Menglong Lu, Yongjun Sun, Wanbin Dou, Zhenjun Ma
Integrating electric vehicles (EVs) into net/nearly zero energy buildings (NZEBs) is crucial for fostering sustainable and resilient energy systems. However, this integration poses challenges due to stochastic EV usage patterns, uncertain renewable generation, and fluctuating building demand, complicating energy coordination among NZEBs, EVs, and the grid. Vehicle-to-building (V2B) technology enhances NZEB performance by enabling bidirectional energy flows, yet battery degradation from V2B and the need for appropriate compensation are often overlooked. This study proposes a flexible energy framework that integrates renewable energy, electricity storage, and EVs, while maintaining grid-friendly interactions. Additionally, a dynamic V2B pricing model is developed considering battery degradation. The simulation results demonstrated that the proposed framework could foster mutually beneficial outcomes for both NZEBs and EV owners. Its reliability and robustness were validated under various uncertainties, achieving an annual average operational profit of 1332.3 USD (0.0067 USD/kWh), a load match ratio of 80.1 %, and a carbon emission reduction of 49,431.8 kg (0.25 kg/kWh), which positively affected the operation of power grids. By facilitating the reliable and cost-effective integration of V2B technology into NZEBs under uncertainties, this study provides valuable insights into fostering an interconnected, intelligent, and resilient energy ecosystem. The findings offer practical guidance for scaling up sustainable energy trading within zero energy communities and cities, contributing to ongoing efforts toward the development of sustainable and low-carbon building energy futures. • Integrating EVs to enhance the energy flexibility and grid independence of NZEBs. • Fostering a mutually beneficial synergy between NZEBs and EV owners through V2B. • Developing a dynamic V2B pricing model accounting for EV battery degradation. • Grid-friendly energy management to advance NZEB development under uncertainties.