IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v17y2024i11p2613-d1404231.html
   My bibliography  Save this article

Regressive and Spatio-Temporal Accessibility of Variability in Solar Energy on a Short Scale Measurement in the Southern and Mid Region of Mozambique

Author

Listed:
  • Fernando Venâncio Mucomole

    (CS-OGET—Center of Excellence of Studies in Oil and Gas Engineering and Technology, Faculty of Engineering, Eduardo Mondlane University, Mozambique Avenue Km 1.5, Maputo 257, Mozambique
    CPE—Centre of Research in Energies, Faculty of Sciences, Eduardo Mondlane University, Main Campus No. 3453, Maputo 257, Mozambique
    Department of Physics, Faculty of Sciences, Eduardo Mondlane University, Main Campus No. 3453, Maputo 257, Mozambique)

  • Carlos Augusto Santos Silva

    (Department of Mechanical Engineering, Instituto Superior Técnico, University of Lisbon, 1600-214 Lisbon, Portugal)

  • Lourenço Lázaro Magaia

    (Department of Mathematics and Informatics, Faculty of Science, Eduardo Mondlane University, Main Campus No. 3453, Maputo 257, Mozambique)

Abstract

Solar energy reaching a horizontal surface can possess fluctuations that impact electricity generation at a solar plant. Despite this, energy access remains inadequate, particularly in rural areas, with an estimated 82% deficiency. This drives us to assess the regressive and spatial-temporal accessibility of solar energy in the southern and mid regions of Mozambique. This evaluation aims to determine the actual availability of energy for electrification purposes. Data on global horizontal irradiation from approximately 8 stations across all provinces in the specified regions, collected between 2012 and 2014 at intervals of 1 and 10 min, were analyzed using regression and correlation methods along with a specialized algorithm for classifying days based on clear sky index terms. The statistical analysis identified days with significant potential for energy accessibility, exceeding 50% of the average. The findings suggest a correlation coefficient of approximately 0.30 for energy and non-linear regression with clear sky index coefficients around 0.80. The method employed demonstrated accuracy when compared to theoretical simulations of the clear sky index in the region, indicating its potential applicability in other regions of interest.

Suggested Citation

  • Fernando Venâncio Mucomole & Carlos Augusto Santos Silva & Lourenço Lázaro Magaia, 2024. "Regressive and Spatio-Temporal Accessibility of Variability in Solar Energy on a Short Scale Measurement in the Southern and Mid Region of Mozambique," Energies, MDPI, vol. 17(11), pages 1-29, May.
  • Handle: RePEc:gam:jeners:v:17:y:2024:i:11:p:2613-:d:1404231
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/17/11/2613/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/17/11/2613/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Takilalte, Abdelatif & Harrouni, Samia & Yaiche, Mohamed Rédha & Mora-López, Llanos, 2020. "New approach to estimate 5-min global solar irradiation data on tilted planes from horizontal measurement," Renewable Energy, Elsevier, vol. 145(C), pages 2477-2488.
    2. Williamson, Sarah & Businger, Steven & Matthews, Dax, 2018. "Development of a solar irradiance dataset for Oahu, Hawai'i," Renewable Energy, Elsevier, vol. 128(PA), pages 432-443.
    3. Armstrong, S. & Hurley, W.G., 2010. "A new methodology to optimise solar energy extraction under cloudy conditions," Renewable Energy, Elsevier, vol. 35(4), pages 780-787.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Guo, Siyu & Walsh, Timothy Michael & Peters, Marius, 2013. "Vertically mounted bifacial photovoltaic modules: A global analysis," Energy, Elsevier, vol. 61(C), pages 447-454.
    2. Rawat, Rahul & Kaushik, S.C. & Lamba, Ravita, 2016. "A review on modeling, design methodology and size optimization of photovoltaic based water pumping, standalone and grid connected system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 1506-1519.
    3. Mäki, Anssi & Valkealahti, Seppo, 2014. "Differentiation of multiple maximum power points of partially shaded photovoltaic power generators," Renewable Energy, Elsevier, vol. 71(C), pages 89-99.
    4. Lv, Yuexia & Si, Pengfei & Rong, Xiangyang & Yan, Jinyue & Feng, Ya & Zhu, Xiaohong, 2018. "Determination of optimum tilt angle and orientation for solar collectors based on effective solar heat collection," Applied Energy, Elsevier, vol. 219(C), pages 11-19.
    5. Gupta, Sowmya & Rajhans, Chinmay & Duttagupta, Siddhartha P. & Mitra, Mira, 2021. "Hybrid energy design for lighter than air systems," Renewable Energy, Elsevier, vol. 173(C), pages 781-794.
    6. Rodríguez, Fermín & Martín, Fernando & Fontán, Luis & Galarza, Ainhoa, 2021. "Ensemble of machine learning and spatiotemporal parameters to forecast very short-term solar irradiation to compute photovoltaic generators’ output power," Energy, Elsevier, vol. 229(C).
    7. Chinchilla, Monica & Santos-Martín, David & Carpintero-Rentería, Miguel & Lemon, Scott, 2021. "Worldwide annual optimum tilt angle model for solar collectors and photovoltaic systems in the absence of site meteorological data," Applied Energy, Elsevier, vol. 281(C).
    8. Llinet Benavides Cesar & Miguel Ángel Manso Callejo & Calimanut-Ionut Cira & Ramon Alcarria, 2023. "CyL-GHI: Global Horizontal Irradiance Dataset Containing 18 Years of Refined Data at 30-Min Granularity from 37 Stations Located in Castile and León (Spain)," Data, MDPI, vol. 8(4), pages 1-21, March.
    9. Kaddoura, Tarek O. & Ramli, Makbul A.M. & Al-Turki, Yusuf A., 2016. "On the estimation of the optimum tilt angle of PV panel in Saudi Arabia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 65(C), pages 626-634.
    10. Mook, W.T. & Aroua, M.K. & Issabayeva, G., 2014. "Prospective applications of renewable energy based electrochemical systems in wastewater treatment: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 38(C), pages 36-46.
    11. Hafez, A.Z. & Soliman, A. & El-Metwally, K.A. & Ismail, I.M., 2017. "Tilt and azimuth angles in solar energy applications – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 147-168.
    12. Gökmen, Nuri & Hu, Weihao & Hou, Peng & Chen, Zhe & Sera, Dezso & Spataru, Sergiu, 2016. "Investigation of wind speed cooling effect on PV panels in windy locations," Renewable Energy, Elsevier, vol. 90(C), pages 283-290.
    13. Kakosimos, Panagiotis E. & Kladas, Antonios G., 2011. "Implementation of photovoltaic array MPPT through fixed step predictive control technique," Renewable Energy, Elsevier, vol. 36(9), pages 2508-2514.
    14. Rehman, Naveed ur & Uzair, Muhammad & Allauddin, Usman, 2020. "An optical-energy model for optimizing the geometrical layout of solar photovoltaic arrays in a constrained field," Renewable Energy, Elsevier, vol. 149(C), pages 55-65.
    15. Ramez Abdallah & Emad Natsheh & Adel Juaidi & Sufyan Samara & Francisco Manzano-Agugliaro, 2020. "A Multi-Level World Comprehensive Neural Network Model for Maximum Annual Solar Irradiation on a Flat Surface," Energies, MDPI, vol. 13(23), pages 1-31, December.
    16. Joylan Nunes Maciel & Jorge Javier Gimenez Ledesma & Oswaldo Hideo Ando Junior, 2024. "Dataset for Machine Learning: Explicit All-Sky Image Features to Enhance Solar Irradiance Prediction," Data, MDPI, vol. 9(10), pages 1-12, September.
    17. Badescu, Viorel & Dumitrescu, Alexandru, 2014. "Simple models to compute solar global irradiance from the CMSAF product Cloud Fractional Coverage," Renewable Energy, Elsevier, vol. 66(C), pages 118-131.
    18. Anthony Patt & Stefan Pfenninger & Johan Lilliestam, 2013. "Vulnerability of solar energy infrastructure and output to climate change," Climatic Change, Springer, vol. 121(1), pages 93-102, November.
    19. Nunes Maciel, Joylan & Javier Gimenez Ledesma, Jorge & Hideo Ando Junior, Oswaldo, 2024. "Hybrid prediction method of solar irradiance applied to short-term photovoltaic energy generation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 192(C).
    20. Yildirim, Deniz & Büyüksalih, Gürcan & Şahin, Ahmet Duran, 2021. "Rooftop photovoltaic potential in Istanbul: Calculations based on LiDAR data, measurements and verifications," Applied Energy, Elsevier, vol. 304(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:17:y:2024:i:11:p:2613-:d:1404231. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.