Residential solar (PV) and electric vehicle (EV) are expected to increase, which leads to interruptions to the electric grid. Furthermore, there are different rates of PV and EV penetrations in neighborhoods. The questions are: (1) is the local utility required to have additional power sources due to the interruption? and (2) how do the unbalanced trends of PV and EV upon neighborhood impact on the grid?
My research will utilize machine learning to classify neighbors based on socioeconomic features and predict local population trends to estimate energy demands due to residential solar (PV) and electric vehicles (EV). The final results would be forecasting energy demand for each neighbor considering the expected PV and EV penetrations and the local population trend. This results will be matched with the local substations of the grid and their capacities meeting the energy demand and point out which neighbors would be mostly interrupted that the utility should pay careful attention.
Advisor: Hyun Woo Lee — Built Environment