Wind Power Plant Prediction by Using Neural Networks: Preprint

Research output: Contribution to conferencePaper

Abstract

This paper introduces a method of short-term wind power prediction for a wind power plant by training neural networks based on historical data of wind speed and wind direction. The model proposed is shown to achieve a high accuracy with respect to the measured data.
Original languageAmerican English
Number of pages9
StatePublished - 2012
EventIEEE Energy Conversion Conference and Exposition - Raleigh, North Carolina
Duration: 15 Sep 201220 Sep 2012

Conference

ConferenceIEEE Energy Conversion Conference and Exposition
CityRaleigh, North Carolina
Period15/09/1220/09/12

NREL Publication Number

  • NREL/CP-5500-55871

Keywords

  • complex-valued recurrent neural network
  • National Renewable Energy Laboratory (NREL)
  • NREL
  • probabilistic neural network
  • wind power plants
  • wind power prediction

Fingerprint

Dive into the research topics of 'Wind Power Plant Prediction by Using Neural Networks: Preprint'. Together they form a unique fingerprint.

Cite this