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Abstract
Energy and load demand forecasting in short-horizons, over an interval ranging from one hour to one week, is crucial for on-line scheduling and security functions of power system. Many load forecasting methods have been developed in recent years which are usually complex solutions with many adjustable parameters. Best-matching models and their relevant parameters have to be determined in a search procedure. We propose a hybrid prediction model, where best exemplars from a possibly large set of different simple short-time load forecasting models are automatically selected based on their past performance by a multi-agent system with history-based weighting. The increase of prediction accuracy has been verified on real load data from the Polish power system.
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Authors (2)
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Dudek Grzegorz dr hab
- Politechnika Częstochowska Wydział Elektryczny Instytut Informatyki
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Keywords
Details
- Category:
- Conference activity
- Type:
- publikacja w wydawnictwie zbiorowym recenzowanym (także w materiałach konferencyjnych)
- Title of issue:
- Electric Power Engineering (EPE), 2016 17th International Scientific Conference on strony 1 - 8
- Language:
- English
- Publication year:
- 2016
- Bibliographic description:
- Opaliński A., Grzegorz D.: Electricity demand prediction by multi-agent system with history-based weighting// Electric Power Engineering (EPE), 2016 17th International Scientific Conference on/ : IEEE eXplore, 2016, s.1-8
- DOI:
- Digital Object Identifier (open in new tab) 10.1109/epe.2016.7521810
- Verified by:
- Gdańsk University of Technology
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