In this session, attendees will hear about key learnings from Rappahannock Electric Cooperative's experience with detecting Level 2 EV residential charging and projecting load growth. With the rapid increase in electric vehicle adoption, understanding consumption patterns and accurately forecasting future demands is crucial for utilities. They will highlight the cooperative’s innovative approach to detection and data analysis, sharing insights on how they've optimized their strategies. Attendees will gain practical knowledge on leveraging data to identify EV charging patterns and anticipate grid impacts, offering a comprehensive roadmap to adapt and prepare for the changing energy landscape.

Attend this session and you will learn:

• Meta Data Adjustment: Learn how to refine machine learning-based models by adjusting meta data to improve the accuracy of EV detection.
• Cross-Checking Estimations: Understand the importance of validating load projections by cross-referencing data from various sources to ensure reliable and comprehensive analysis.