Renewable energy design and optimization for a net-zero energy building integrating electric vehicles and battery storage considering grid flexibility

This study proposes a design management and optimization framework of renewable energy systems for advancing net-zero energy buildings integrated with electric vehicles and battery storage. A building load data augmentation model is developed to obtain the annual hourly load profile of a campus building based on the onsite collected data adopting the Gate Recurrent Unit neural network. A grid-protective energy management strategy of the solar photovoltaic (PV) power and storage system is proposed with novel assessment indicators including PV utilization ratio, load match ratio and grid flexibility factor. Multi-objective optimizations are conducted to identify optimal sizing of the renewable energy system and its interactive impact on balanced techno-economic performance. The research results indicate that the net-zero energy building achieves optimum performance with the sizing configuration of 1050 kW rooftop PV power, 300 electric vehicles and 450 kWh batteries. The vehicle-to-building interaction introducing vehicle discharge improves the load coverage (+12.08 %), grid flexibility (-29.63 %), annual electricity bill (-18.70 %) and levelized cost of energy (-6.24 %). The optimum net-zero energy building achieves good techno-economic-environmental feasibility regarding the load coverage (+16.22 %), grid flexibility performance (-58.48 %), annual electricity bill (-27.86 %), decarbonisation benefits (-34 times) and vehicle degradation. The developed design management and optimization framework of the renewable energy system provides a possible pathway for the typical campus building towards zero-carbon operations, and it also offers guidance and reference for stakeholders to develop similar carbon-neutral buildings.