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Electricity peak shaving for commercial buildings using machine learning and vehicle to building (V2B) system by Mahdi Ghafoori; Moatassem Abdallah; Serena Kim is a scholarly article available to read on EtoBox.

What is Electricity peak shaving for commercial buildings using machine learning and vehicle to building (V2B) system about?

Reducing electricity peak demand is essential to maintain the balance between supply and demand side in electricity power markets, as well as reduce utility costs and environmental impacts. With growth in adoption of Electric Vehicles (EVs), there is an emerging opportunity to balance electrical power demand of buildings by storing electricity in EVs during low demand periods and discharging electricity into buildings during peak demand periods. Due to uncertainty in time and magnitude of peak demand, decision makers are always faced with a challenging task to identify optimal schedules for charging and discharging EVs to minimize peak electricity demand. This paper presents the development of a novel system that is capable of predicting day-ahead building electricity demand profile and identifying optimum schedule of charging and discharging EVs to minimize electricity peak demand. The system is designed to comply with planned EV trip schedules and minimum state of charge (SOC). The system consists of (1) machine Learning (ML) model to predict electrical power demand, and (2) demand management optimization model to identify optimal schedule for charging and discharging EVs. Four m

Author

Mahdi Ghafoori; Moatassem Abdallah; Serena Kim

Publisher

Elsevier BV

Published

2023

Language

EN