Distributionally Robust Chance-Constrained Energy Management of Multi-Building Residential Apartment Complexes Using Wasserstein Metric

The decreasing costs of photovoltaic (PV) systems and battery storage, alongside the rapid rise of electric vehicles (EVs), present a unique opportunity to revolutionize energy use in apartment complexes. Electricity generation using PV and battery systems is currently more cost-effective and environmen-tally friendly than grid power which is often expensive. However, access to fast EV charging infrastructure remains limited in multi-building apartment complexes. To this end, this paper proposed a business model for deploying commercial PV-powered battery storage and EV fast chargers within apartment complexes in Orlando, Florida, operated by complex owners. By modeling the complex as a grid-connected microgrid, it aims to meet resi-dents' energy needs, provide backup power during emergencies, and introduce a profitable business model for property owners. To address PV power uncertainty, a distributionally robust chance-constrained optimization method using the Wasserstein metric is employed, ensuring robust and reliable operation. The techno-economic analysis reveals that EVs powered by PV and batteries are more cost-effective and environmentally friendly than gasoline vehicles and EV owners can save up to $100 per month by saving on fuel costs. The results also show that integrating PV and battery systems reduces operational costs, lowers emissions, increases resilience, and supports EV adoption while offering monetary benefits for property owners. These findings highlight a practical and sustainable framework for advancing clean energy use in residential complexes.