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Data-based investigation on the performance of an independent gas turbine for electricity generation using real power measurements and other closely related parameters

Generally, sub-Saharan countries possess abundant energy resources including renewables and fossil sources, with natural gas potentially being among the more abundant resource second only to solar power. For conventional electrical energy generation, gas turbines are one of the most prominent techno...

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Autores principales: Esan, Ayodele Benjamin, Ehiaguina, Vincent, Awosope, Claudius, Olatomiwa, Lanre, Egbune, Dickson
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6742853/
https://www.ncbi.nlm.nih.gov/pubmed/31528678
http://dx.doi.org/10.1016/j.dib.2019.104444
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author Esan, Ayodele Benjamin
Ehiaguina, Vincent
Awosope, Claudius
Olatomiwa, Lanre
Egbune, Dickson
author_facet Esan, Ayodele Benjamin
Ehiaguina, Vincent
Awosope, Claudius
Olatomiwa, Lanre
Egbune, Dickson
author_sort Esan, Ayodele Benjamin
collection PubMed
description Generally, sub-Saharan countries possess abundant energy resources including renewables and fossil sources, with natural gas potentially being among the more abundant resource second only to solar power. For conventional electrical energy generation, gas turbines are one of the most prominent technologies being adopted in producing electricity from natural gas. Nigeria, for instance has the largest natural gas reserves in Africa, and the 9th largest in the World. Thus, more than 80% of her electricity generation utilizes gas turbines. To effectively monitor the state of these gas turbines, several sensors are located on the turbines to acquire data in real time. In this data article, we present the acquired data from a 5.68-MW gas turbine installed as an independent power producing unit in a community in Ogun State, Nigeria over a period of six months. Performing various descriptive analysis on the dataset, the real power measurements were taken as the target parameters, and based on a threshold correlation co-efficient of 0.5, only sixteen (16) parameters were shown to be more closely positively correlated with the real power measurements. Thus, any variation in the real power supplied by the gas turbine would have a commensurate effect on any of the other 16 parameters identified, and could thus help in troubleshooting or scheduling maintenance.
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spelling pubmed-67428532019-09-16 Data-based investigation on the performance of an independent gas turbine for electricity generation using real power measurements and other closely related parameters Esan, Ayodele Benjamin Ehiaguina, Vincent Awosope, Claudius Olatomiwa, Lanre Egbune, Dickson Data Brief Energy Generally, sub-Saharan countries possess abundant energy resources including renewables and fossil sources, with natural gas potentially being among the more abundant resource second only to solar power. For conventional electrical energy generation, gas turbines are one of the most prominent technologies being adopted in producing electricity from natural gas. Nigeria, for instance has the largest natural gas reserves in Africa, and the 9th largest in the World. Thus, more than 80% of her electricity generation utilizes gas turbines. To effectively monitor the state of these gas turbines, several sensors are located on the turbines to acquire data in real time. In this data article, we present the acquired data from a 5.68-MW gas turbine installed as an independent power producing unit in a community in Ogun State, Nigeria over a period of six months. Performing various descriptive analysis on the dataset, the real power measurements were taken as the target parameters, and based on a threshold correlation co-efficient of 0.5, only sixteen (16) parameters were shown to be more closely positively correlated with the real power measurements. Thus, any variation in the real power supplied by the gas turbine would have a commensurate effect on any of the other 16 parameters identified, and could thus help in troubleshooting or scheduling maintenance. Elsevier 2019-08-28 /pmc/articles/PMC6742853/ /pubmed/31528678 http://dx.doi.org/10.1016/j.dib.2019.104444 Text en © 2019 The Author(s) http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Energy
Esan, Ayodele Benjamin
Ehiaguina, Vincent
Awosope, Claudius
Olatomiwa, Lanre
Egbune, Dickson
Data-based investigation on the performance of an independent gas turbine for electricity generation using real power measurements and other closely related parameters
title Data-based investigation on the performance of an independent gas turbine for electricity generation using real power measurements and other closely related parameters
title_full Data-based investigation on the performance of an independent gas turbine for electricity generation using real power measurements and other closely related parameters
title_fullStr Data-based investigation on the performance of an independent gas turbine for electricity generation using real power measurements and other closely related parameters
title_full_unstemmed Data-based investigation on the performance of an independent gas turbine for electricity generation using real power measurements and other closely related parameters
title_short Data-based investigation on the performance of an independent gas turbine for electricity generation using real power measurements and other closely related parameters
title_sort data-based investigation on the performance of an independent gas turbine for electricity generation using real power measurements and other closely related parameters
topic Energy
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6742853/
https://www.ncbi.nlm.nih.gov/pubmed/31528678
http://dx.doi.org/10.1016/j.dib.2019.104444
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