Meaningful use of artificial intelligence can lead to savings for each energy market participant.
Mária Lucká
Senior researcher, KInIT
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CloseThe PREDICT project aims to:
Modern power systems are experiencing an increase in power demand and changes to complex interconnected power networks comprising conventional and renewable energy sources.
Maintaining a balance between generation and demand is important for the reliable operation of power networks. Besides forecasts of generation and demand, forecasts of transmission losses play an important role in the decision-making of system operators.
This project aimed to design and verify transmission loss prediction models using artificial intelligence methods. Predictions were based on historical data using state-of-the-art AI methods, such as support vector regression and a machine learning method based on gradient boosting and decision trees.
Enrichment of model attributes with a mix of weather measurements and data engineered attributes increased the overall prediction accuracy.
Application of the proposed methods for line loss prediction might help the system operators to reduce operating costs and ultimately save energy costs for all electricity market participants.
You can read a detailed report about the PREDICT here.
Mária Lucká
Senior researcher, KInIT
This project was supported by the Slovenská elektrizačná prenosová sústava Fund at the Pontis Foundation.
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