Very short term wind power prediction: A data mining approach

Michael Negnevitsky; Philip M. Johnson

doi:10.1109/pes.2008.4596604

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JOURNAL ARTICLE

Very short term wind power prediction: A data mining approach

Michael Negnevitsky Philip M. Johnson

Year: 2008 Vol: 3 Pages: 1-3

DOI: 10.1109/pes.2008.4596604

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Abstract

This panel paper reviews the available techniques for wind power forecasting in the very short term time frame out to 30 minutes ahead. A generic approach is proposed where the most appropriate techniques are selected based on data availability and data characteristics. The need for appropriate data generation for development and testing of a generic approach is also discussed.

Keywords:

Term (time) Wind power Computer science Frame (networking) Data mining Wind power forecasting Data modeling Electric power system Power (physics) Engineering Database Telecommunications

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Topics

Energy Load and Power Forecasting

Physical Sciences → Engineering → Electrical and Electronic Engineering

Electric Power System Optimization

Physical Sciences → Engineering → Electrical and Electronic Engineering

Computational Physics and Python Applications

Physical Sciences → Computer Science → Artificial Intelligence

Very short term wind power prediction: A data mining approach

Abstract

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Citation History

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