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A Bibliometric Analysis of Solar Energy Forecasting Studies in Africa

Author

Listed:
  • Nosipho Zwane

    (South African Weather Service, Private Bag X097, Pretoria 0001, South Africa
    Department of Geography, Geoinformatics and Meteorology, University of Pretoria, Private Bag X20, Hatfield Pretoria 0028, South Africa)

  • Henerica Tazvinga

    (South African Weather Service, Private Bag X097, Pretoria 0001, South Africa)

  • Christina Botai

    (South African Weather Service, Private Bag X097, Pretoria 0001, South Africa)

  • Miriam Murambadoro

    (South African Weather Service, Private Bag X097, Pretoria 0001, South Africa)

  • Joel Botai

    (South African Weather Service, Private Bag X097, Pretoria 0001, South Africa
    Department of Geography, Geoinformatics and Meteorology, University of Pretoria, Private Bag X20, Hatfield Pretoria 0028, South Africa
    Centre for Transformative Agricultural and Food Systems, School of Agriculture, Earth and Environmental Sciences, University of KwaZulu Natal, Scottsville, Pietermaritzburg 3209, South Africa)

  • Jaco de Wit

    (South African Weather Service, Private Bag X097, Pretoria 0001, South Africa)

  • Brighton Mabasa

    (South African Weather Service, Private Bag X097, Pretoria 0001, South Africa)

  • Siphamandla Daniel

    (South African Weather Service, Private Bag X097, Pretoria 0001, South Africa)

  • Tafadzwanashe Mabhaudhi

    (Centre for Transformative Agricultural and Food Systems, School of Agriculture, Earth and Environmental Sciences, University of KwaZulu Natal, Scottsville, Pietermaritzburg 3209, South Africa
    International Water Management Institute (IWMI-GH), West Africa Office, PMB CT 112 Cantonments, Accra GA015, Ghana)

Abstract

Solar energy forecasting is considered an essential scientific aspect in supporting efforts to integrate solar energy into power grids. Moreover, solar energy forecasting plays an essential role in mitigating greenhouse gas emissions and conserving energy for future use. This study conducted a bibliometric analysis to assess solar energy forecasting research studies evolution at the continental (Africa) and southern Africa levels. Key aspects of analysis included (i) scientific research trends, (ii) nature of collaboration networks, (iii) co-occurrence of keywords and (iv) emerging themes in solar energy forecasting over the last two decades, between the years 2000–2021. The results indicate that solar energy forecasting research has, on average, expanded by 6.4% and 3.3% in Africa and southern Africa, respectively. Based on the study context, solar energy forecasting research only gained momentum in 2015, peaking in 2019, but it is generally still subtle. The scientific mapping illustrated that only South Africa ranks among the leading countries that have produced high numbers of published documents and also leads in contributions to the research area in both Africa and southern Africa. Three emerging topics were identified from the thematic map analysis—namely, “solar irradiance”, “artificial intelligence” and “clear sky”, which implies that researchers are paying attention to solar irradiance, using modelling techniques that incorporate machine learning techniques. Overall, this study contributes to scientific information on the potential bankability of renewable energy projects that could assist power utilities, governments and policymakers in Africa to enforce the green economy through accelerated decarbonisation of the energy systems and building relationships with developed countries for support and better transitioning to solar energy. From a Water–Energy–Food nexus perspective, the results of this work could assist the scientific community in Africa to take advantage of the inherent interconnectedness of water, energy and food resources, whilst also advancing the use of integrated solutions to shape the focus of solar energy research into a more systems thinking and transdisciplinary approach involving the interconnected primary resources and stakeholders pursuit of the Sustainable Development Goals.

Suggested Citation

  • Nosipho Zwane & Henerica Tazvinga & Christina Botai & Miriam Murambadoro & Joel Botai & Jaco de Wit & Brighton Mabasa & Siphamandla Daniel & Tafadzwanashe Mabhaudhi, 2022. "A Bibliometric Analysis of Solar Energy Forecasting Studies in Africa," Energies, MDPI, vol. 15(15), pages 1-23, July.
  • Handle: RePEc:gam:jeners:v:15:y:2022:i:15:p:5520-:d:875812
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    References listed on IDEAS

    as
    1. Aria, Massimo & Cuccurullo, Corrado, 2017. "bibliometrix: An R-tool for comprehensive science mapping analysis," Journal of Informetrics, Elsevier, vol. 11(4), pages 959-975.
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    Cited by:

    1. Ho Kim Dan & Ha Thanh Tung & Duong Van Khanh & Ho Nguyen, 2023. "Bibliometric Analysis of Research Trends on Quantum-Dot-Sensitized Solar Cells over Two Decades," Energies, MDPI, vol. 16(15), pages 1-16, August.
    2. Luka Djordjević & Jasmina Pekez & Borivoj Novaković & Mihalj Bakator & Mića Djurdjev & Dragan Ćoćkalo & Saša Jovanović, 2023. "Increasing Energy Efficiency of Buildings in Serbia—A Case of an Urban Neighborhood," Sustainability, MDPI, vol. 15(7), pages 1-20, April.

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