Affiliation:
1. Facultad de Energía, Universidad Nacional de Loja, Loja, Ecuador
Abstract
Accurate and reliable prediction of wind energy in the short term is of great importance for the efficient operation of wind farms. One of the procedures to search for, summarize, organize and synthesize existing information is a systematic literature review. In this article, we present a systematic literature review on the predictive models of wind energy, aiming to establish the baseline for the development of a short-term wind energy prediction model that employs artificial intelligence tools to be applied in the Villonaco Wind Power Plant. Following a systematic method of literature review, we have established 4 research questions and 37 scientific articles that answer the said questions. Consequently, we found that artificial neural networks are used more frequently for the prediction of wind energy, which highlights its use in the studies consulted for the results achieved compared with that of other methods.
Subject
Energy Engineering and Power Technology,Renewable Energy, Sustainability and the Environment
Cited by
42 articles.
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