June 18 Data Science Community - Using AMI Interval Data to do EV Prediction

Join our panel of utility analytics professionals at the UAI Data Science Community on June 18, 2024 as they delve into the fascinating realm of utilizing Advanced Metering Infrastructure (AMI) Interval Data for Electric Vehicle (EV) prediction. As the energy landscape evolves, understanding the intersection of machine learning and deep learning with AMI data becomes crucial for accurate predictions. This panel discussion aligns with the UAI Data Science Community's commitment to collaborative exploration and knowledge sharing, providing a platform for attendees to learn from industry experts, share their own experiences, and collectively advance the understanding of machine learning and deep learning in the context of AMI data for EV predictions.

Key Discussion Points:

1. Innovative Use of Models Across Domains: Explore how machine learning models originally designed for one purpose, such as load forecasting, are adapted and leveraged for predicting EV behavior.

2. Utility-Specific Applications: Uncover the experiences of industry leaders like SRP, who utilize 15-minute interval reads to identify probable EV charging events, feeding into subsequent models for EV adoption over their service territory.

3. Implementation Challenges and Best Practices: Santee Cooper shares their ongoing efforts with 30-minute AMI data, providing valuable insights into the challenges faced and the best practices employed in implementing AMI interval data for EV predictions.

4. Production Deployment and Validation: Delve into the real-world aspects of deploying these models in production, validating their accuracy, and ensuring they meet the evolving demands of the utility sector.