EVALUATION OF HYBRID SOLAR PHOTOVOLTAIC-GAS TURBINE SYSTEM USING ARTIFICIAL NEURAL NETWORK

Solar energy one of the most available power source in Malaysia. The economic impact was the main target of this investigation with the fulfilment of the technical requirements of the Universiti Teknologi PETRONAS (UTP) Microgrid (MG). Since hybrid Solar Photovoltaic (SPV) and Gas Turbine Generator...

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Main Author: MOHAMED SHAABAN KHAMIS, MOHAMED ATEF
Format: Thesis
Language: English
Institution: Universiti Teknologi Petronas
Record Id / ISBN-0: utp-utpedia.20513 /
Published: 2020
Subjects:
TK Electrical engineering. Electronics Nuclear engineering
Online Access: http://utpedia.utp.edu.my/20513/1/Mohamed%20Atef%20Mohamed%20Shaaban_15002244.pdf
http://utpedia.utp.edu.my/20513/
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spelling utp-utpedia.205132021-08-30T16:29:56Z http://utpedia.utp.edu.my/20513/ EVALUATION OF HYBRID SOLAR PHOTOVOLTAIC-GAS TURBINE SYSTEM USING ARTIFICIAL NEURAL NETWORK MOHAMED SHAABAN KHAMIS, MOHAMED ATEF TK Electrical engineering. Electronics Nuclear engineering Solar energy one of the most available power source in Malaysia. The economic impact was the main target of this investigation with the fulfilment of the technical requirements of the Universiti Teknologi PETRONAS (UTP) Microgrid (MG). Since hybrid Solar Photovoltaic (SPV) and Gas Turbine Generator (GTG) (H-PVGTGs) will be considered in this research, the former models’ accuracy (in hybrid SPV optimization techniques) is very important. The least error for the existing mathematical models for SPV is 5.5% and this figure hypothetically can be further improved by using Artificial Intelligent (AI) method. There is always potential Annualized Total Life Cycle Cost (ATLCC) to be improved for the feasibility options. 2020-06 Thesis NonPeerReviewed application/pdf en http://utpedia.utp.edu.my/20513/1/Mohamed%20Atef%20Mohamed%20Shaaban_15002244.pdf MOHAMED SHAABAN KHAMIS, MOHAMED ATEF (2020) EVALUATION OF HYBRID SOLAR PHOTOVOLTAIC-GAS TURBINE SYSTEM USING ARTIFICIAL NEURAL NETWORK. Masters thesis, Universiti Teknologi PETRONAS.
institution Universiti Teknologi Petronas
collection UTPedia
language English
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
MOHAMED SHAABAN KHAMIS, MOHAMED ATEF
EVALUATION OF HYBRID SOLAR PHOTOVOLTAIC-GAS TURBINE SYSTEM USING ARTIFICIAL NEURAL NETWORK
description Solar energy one of the most available power source in Malaysia. The economic impact was the main target of this investigation with the fulfilment of the technical requirements of the Universiti Teknologi PETRONAS (UTP) Microgrid (MG). Since hybrid Solar Photovoltaic (SPV) and Gas Turbine Generator (GTG) (H-PVGTGs) will be considered in this research, the former models’ accuracy (in hybrid SPV optimization techniques) is very important. The least error for the existing mathematical models for SPV is 5.5% and this figure hypothetically can be further improved by using Artificial Intelligent (AI) method. There is always potential Annualized Total Life Cycle Cost (ATLCC) to be improved for the feasibility options.
format Thesis
author MOHAMED SHAABAN KHAMIS, MOHAMED ATEF
author_sort MOHAMED SHAABAN KHAMIS, MOHAMED ATEF
title EVALUATION OF HYBRID SOLAR PHOTOVOLTAIC-GAS TURBINE SYSTEM USING ARTIFICIAL NEURAL NETWORK
title_short EVALUATION OF HYBRID SOLAR PHOTOVOLTAIC-GAS TURBINE SYSTEM USING ARTIFICIAL NEURAL NETWORK
title_full EVALUATION OF HYBRID SOLAR PHOTOVOLTAIC-GAS TURBINE SYSTEM USING ARTIFICIAL NEURAL NETWORK
title_fullStr EVALUATION OF HYBRID SOLAR PHOTOVOLTAIC-GAS TURBINE SYSTEM USING ARTIFICIAL NEURAL NETWORK
title_full_unstemmed EVALUATION OF HYBRID SOLAR PHOTOVOLTAIC-GAS TURBINE SYSTEM USING ARTIFICIAL NEURAL NETWORK
title_sort evaluation of hybrid solar photovoltaic-gas turbine system using artificial neural network
publishDate 2020
url http://utpedia.utp.edu.my/20513/1/Mohamed%20Atef%20Mohamed%20Shaaban_15002244.pdf
http://utpedia.utp.edu.my/20513/
_version_ 1741195629760086016
score 11.62408

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