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Title: Improvement in Wind Power Forecasting Based on Information Entropy-Related Concepts
Authors: Ricardo Jorge Bessa
Vladimiro Miranda
João Gama
Issue Date: 2008
Abstract: This paper reports new results in adopting entropy concepts to the training of mappers such as neural networks to perform wind power prediction as a function of wind characteristics (mainly speed and direction) in wind parks connected to a power grid. It also addresses the differences relevant to power system operation between off-line and on-line training of neural networks. Real case examples are presented.
metadata.dc.type: conferenceObject
Appears in Collections:CPES - Articles in International Conferences

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