End User
EMOT
Description
This service forecasts day-ahead charging behavior and energy demand patterns of private and public EV users based on historical usage data, contextual information (e.g., location, time-of-day), and exogenous variables such as weather. The model enables proactive load balancing, infrastructure planning, and tailored incentives by DSOs or aggregators.
Core Capabilities
Predictive & Prescriptive Analytics
Business Need
Accurate prediction of private EV-user behavior is critical for grid stability, efficient energy use, and planning smart charging strategies. The service supports DSOs in peak shaving and infrastructure upgrades, while enabling aggregators to better engage EV users in flexibility markets.
Key Performance Indicators
Recall on charging event detection
User segmentation clustering accuracy
Response time for inference
Data Provided
Smart meter and EVSE data (private, internal)
User demographic and behavioral data (anonymized, internal)
Weather forecast and traffic data (Open Meteo, public APIs)
TEF
TEF EV