In this paper, a comparative analysis of a 2.5 MW grid-connected solar photovoltaic (PV) power plant in Navrongo, Ghana is presented. The measured data from the plant was compared with that of the modelled and simulated results. The modelling was carried out using a genetic algorithm in MATLAB/Simulink. The comparison was based on power and solar irradiation as well as the efficiency of the plant under study. The results showed that, the model yielded increased output power compared with the power output determined from the measured data. This increase in power was observed in all three months; March, July and November 2014. PV module maximum power was more pronounced at a Fill Factor (FF) ranging from 0.5 to 0.8 at higher solar irradiation. Moreover, the efficiency of the modelled PV modules recorded a significant improvement in performance over that of the measured efficiencies for the same period. The monthly daily average measured efficiency value for March was 9.9% compared to 11.4% in the model, indicating a 1.5% increase. In July, however, efficiency increased by 1.0% by comparing the measured and modelled values of 9.6% and 10.6% respectively. November realised a 2.1% rise with a measured value of 11.2% against 13.3% being the modelled value. Conclusively, the study verifies the model’s accuracy to a large extent.
| Published in | Journal of Electrical and Electronic Engineering (Volume 10, Issue 3) |
| DOI | 10.11648/j.jeee.20221003.15 |
| Page(s) | 104-113 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2022. Published by Science Publishing Group |
Photovoltaic, Comparative Analysis, Genetic Algorithms, Output Power, Efficiency
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APA Style
Morrison Amenyo Vehe, Joseph Cudjoe Attachie, Christian Kwaku Amuzuvi. (2022). Comparative Analysis of the Solar PV Power Plant Efficiency and Output Power at Navrongo in Ghana. Journal of Electrical and Electronic Engineering, 10(3), 104-113. https://doi.org/10.11648/j.jeee.20221003.15
ACS Style
Morrison Amenyo Vehe; Joseph Cudjoe Attachie; Christian Kwaku Amuzuvi. Comparative Analysis of the Solar PV Power Plant Efficiency and Output Power at Navrongo in Ghana. J. Electr. Electron. Eng. 2022, 10(3), 104-113. doi: 10.11648/j.jeee.20221003.15
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Download@article{10.11648/j.jeee.20221003.15,
author = {Morrison Amenyo Vehe and Joseph Cudjoe Attachie and Christian Kwaku Amuzuvi},
title = {Comparative Analysis of the Solar PV Power Plant Efficiency and Output Power at Navrongo in Ghana},
journal = {Journal of Electrical and Electronic Engineering},
volume = {10},
number = {3},
pages = {104-113},
doi = {10.11648/j.jeee.20221003.15},
url = {https://doi.org/10.11648/j.jeee.20221003.15},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.jeee.20221003.15},
abstract = {In this paper, a comparative analysis of a 2.5 MW grid-connected solar photovoltaic (PV) power plant in Navrongo, Ghana is presented. The measured data from the plant was compared with that of the modelled and simulated results. The modelling was carried out using a genetic algorithm in MATLAB/Simulink. The comparison was based on power and solar irradiation as well as the efficiency of the plant under study. The results showed that, the model yielded increased output power compared with the power output determined from the measured data. This increase in power was observed in all three months; March, July and November 2014. PV module maximum power was more pronounced at a Fill Factor (FF) ranging from 0.5 to 0.8 at higher solar irradiation. Moreover, the efficiency of the modelled PV modules recorded a significant improvement in performance over that of the measured efficiencies for the same period. The monthly daily average measured efficiency value for March was 9.9% compared to 11.4% in the model, indicating a 1.5% increase. In July, however, efficiency increased by 1.0% by comparing the measured and modelled values of 9.6% and 10.6% respectively. November realised a 2.1% rise with a measured value of 11.2% against 13.3% being the modelled value. Conclusively, the study verifies the model’s accuracy to a large extent.},
year = {2022}
}
TY - JOUR T1 - Comparative Analysis of the Solar PV Power Plant Efficiency and Output Power at Navrongo in Ghana AU - Morrison Amenyo Vehe AU - Joseph Cudjoe Attachie AU - Christian Kwaku Amuzuvi Y1 - 2022/06/20 PY - 2022 N1 - https://doi.org/10.11648/j.jeee.20221003.15 DO - 10.11648/j.jeee.20221003.15 T2 - Journal of Electrical and Electronic Engineering JF - Journal of Electrical and Electronic Engineering JO - Journal of Electrical and Electronic Engineering SP - 104 EP - 113 PB - Science Publishing Group SN - 2329-1605 UR - https://doi.org/10.11648/j.jeee.20221003.15 AB - In this paper, a comparative analysis of a 2.5 MW grid-connected solar photovoltaic (PV) power plant in Navrongo, Ghana is presented. The measured data from the plant was compared with that of the modelled and simulated results. The modelling was carried out using a genetic algorithm in MATLAB/Simulink. The comparison was based on power and solar irradiation as well as the efficiency of the plant under study. The results showed that, the model yielded increased output power compared with the power output determined from the measured data. This increase in power was observed in all three months; March, July and November 2014. PV module maximum power was more pronounced at a Fill Factor (FF) ranging from 0.5 to 0.8 at higher solar irradiation. Moreover, the efficiency of the modelled PV modules recorded a significant improvement in performance over that of the measured efficiencies for the same period. The monthly daily average measured efficiency value for March was 9.9% compared to 11.4% in the model, indicating a 1.5% increase. In July, however, efficiency increased by 1.0% by comparing the measured and modelled values of 9.6% and 10.6% respectively. November realised a 2.1% rise with a measured value of 11.2% against 13.3% being the modelled value. Conclusively, the study verifies the model’s accuracy to a large extent. VL - 10 IS - 3 ER -
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