Computational tool for analysis of vehicle-to-home as home backup solution

Power outages have been increasing due to major weather events, such as hurricanes, wildfires, and winter storms. Furthermore, when the electric grid is down, rooftop solar photovoltaic (PV) panels cannot operate without battery storage or another way to isolate the home from the bulk grid. Meanwhile, battery electric vehicles (BEVs) and plug-in hybrid electric vehicles (PHEVs) with bidirectional charging can power a home during an outage, a premise called vehicle -to -home (V2H). Electric vehicles typically have much larger batteries than residential behind -the -meter (BTM) battery energy storage systems. This paper explores V2H capabilities during power outages by use of an open -source computational tool developed in Microsoft Excel and Python. The user selects inputs of weather and home size as well as backup source and home load characteristics into the Excel interface. A Python mixed -integer linear programming (MILP) optimization model schedules loads while maximizing PV usage and battery state -of -charge (SoC) and minimizing battery and generator fuel use. The backup duration and electricity consumption of desired load are calculated. The tool was used to execute 504 simulations with differing home size, weather condition, backup source configuration, and load configuration. On average, the backup duration can be increased by about a factor of 9 (from 2.7 to 25 days) by reducing consumption to only critical loads. For certain weather conditions, homes with solar panels can potentially be powered for unlimited duration with enough battery storage.