Demand Forecasting: Predicting the Future of Energy Use
Master the art and science of demand forecasting, the critical foundation that enables effective demand response programs and helps utilities balance supply and demand
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Section 3 of 5Why Accurate Forecasting Matters
Demand forecasting is the backbone of effective demand response. Without accurate predictions of future electricity demand, utilities cannot properly plan demand response events or ensure grid reliability.
Forecasting Challenges
- • Weather variability affects demand patterns
- • Economic factors influence consumption
- • Behavioral changes from DR programs
- • Integration of distributed energy resources
Forecasting Methods
From simple statistical methods to advanced machine learning algorithms, explore different approaches to predicting electricity demand.
Forecasting Method Comparison
Select Forecasting Method
24-Hour Demand Forecast
Simple Average
Uses average of past values
Economic Impact of Forecast Accuracy
See how forecasting accuracy directly affects the financial performance and effectiveness of demand response programs.
Forecast Impact Calculator
See how forecasting accuracy affects the economic value and effectiveness of demand response programs.
Annual Impact
Forecasting Best Practices
Data Quality
- • High-resolution smart meter data
- • Weather and temperature data
- • Economic indicators and trends
- • Calendar and holiday information
Model Validation
- • Cross-validation techniques
- • Out-of-sample testing
- • Rolling forecast evaluation
- • Continuous model improvement
Uncertainty Quantification
- • Prediction intervals
- • Ensemble forecasting methods
- • Scenario-based planning
- • Risk-adjusted decision making
Continuous Improvement
- • Regular model retraining
- • Performance monitoring
- • Stakeholder feedback integration
- • Technology and methodology updates