of minimum electricity cost, maximum renewable energy utilization ratio, and minimum net power purchase from the grid simultaneously based on the nondominated sorting genetic algorithm II (NSGA-II). The optimal system is analyzed from the perspective of energy flow and typical daily operation. The influences of the EV fast charging ratio and carbon tax on the optimal system are also studied. According to the results, the electricity cost, renewable energy utilization ratio, and net power purchase can be 0.0773 $ kWh −1 , 54.3%, and 172.65 MWh year −1 simultaneously. • Building energy system with uncertain EV charging and TOU pricing is studied. • LCOE , R self , and E p,net can reach 0.0773 $ kWh −1 , 54.3%, and 172.65 MWh year −1 . • The energy flow of the system year and day is analyzed in detail. • Influences of fast charging ratio and carbon tax on the optimal system are discussed.