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Comparative Analysis of the Solar PV Power Plant Efficiency and Output Power at Navrongo in Ghana

Received: 20 May 2022     Accepted: 8 June 2022     Published: 20 June 2022
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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.

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

Keywords

Photovoltaic, Comparative Analysis, Genetic Algorithms, Output Power, Efficiency

References
[1] Attachie, J. C. and Amuzuvi, C. K. (2013), “Renewable Energy Technologies in Ghana: Opportunities and Threats”, Research Journal of Applied Sciences, Engineering and Technology, Vol. 6, No. 5, pp. 776-782.
[2] Mahama, E. K. (2013), “Renewable Energy: An Alternative to Meeting Ghana’s Energy Challenges”, www.vibeghana.com/2013/04/08/renewable-energy-an-alternative-to-meeting-ghanas-energy-challenges/, Accessed: October 6, 2015.
[3] Anon. (2016), “Power Generation Facts and Figures”, www.vraghana.com/resources/facts.php, Accessed: April 13, 2016.
[4] Yatey, E. (2015), “Ghana’s Road to Energy Sufficiency”, www.africanreview.com. Accessed: February 3, 2015.
[5] Kale-Dery, S. (2015), “Solar Power Generating Plant on Test Trial”, www.graphic.com.gh/news/general-news/53683-solar- power-generating-plant-on-test-trial.html, Accessed: April 13, 2016.
[6] Acheampong, J. (2014), “US$350 Million Solar Project for Ghana”, www.graphic.com.gh/business/business-news/18704 -us-350-million-solar-project-for-ghana.html#sthash.EGPk7UVR.dpuf, Accessed: April 13, 2016.
[7] Fetyan, K. M. and Hady, R. (2021), “Performance Evaluation of on-grid PV Systems in Egypt”, Water Science, 35: 1, 63-70, DOI: 10.1080/23570008.2021.1905347.
[8] Esmaeilion, F., Ahmadi, A., Esmaeilion, A. and Aliehyaei, M. (2021), “The Performance Analysis and Monitoring of Grid-Connected Photovoltaic Power Plant”, Current Chinese Computer Science, Volume 1, Issue 1, doi: 10.2174/2665997201999200511083228.
[9] Kymakis, E., Kalykakis, S. and Papazoglou, T. M. (2009), “Performance Analysis of a Grid-Connected Photovoltaic Park on the Island of Crete”, Energy Conversion and Management, Vol. 50, No. 3, pp. 433-438.
[10] Omane, F. (2013), “Status and Development of the Local PV Market Structure”, www.giz.de/fachexpertise/downloads/2013 -en-pep-informationsveranstaltung-pv-ghana-frimpong.pdf, Accessed: September 4, 2015.
[11] Vimalarani, C. and Kamaraj, N. (2015), “Modeling and Performance Analysis of the Solar Photovoltaic Cell Model Using Embedded Matlab”, Transactions of the Society for Modeling and Simulation International, 16pp.
[12] Ma, T., Yang, H. and Lu, L. (2014), “Photovoltaic System Modeling and Performance Prediction”, Renewable Sustainable Energy Rev, Vol. 36, pp. 304-315.
[13] Ishaque, K., Salam, Z. and Syafaruddin (2011), “A Comprehensive Matlab Simulink PV System Simulator with Partial Shading Capability Based on Two-Diode Model”, Solar Energy, Vol. 85, pp. 2217-2227.
[14] Villalva, M. G., Gazoli, J. R. and Filho, E. R. (2009), “Comprehensive Approach to Modeling and Simulation of Photovoltaic Arrays”, IEEE Transactions on Power Electronics, Vol. 24, No. 5, pp. 1198-1208.
[15] Ishaque, K. Salam, Z. and Taheri, H. (2011a), “Simple, Fast and Accurate Two-Diode Model for Photovoltaic Modules”, Solar Energy Materials Solar Cells, Vol. 95, No. 2, pp. 586-594.
[16] Ishaque, K., Salam, Z. and Taheri, H. (2011b), “Accurate Matlab Simulink PV System Simulator Based on a Two-Diode Model”, Journal of Power Electronics, Vol. 11, No. 2, pp. 179-187.
[17] Anon. (2014e), “Global Optimization Toolbox User’s Guide for MATLAB (R2014a)”, Mathworks, 2014.
[18] Guda, H. A. and Aliyu U. O. (2015), “Effects of Temperature on Photovoltaic Array Conversion Efficiency and Fill Factor”, International Journal of Engineering and Technology, Vol. 5, No. 1, 7 pp.
[19] Sivanandam, S. N. and Deeper, S. N. (2008), Introduction to Genetic Algorithms, Springer, New York, 453pp.
Cite This Article
  • 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

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    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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    AMA 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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  • @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}
    }
    

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  • 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
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    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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Author Information
  • Department of Electrical and Electronic Engineering, Regional Maritime University, Accra, Ghana

  • Department of Electrical and Electronic Engineering, University of Mines and Technology, Tarkwa, Ghana

  • Department of Renewable Energy Engineering, University of Mines and Technology, Tarkwa, Ghana

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