Develop and deploy algorithms for accurate electricity load forecasting
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®.
Examples and How To
- Database Toolbox™ (Product)
- MATLAB Compiler™ (Product)
- Deep Learning Toolbox™ (Product)
- Statistics and Machine Learning Toolbox™ (Product)
See also: energy production, algorithm development, desktop and web deployment, machine learning