Paper on Load Forecasting During the COVID-19 Pandemic Using Mobility Data

We recently posted a preprint Using Mobility for Load Forecasting During the COVID-19 Pandemic on Arxiv. We proposed a novel load forecasting method to use the mobility data and transfer learning to help forecast the volatile load during the pandemic. Code and dataset are found here. This result is also featured in VentureBeat.