Wind Power Forecasting With Entropy-Based Criteria Algorithms

• Type: Article in International Conference Proceedings Book
• Date: 2008

Authors

Ricardo Bessa (Author) FEUP; Vladimiro Miranda (Author) FEUP; João Gama (Author) Other

Conference proceedings International

Title: 2008 10TH INTERNATIONAL CONFERENCE ON PROBABILISTIC METHODS APPLIED TO POWER SYSTEMS

Pages: 106-112

10th International Conference on Probabilistic Methods Applied to Power Systems

Rincon, PR, MAY 25-29, 2008

Indexing

ISI Web of Knowledge - 0 Citations

Scopus - 5 Citations

Scientific classification

FOS: Engineering and technology > Electrical engineering, Electronic engineering, Information engineering

Other information

Authenticus ID: P-004-54H

Abstract (EN): 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. Renyi's Entropy is combined with a Parzen Windows estimation of the error pdf to form the basis of three criteria (MEE, MCC and MEEF) under which neural networks are trained. The results are favourably compared with the traditional minimum square error (MSE) criterion. Real case examples for two distinct wind parks are presented.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 7