Power companies rely on accurate electricity load forecasting to minimize financial risk and optimize operational efficiency and reliability.

Critical load forecasting tasks include:

• Automating data access from regional wholesale electricity markets
• Customizing models using nonlinear regression, nonparametric, and neural network techniques
• Calibrating models with historical predictors such as weather, seasonality, load, fuel price, and power price
• Deploying and integrating load forecasting algorithms into enterprise systems

For details on performing these tasks in a single modeling environment, see MATLAB^®.