Methodology for integration of wind resource forecasts based on artificial neural networks-Reference-Cited by-同舟云学术

Methodology for integration of wind resource forecasts based on artificial neural networks

Published:2022-02-15 Issue:6 Volume:46 Page:8271-8287
ISSN:0363-907X
Container-title:International Journal of Energy Research
language:en
Short-container-title:Intl J of Energy Research

Author:

Carneiro Tatiane C.¹^ORCID,Ferreira Batista Lima Marcello A.²^ORCID,Marques de Carvalho Paulo C.³^ORCID,Guimarães Batista Josias²^ORCID,Fernández‐Ramírez Luis M.⁴^ORCID

Affiliation:

1. Environmental Engineering Course Federal University of Maranhão São Luís Brazil

2. Department of Industrial Mechatronics Federal Institute of Education, Science and Technology Limoeiro do Norte Brazil

3. Electrical Engineering Department Federal University of Ceará Fortaleza Brazil

4. Research Group in Sustainable and Renewable Electrical Technologies (PAIDI‐TEP023), Department of Electrical Engineering University of Cadiz, ETSI Algeciras Algeciras Spain

Funder

Conselho Nacional de Desenvolvimento Científico e Tecnológico

Publisher

Hindawi Limited

Subject

Energy Engineering and Power Technology,Fuel Technology,Nuclear Energy and Engineering,Renewable Energy, Sustainability and the Environment

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/er.7728

Reference36 articles.

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4. Impacts of Large-Scale Wind Penetration on Designing and Operation of Electric Power Systems

5. SpethV. Wind and solar portfolios and their impact on predictability: german case study 2010‐2011. Paper presented at: 11th International Workshop on Large‐Scale Integration of Wind Power into Power Systems as well as on Transmission Networks for Offshore Wind Power Plants; November 13‐15 2012; Lisbon Portugal. Anais […] Lisbon: Energynautics 2012 pp. 1–6. Disponível em:https://windintegrationworkshop.org/lisbon2012/index.html. Acesso em set. 10 2018.

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