A comparison of sizing methods for a long-term renewable hybrid system. Case study: Galapagos Islands 2031

This research compares different sizing methods to improve the current autonomous hybrid system in the Galapagos Islands in the year 2031, analyzing the loss of power supply probability (LPSP). In the first place, the energy consumed in the islands for the year 2031 has been obtained, using ANN arti...

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Autores: Cano-Ortega, Antonio, Arévalo, Paul, Jurado-Melguizo, Francisco
Tipo de recurso: artículo
Estado:Versión aceptada para publicación
Fecha de publicación:2021
País:España
Institución:Universidad de Jaén
Repositorio:RUJA. Repositorio Institucional de la Producción Científica de la Universidad de Jaén
OAI Identifier:oai:ruja.ujaen.es:10953/6162
Acceso en línea:https://pubs.rsc.org/en/content/articlelanding/2021/se/d1se00078k
https://hdl.handle.net/10953/6162
Access Level:acceso abierto
Palabra clave:LPSP
Pattern Search
Simulink Design Optimization
Neuronal Network
Pumped Storage
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spelling A comparison of sizing methods for a long-term renewable hybrid system. Case study: Galapagos Islands 2031Cano-Ortega, AntonioArévalo, PaulJurado-Melguizo, FranciscoLPSPPattern SearchSimulink Design OptimizationNeuronal NetworkPumped Storage621.35This research compares different sizing methods to improve the current autonomous hybrid system in the Galapagos Islands in the year 2031, analyzing the loss of power supply probability (LPSP). In the first place, the energy consumed in the islands for the year 2031 has been obtained, using ANN artificial neural networks with Matlab, from fundamental parameters in the design of a multilayer perceptron neural network model. Second, the methods used for sizing the system are HOMER Pro and Simulink Design Optimization (SDO). The dynamic models of the different components of the hybrid system have been made in MATLAB/Simulink. The proposed hybrid system is composed of PV photovoltaic and WT wind, and lead-acid batteries, hydraulic pumping, and diesel generator as storage and support systems. Then, in order to design a sustainable system, a hybrid system has been dimensioned with renewable energy sources of an appropriate size. The LPSP values obtained are below 0.09% and 0.22%, which shows that the system has been optimally dimensioned. In addition, a cost analysis has been carried out, the values obtained from NPC and COE according to HOMER Pro are $ 183,810,067 and 0.26 $/kWh, and $ 233,385,656 and 0.25 $/kWh and using SDO are $ 148,523,110 and 0.25 $/kWh, $ 189,576,556 and 0.24 $/kWh for strategies I and II respectively of the proposed hybrid system. The data obtained shows that SDO's Latin Hypercube algorithm achieves a better optimization compared to HOMER Pro.Abstract text goes here. The abstract should be a single paragraph that summarises the content of the article.The Royal Society of Chemistry202520252021info:eu-repo/semantics/articleinfo:eu-repo/semantics/acceptedVersionapplication/pdfhttps://pubs.rsc.org/en/content/articlelanding/2021/se/d1se00078khttps://hdl.handle.net/10953/6162reponame:RUJA. Repositorio Institucional de la Producción Científica de la Universidad de Jaéninstname:Universidad de JaénInglésSustainable Energy & FuelsCC0 1.0 Universalhttp://creativecommons.org/publicdomain/zero/1.0/info:eu-repo/semantics/openAccessoai:ruja.ujaen.es:10953/61622026-06-24T12:41:07Z
dc.title.none.fl_str_mv A comparison of sizing methods for a long-term renewable hybrid system. Case study: Galapagos Islands 2031
title A comparison of sizing methods for a long-term renewable hybrid system. Case study: Galapagos Islands 2031
spellingShingle A comparison of sizing methods for a long-term renewable hybrid system. Case study: Galapagos Islands 2031
Cano-Ortega, Antonio
LPSP
Pattern Search
Simulink Design Optimization
Neuronal Network
Pumped Storage
621.35
title_short A comparison of sizing methods for a long-term renewable hybrid system. Case study: Galapagos Islands 2031
title_full A comparison of sizing methods for a long-term renewable hybrid system. Case study: Galapagos Islands 2031
title_fullStr A comparison of sizing methods for a long-term renewable hybrid system. Case study: Galapagos Islands 2031
title_full_unstemmed A comparison of sizing methods for a long-term renewable hybrid system. Case study: Galapagos Islands 2031
title_sort A comparison of sizing methods for a long-term renewable hybrid system. Case study: Galapagos Islands 2031
dc.creator.none.fl_str_mv Cano-Ortega, Antonio
Arévalo, Paul
Jurado-Melguizo, Francisco
author Cano-Ortega, Antonio
author_facet Cano-Ortega, Antonio
Arévalo, Paul
Jurado-Melguizo, Francisco
author_role author
author2 Arévalo, Paul
Jurado-Melguizo, Francisco
author2_role author
author
dc.subject.none.fl_str_mv LPSP
Pattern Search
Simulink Design Optimization
Neuronal Network
Pumped Storage
621.35
topic LPSP
Pattern Search
Simulink Design Optimization
Neuronal Network
Pumped Storage
621.35
description This research compares different sizing methods to improve the current autonomous hybrid system in the Galapagos Islands in the year 2031, analyzing the loss of power supply probability (LPSP). In the first place, the energy consumed in the islands for the year 2031 has been obtained, using ANN artificial neural networks with Matlab, from fundamental parameters in the design of a multilayer perceptron neural network model. Second, the methods used for sizing the system are HOMER Pro and Simulink Design Optimization (SDO). The dynamic models of the different components of the hybrid system have been made in MATLAB/Simulink. The proposed hybrid system is composed of PV photovoltaic and WT wind, and lead-acid batteries, hydraulic pumping, and diesel generator as storage and support systems. Then, in order to design a sustainable system, a hybrid system has been dimensioned with renewable energy sources of an appropriate size. The LPSP values obtained are below 0.09% and 0.22%, which shows that the system has been optimally dimensioned. In addition, a cost analysis has been carried out, the values obtained from NPC and COE according to HOMER Pro are $ 183,810,067 and 0.26 $/kWh, and $ 233,385,656 and 0.25 $/kWh and using SDO are $ 148,523,110 and 0.25 $/kWh, $ 189,576,556 and 0.24 $/kWh for strategies I and II respectively of the proposed hybrid system. The data obtained shows that SDO's Latin Hypercube algorithm achieves a better optimization compared to HOMER Pro.Abstract text goes here. The abstract should be a single paragraph that summarises the content of the article.
publishDate 2021
dc.date.none.fl_str_mv 2021
2025
2025
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/acceptedVersion
format article
status_str acceptedVersion
dc.identifier.none.fl_str_mv https://pubs.rsc.org/en/content/articlelanding/2021/se/d1se00078k
https://hdl.handle.net/10953/6162
url https://pubs.rsc.org/en/content/articlelanding/2021/se/d1se00078k
https://hdl.handle.net/10953/6162
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Sustainable Energy & Fuels
dc.rights.none.fl_str_mv CC0 1.0 Universal
http://creativecommons.org/publicdomain/zero/1.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv CC0 1.0 Universal
http://creativecommons.org/publicdomain/zero/1.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv The Royal Society of Chemistry
publisher.none.fl_str_mv The Royal Society of Chemistry
dc.source.none.fl_str_mv reponame:RUJA. Repositorio Institucional de la Producción Científica de la Universidad de Jaén
instname:Universidad de Jaén
instname_str Universidad de Jaén
reponame_str RUJA. Repositorio Institucional de la Producción Científica de la Universidad de Jaén
collection RUJA. Repositorio Institucional de la Producción Científica de la Universidad de Jaén
repository.name.fl_str_mv
repository.mail.fl_str_mv
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