IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v180y2021icp516-535.html
   My bibliography  Save this article

Diffusion forecast for grid-tied rooftop solar photovoltaic technology under store-on grid scheme model in Sub-Saharan Africa: Government role assessment

Author

Listed:
  • Mukisa, Nicholas
  • Zamora, Ramon
  • Lie, Tek Tjing

Abstract

Government support is crucial for the competitiveness and success of renewable energy market policies. As an advancement to the previously developed store-on grid (SoG) scheme, this study considered 14 countries to examine the government's role in facilitating the battery energy storage systems (BESS) under the SoG scheme. A methodology for evaluating the total government expenditure on the BESS to achieve the solar photovoltaic cumulative capacity forecasted by the Bass model and possible total greenhouse gases (GHG) emissions avoided was presented. Using a 15 years' timeline and cumulative capacity target of 500 MW, the Bass model forecasting results revealed that over 480 MW cumulative capacity would be achieved under the SoG scheme. The average present value of the total government expenditure on the BESS across the selected countries was about $ 47,154,052. Eswatini at $ 61,304,636 and Zimbabwe at $ 30,924,616 recorded the highest and lowest total government expenditure on the BESS, respectively. This is attributed mainly to the country's forecasted diffusion capacity at the peak point and duration to the inflection points. Furthermore, Zimbabwe with 19.99 MtCO2eq and Uganda with 2.79 MtCO2eq recorded the highest and least total GHG emissions avoided, respectively, attributed mainly to the country's grid emission factor.

Suggested Citation

  • Mukisa, Nicholas & Zamora, Ramon & Lie, Tek Tjing, 2021. "Diffusion forecast for grid-tied rooftop solar photovoltaic technology under store-on grid scheme model in Sub-Saharan Africa: Government role assessment," Renewable Energy, Elsevier, vol. 180(C), pages 516-535.
    • Handle: RePEc:eee:renene:v:180:y:2021:i:c:p:516-535
    DOI: 10.1016/j.renene.2021.08.122
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148121012908
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.renene.2021.08.122?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Philippe Menanteau & Dominique Finon & Marie-Laure Lamy, 2003. "Prices versus quantities :environmental policies for promoting the development of renewable energy," Post-Print halshs-00480457, HAL.
    2. H. Ahmed & SM. Miller, 2000. "Crowding‐out and crowding‐in effects of the components of government expenditure," Contemporary Economic Policy, Western Economic Association International, vol. 18(1), pages 124-133, January.
    3. Tascikaraoglu, Akin & Sanandaji, Borhan M. & Poolla, Kameshwar & Varaiya, Pravin, 2016. "Exploiting sparsity of interconnections in spatio-temporal wind speed forecasting using Wavelet Transform," Applied Energy, Elsevier, vol. 165(C), pages 735-747.
    4. Venkatesan, Rajkumar & Kumar, V., 2002. "A genetic algorithms approach to growth phase forecasting of wireless subscribers," International Journal of Forecasting, Elsevier, vol. 18(4), pages 625-646.
    5. Islam, Towhidul, 2014. "Household level innovation diffusion model of photo-voltaic (PV) solar cells from stated preference data," Energy Policy, Elsevier, vol. 65(C), pages 340-350.
    6. Lee, Chul-Yong & Huh, Sung-Yoon, 2017. "Forecasting the diffusion of renewable electricity considering the impact of policy and oil prices: The case of South Korea," Applied Energy, Elsevier, vol. 197(C), pages 29-39.
    7. Rao, K. Usha & Kishore, V.V.N., 2010. "A review of technology diffusion models with special reference to renewable energy technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(3), pages 1070-1078, April.
    8. Menanteau, Philippe & Finon, Dominique & Lamy, Marie-Laure, 2003. "Prices versus quantities: choosing policies for promoting the development of renewable energy," Energy Policy, Elsevier, vol. 31(8), pages 799-812, June.
    9. Frank M. Bass, 1969. "A New Product Growth for Model Consumer Durables," Management Science, INFORMS, vol. 15(5), pages 215-227, January.
    10. Dong, Changgui & Sigrin, Benjamin, 2019. "Using willingness to pay to forecast the adoption of solar photovoltaics: A “parameterization + calibration” approach," Energy Policy, Elsevier, vol. 129(C), pages 100-110.
    11. Saed Alizamir & Francis de Véricourt & Peng Sun, 2016. "Efficient Feed-In-Tariff Policies for Renewable Energy Technologies," Operations Research, INFORMS, vol. 64(1), pages 52-66, February.
    12. Anwar Shah, 2006. "Local Governance in Developing Countries," World Bank Publications - Books, The World Bank Group, number 7192.
    13. Aasim, & Singh, S.N. & Mohapatra, Abheejeet, 2019. "Repeated wavelet transform based ARIMA model for very short-term wind speed forecasting," Renewable Energy, Elsevier, vol. 136(C), pages 758-768.
    14. Mukisa, Nicholas & Zamora, Ramon & Lie, Tek Tjing, 2021. "Store-on grid scheme model for grid-tied solar photovoltaic systems for industrial sector application: Benefits analysis," Renewable Energy, Elsevier, vol. 171(C), pages 1257-1275.
    15. Piotr Wróblewski & Wojciech Drożdż & Wojciech Lewicki & Jakub Dowejko, 2021. "Total Cost of Ownership and Its Potential Consequences for the Development of the Hydrogen Fuel Cell Powered Vehicle Market in Poland," Energies, MDPI, vol. 14(8), pages 1-25, April.
    16. Anton Eberhard & Katharine Gratwick & Elvira Morella & Pedro Antmann, 2017. "Accelerating investments in power in sub-Saharan Africa," Nature Energy, Nature, vol. 2(2), pages 1-5, February.
    17. Guidolin, Mariangela & Guseo, Renato, 2016. "The German energy transition: Modeling competition and substitution between nuclear power and Renewable Energy Technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 1498-1504.
    18. Azadeh, A. & Babazadeh, R. & Asadzadeh, S.M., 2013. "Optimum estimation and forecasting of renewable energy consumption by artificial neural networks," Renewable and Sustainable Energy Reviews, Elsevier, vol. 27(C), pages 605-612.
    19. Huh, Sung-Yoon & Lee, Chul-Yong, 2014. "Diffusion of renewable energy technologies in South Korea on incorporating their competitive interrelationships," Energy Policy, Elsevier, vol. 69(C), pages 248-257.
    20. Severiano, Carlos A. & Silva, Petrônio Cândido de Lima e & Weiss Cohen, Miri & Guimarães, Frederico Gadelha, 2021. "Evolving fuzzy time series for spatio-temporal forecasting in renewable energy systems," Renewable Energy, Elsevier, vol. 171(C), pages 764-783.
    21. Shrimali, Gireesh & Konda, Charith & Farooquee, Arsalan Ali, 2016. "Designing renewable energy auctions for India: Managing risks to maximize deployment and cost-effectiveness," Renewable Energy, Elsevier, vol. 97(C), pages 656-670.
    22. Massiani, Jérôme & Gohs, Andreas, 2015. "The choice of Bass model coefficients to forecast diffusion for innovative products: An empirical investigation for new automotive technologies," Research in Transportation Economics, Elsevier, vol. 50(C), pages 17-28.
    23. Dobrotkova, Zuzana & Surana, Kavita & Audinet, Pierre, 2018. "The price of solar energy: Comparing competitive auctions for utility-scale solar PV in developing countries," Energy Policy, Elsevier, vol. 118(C), pages 133-148.
    24. Agnew, Scott & Dargusch, Paul, 2017. "Consumer preferences for household-level battery energy storage," Renewable and Sustainable Energy Reviews, Elsevier, vol. 75(C), pages 609-617.
    25. Mukisa, Nicholas & Zamora, Ramon & Lie, Tek Tjing, 2021. "Viability of the store-on Grid Scheme model for grid-tied rooftop solar photovoltaic systems in Sub-Saharan African countries," Renewable Energy, Elsevier, vol. 178(C), pages 845-863.
    26. J�r�me Massiani, 2013. "The use of Stated Preferences to forecast alternative fuel vehicles market diffusion: Comparisons with other methods and proposal for a Synthetic Utility Function," Working Papers 2013:12, Department of Economics, University of Venice "Ca' Foscari".
    27. Eberhard, Anton & Gratwick, Katharine & Morella, Elvira & Antmann, Pedro, 2017. "Independent Power Projects in Sub-Saharan Africa: Investment trends and policy lessons," Energy Policy, Elsevier, vol. 108(C), pages 390-424.
    28. Jones, J. & Genovese, A. & Tob-Ogu, A., 2020. "Hydrogen vehicles in urban logistics: A total cost of ownership analysis and some policy implications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 119(C).
    29. Harrison, Gillian & Thiel, Christian, 2017. "An exploratory policy analysis of electric vehicle sales competition and sensitivity to infrastructure in Europe," Technological Forecasting and Social Change, Elsevier, vol. 114(C), pages 165-178.
    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. Lee, Chul-Yong & Huh, Sung-Yoon, 2017. "Forecasting the diffusion of renewable electricity considering the impact of policy and oil prices: The case of South Korea," Applied Energy, Elsevier, vol. 197(C), pages 29-39.
    2. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    3. Brito, Thiago Luis Felipe & Islam, Towhidul & Stettler, Marc & Mouette, Dominique & Meade, Nigel & Moutinho dos Santos, Edmilson, 2019. "Transitions between technological generations of alternative fuel vehicles in Brazil," Energy Policy, Elsevier, vol. 134(C).
    4. Xu, Mei & Xie, Pu & Xie, Bai-Chen, 2020. "Study of China's optimal solar photovoltaic power development path to 2050," Resources Policy, Elsevier, vol. 65(C).
    5. Liu, Xueying & Madlener, Reinhard, 2019. "Get Ready for Take-Off: A Two-Stage Model of Aircraft Market Diffusion," FCN Working Papers 15/2019, E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN).
    6. Bose, A.S. & Sarkar, S., 2019. "India's e-reverse auctions (2017–2018) for allocating renewable energy capacity: An evaluation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 112(C), pages 762-774.
    7. Alina Ștefania Chenic & Alin Ioan Cretu & Adrian Burlacu & Nicolae Moroianu & Daniela Vîrjan & Dragos Huru & Mihaela Roberta Stanef-Puica & Vladimir Enachescu, 2022. "Logical Analysis on the Strategy for a Sustainable Transition of the World to Green Energy—2050. Smart Cities and Villages Coupled to Renewable Energy Sources with Low Carbon Footprint," Sustainability, MDPI, vol. 14(14), pages 1-30, July.
    8. Bunea, Anita M. & Della Posta, Pompeo & Guidolin, Mariangela & Manfredi, Piero, 2020. "What do adoption patterns of solar panels observed so far tell about governments’ incentive? Insights from diffusion models," Technological Forecasting and Social Change, Elsevier, vol. 160(C).
    9. Meade, Nigel & Islam, Towhidul, 2015. "Modelling European usage of renewable energy technologies for electricity generation," Technological Forecasting and Social Change, Elsevier, vol. 90(PB), pages 497-509.
    10. Lee, Chul-Yong & Huh, Sung-Yoon, 2017. "Forecasting new and renewable energy supply through a bottom-up approach: The case of South Korea," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 207-217.
    11. Anita M. Bunea & Mariangela Guidolin & Piero Manfredi & Pompeo Della Posta, 2022. "Diffusion of Solar PV Energy in the UK: A Comparison of Sectoral Patterns," Forecasting, MDPI, vol. 4(2), pages 1-21, April.
    12. Bessi, Alessandro & Guidolin, Mariangela & Manfredi, Piero, 2021. "The role of gas on future perspectives of renewable energy diffusion: Bridging technology or lock-in?," Renewable and Sustainable Energy Reviews, Elsevier, vol. 152(C).
    13. Reddy, B. Sudhakara, 2018. "Economic dynamics and technology diffusion in indian power sector," Energy Policy, Elsevier, vol. 120(C), pages 425-435.
    14. Choi, Gobong & Huh, Sung-Yoon & Heo, Eunnyeong & Lee, Chul-Yong, 2018. "Prices versus quantities: Comparing economic efficiency of feed-in tariff and renewable portfolio standard in promoting renewable electricity generation," Energy Policy, Elsevier, vol. 113(C), pages 239-248.
    15. Sanghamitra Mukherjee, 2021. "A Framework to Measure Regional Disparities in Battery Electric Vehicle Diffusion in Ireland," Working Papers 202119, School of Economics, University College Dublin.
    16. Marc Baudry & Clément Bonnet, 2016. "Demand pull isntruments and the development of wind power in Europe: A counter-factual analysis," Working Papers 1607, Chaire Economie du climat.
    17. Wang, Bing & Wei, Yi-Ming & Yuan, Xiao-Chen, 2018. "Possible design with equity and responsibility in China’s renewable portfolio standards," Applied Energy, Elsevier, vol. 232(C), pages 685-694.
    18. Marc Baudry & Clément Bonnet, 2019. "Demand-Pull Instruments and the Development of Wind Power in Europe: A Counterfactual Analysis," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 73(2), pages 385-429, June.
    19. Arias-Gaviria, Jessica & Larsen, Erik R. & Arango-Aramburo, Santiago, 2018. "Understanding the future of Seawater Air Conditioning in the Caribbean: A simulation approach," Utilities Policy, Elsevier, vol. 53(C), pages 73-83.
    20. Rui, Zhaobiao & Peng, Weicai & Qin, Ximei & Wang, Jun, 2023. "Assessing carbon cap-and-trade policies on hybrid renewable energy investments: Implications for pricing and capacity decisions," Resources Policy, Elsevier, vol. 86(PA).

    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:eee:renene:v:180:y:2021:i:c:p:516-535. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/renewable-energy .

    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.