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arXiv · 2412.00875

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

Hamed Haggi·James M. Fenton
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Abstract

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. Generating electricity via PV and batteries is currently cheaper and greener than relying on grid power, which is often expensive. Yet, residents in multi-building apartment complexes typically lack access to fast EV charging infrastructure. To this end, this paper investigates the feasibility and energy management of 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 residents' energy needs, provide backup power during emergencies, and introduce a profitable business model for property owners. To address PV power generation 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 that EV owners can save up to 100 dollars 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 a profitable business model for property owners. These findings highlight a practical and sustainable framework for advancing clean energy use in residential complexes.

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BibTeXRIS

Hamed Haggi, James M. Fenton. 2024-12-01. Distributionally Robust Chance-Constrained Energy Management of Multi-Building Residential Apartment Complexes Using Wasserstein Metric. https://arxiv.org/abs/2412.00875

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