An artificial neural network approach for short-term wind power forecasting in Portugal

• Type: Article in International Scientific Journal
• Date: 2009

Authors

Catalao, JPS (Author) Other; Pousinho, HMI (Author) Other; Mendes, VMF (Author) Other

Journal

Title: Engineering Intelligent Systems

Vol. 17

Pages: 5-11

ISSN: 1472-8915

Indexing

ISI Web of Knowledge - 56 Citations

Scopus - 55 Citations

Other information

Authenticus ID: P-003-MQX

Abstract (EN): This paper presents an artificial neural network approach for short-term wind power forecasting in Portugal. The increased integration of wind power into the electric grid, as nowadays occurs in Portugal, poses new challenges due to its intermittency and volatility. Hence, good forecasting tools play a key role in tackling these challenges. The accuracy of the wind power forecasting attained with the proposed approach is evaluated against persistence and ARIMA approaches, reporting the numerical results from a real-world case study.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 7