Optimizing Renewable Power Generation Forecasting for Utilities

Optimizing Renewable Power Generation Forecasting for Energy Company

Introduction: Powering Precision in Wind Energy Forecasting

A leading Indian wind energy generator with a total installed capacity of 5 GW faced growing operational and financial pressures due to inaccurate forecasting of power generation. Their reliance on conventional Qualified Coordinating Agencies (QCAs) led to consistent over-forecasting, impacting grid stability and incurring substantial deviation penalties. Recognizing the critical importance of forecast accuracy in wind energy operations, the client partnered with JBS to implement an AI/ML-powered forecasting system tailored to reduce penalties, improve scheduling efficiency, and unlock profitable trading opportunities.

Technician Scheduling Issues

Problem Statement: Over-Forecasting and Grid Code Violations

📈 Over-Predicted Output:
QCA forecasts frequently exceeded actual generation, destabilizing power schedules.

💸 Escalating Deviation Penalties:
Inaccurate forecasting led to non-compliance with grid norms (e.g., DSM), translating into high financial penalties.

🔄 Lack of Multi-Horizon Forecasting:
The QCA approach lacked precision across intraday, day-ahead, and long-term horizons.

📉 Missed Trading Opportunities:
Inflated forecasts disrupted the ability to participate profitably in energy markets.

Impact Section

Impact: Financial Drain and Inefficient Grid Operations

17% of annual costs attributed to forecasting errors and penalties.

Escalating Deviation Penalties: Inaccurate forecasting led to non-compliance with grid norms (e.g., DSM), translating into high financial penalties.

Lack of Multi-Horizon Forecasting: The QCA approach lacked precision across intraday, day-ahead, and long-term horizons.

Missed Trading Opportunities: Inflated forecasts disrupted the ability to participate profitably in energy markets.

Solution Section

Solution: AI-Driven, Compliance-Focused Forecasting Suite

JBS delivered a custom forecasting engine with core features including:

AI/ML Forecasting Models
Tailored statistical and machine learning algorithms built specifically for wind energy dynamics. Continuously trained using real-time SCADA and historical generation data.

Multi-Horizon Forecasting Framework
Separate forecast streams for intraday, day-ahead, and long-range scheduling. Enhanced flexibility for trading, dispatch, and compliance planning.

NWP + SCADA Fusion
Integrated Numerical Weather Prediction (NWP) models with on-ground SCADA data for precision tuning.

Compliance-Ready Outputs
Designed to align with CERC DSM regulations, reducing deviation and penalty exposure.

Business Benefits Section

Business Benefits: Measurable Gains from Smarter Forecasting

The implementation of the new forecasting solution yielded significant and quantifiable business benefits, directly impacting the client's financial performance: