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Using Resevoir Computing for Wind Ramp Events Classification and Prediction

Authors:
Tatyana Mendonça Pio dos Santos
Mêuser Jorge Silva Valença

Keywords: ramp events; wind power forecast; reservoir computing; neural networks; mlp.

Abstract:
The increasing use of wind power as source of electricity motivates a continuous improvement of the accuracy of wind power forecasts. There is a considerable value in optimizing forecasts systems to provide the best performance in an environment where the wind power production increases and/or decreases by a large amount over a short period of time. This paper presents a model that uses Reservoir Computing to classify energy production variations in wind farms, known as ramp events. This method is compared with two other approaches: one that uses a MLP network and the other is based in Persistence. The tests were performed and the results are given for real cases, reaching up over 90% of success rate.

Pages: 87 to 93

Copyright: Copyright (c) IARIA, 2014

Publication date: May 25, 2014

Published in: conference

ISSN: 2308-4197

ISBN: 978-1-61208-340-7

Location: Venice, Italy

Dates: from May 25, 2014 to May 29, 2014