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DERMS

  • Advanced Forecasting

    ML-powered predictions for precision grid management
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Overview

Combine clustering, neural networks, decision trees, and traditional algorithms with real-time local weather data to deliver highly accurate forecasts—whether for individual DER assets or your entire VPP portfolio.

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Key Features

    • Ensemble Machine Learning: Leverage clustering, neural models, decision trees, and classical methods in a unified forecasting engine.

    • Asset-Level & Aggregate Forecasts: Generate predictions for each resource or roll up to portfolio-wide outlooks.

    • Real-Time Weather Integration: Continuously refine forecasts with live local meteorological data.

    • Automated Model Retraining: Adapt to changing conditions and usage patterns for ongoing accuracy.

    • Anomaly Detection: Identify unexpected deviations and trigger alerts for manual review or automated correction.


Benefits

    • Enhanced Operational Planning: Reduce uncertainty in dispatch and resource scheduling.

    • Risk Mitigation: Minimize forecasting errors that can lead to costly grid imbalances.

    • Optimized Asset Utilization: Align resource availability with actual grid and market needs.


How it works

    • Data Collection: Ingest DER telemetry and high-resolution weather feeds.

    • Model Development: Train and validate ML models using historical and real-time data.

    • Forecast Execution: Produce day-ahead, intra-day, and real-time predictions.

    • Live Adjustment: Integrate updated weather inputs to recalibrate forecasts on the fly.

    • Delivery & Reporting: Surface forecasts and performance analytics via dashboards and APIs.