A Review of the Use of Artificial Neural Network Models for Energy and Reliability Prediction. A Study of the Solar PV, Hydraulic and Wind Energy Sources
| Autor: | Juan Francisco Gómez Fernández, Adolfo Crespo Márquez, Fernando Agustín Olivencia Polo, Jesús Ferrero Bermejo |
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| Přispěvatelé: | Universidad de Sevilla. Departamento de Organización Industrial y Gestión de Empresas I |
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
Artificial neural network
Renewable energy Artificial intelligence Computer science 020209 energy 02 engineering and technology 010501 environmental sciences Asset (computer security) 01 natural sciences lcsh:Technology lcsh:Chemistry 0202 electrical engineering electronic engineering information engineering General Materials Science survey Survey Instrumentation lcsh:QH301-705.5 Reliability (statistics) 0105 earth and related environmental sciences Fluid Flow and Transfer Processes Wind power business.industry lcsh:T Process Chemistry and Technology Photovoltaic system General Engineering artificial intelligence Industrial engineering renewable energy lcsh:QC1-999 Computer Science Applications Electricity generation lcsh:Biology (General) lcsh:QD1-999 lcsh:TA1-2040 business Energy source lcsh:Engineering (General). Civil engineering (General) artificial neural network lcsh:Physics |
| Zdroj: | Applied Sciences, Vol 9, Iss 9, p 1844 (2019) idUS. Depósito de Investigación de la Universidad de Sevilla instname |
| ISSN: | 2076-3417 |
| Popis: | The generation of energy from renewable sources is subjected to very dynamic changes in environmental parameters and asset operating conditions. This is a very relevant issue to be considered when developing reliability studies, modeling asset degradation and projecting renewable energy production. To that end, Artificial Neural Network (ANN) models have proven to be a very interesting tool, and there are many relevant and interesting contributions using ANN models, with different purposes, but somehow related to real-time estimation of asset reliability and energy generation. This document provides a precise review of the literature related to the use of ANN when predicting behaviors in energy production for the referred renewable energy sources. Special attention is paid to describe the scope of the different case studies, the specific approaches that were used over time, and the main variables that were considered. Among all contributions, this paper highlights those incorporating intelligence to anticipate reliability problems and to develop ad-hoc advanced maintenance policies. The purpose is to offer the readers an overall picture per energy source, estimating the significance that this tool has achieved over the last years, and identifying the potential of these techniques for future dependability analysis. Unión Europea H2020-MSCA-RISE-2014 Ministerio de Economía y Competitividad DPI2015-70842-R |
| Databáze: | OpenAIRE |
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