Smart Energy Management for Industrial Buildings: A Solar and EV Charging Case Study in Malta

This study examines energy management and optimization strategies for an industrial building complex in Malta, with a particular emphasis on solar energy estimation, State of Charge (SOC) prediction for electric vehicles (EVs), and the design of an integrated energy storage system. The building cluster is equipped with a 6 MW photovoltaic (PV) system, complemented by plans to expand PV coverage over a parking area designed to accommodate 100 vehicles, 25 of which are EVs. During operational hours, energy generated by rooftop PV systems is utilized to power the building complex, while the PV installations in the parking area supply energy for EV charging via Level 2 (L2) charging stations rated at 11 kW. MATLAB-based simulations were conducted to analyse energy production dynamics, EV charging profiles, and the utilization of surplus energy. The results indicate that the system generates sufficient energy to meet the demands of both the buildings and the EVs, with a weekly surplus of 123 MWh. Further analysis was performed to explore optimal strategies for utilizing this surplus energy, leading to the development of advanced optimization approaches. These include battery energy storage systems, hydrogen generation, and grid interaction mechanisms, all supported by sophisticated forecasting algorithms. A stochastic model was employed to simulate EV distribution patterns, revealing critical periods of high charging demand. The findings suggest that implementing slower charging rates could effectively mitigate peak load pressures on the system. This research highlights the potential for integrating renewable energy sources with EV charging infrastructure and energy storage solutions, providing valuable insights into sustainable practices and their economic feasibility. Future work will focus on enhancing real-time energy management systems using SIMULINK-based modeling to further refine operational efficiency and sustainability [1].