IDEAS home Printed from https://ideas.repec.org/a/eee/rensus/v152y2021ics1364032121009382.html
   My bibliography  Save this article

Developing a framework to assess the long-term adoption of renewable energy technologies in the electric power sector: The effects of carbon price and economic incentives

Author

Listed:
  • Radpour, S.
  • Gemechu, E.
  • Ahiduzzaman, Md
  • Kumar, A.

Abstract

Greenhouse gas emissions from the burning of fossil fuels are one of the main causes of anthropogenic climate change. Large-scale deployment of renewable energy can play an immense role in transforming the global energy system and mitigating the emissions. This paper describes the development of a novel framework called MArket Penetration ModeLing of Renewable Energy Technologies in Electric Power Sector (MAPLET-PS). MAPLET-PS assesses the impacts of policy measures such as carbon price and financial incentives on the adoption of renewable energy technologies. The framework was used to develop a case study for the electric power sector of Alberta, a fossil-dominated province in Western Canada. The results show that implementing a carbon price on fossil fuel electric power sources and incentives for renewable energy, along with the phase-out of coal-fired electricity generation, can mitigate 29% of Alberta's electricity sector 2020 GHG emissions by 2050 and reduce GHG emissions from 46.5 Mt of CO2 eq. in 2020 to 23.6 and 29.1 Mt of CO2 eq. per year in 2030 and 2050, respectively, in Alberta. Moreover, these changes can increase the share of renewable energies from 12.5% in 2018 to 30% in 2050. These rates can be achieved by implementing a carbon price along with a 1000 $ incentive per kW new capacity development and 70 $ incentive per MWh electric power generation from renewable sources, from 2021 to 2025, primarily from wind turbines.

Suggested Citation

  • Radpour, S. & Gemechu, E. & Ahiduzzaman, Md & Kumar, A., 2021. "Developing a framework to assess the long-term adoption of renewable energy technologies in the electric power sector: The effects of carbon price and economic incentives," Renewable and Sustainable Energy Reviews, Elsevier, vol. 152(C).
    • Handle: RePEc:eee:rensus:v:152:y:2021:i:c:s1364032121009382
    DOI: 10.1016/j.rser.2021.111663
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1364032121009382
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.rser.2021.111663?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. Chinmoy, Lakshmi & Iniyan, S. & Goic, Ranko, 2019. "Modeling wind power investments, policies and social benefits for deregulated electricity market – A review," Applied Energy, Elsevier, vol. 242(C), pages 364-377.
    2. Ibenholt, Karin, 2002. "Explaining learning curves for wind power," Energy Policy, Elsevier, vol. 30(13), pages 1181-1189, October.
    3. Lund, P.D., 2007. "Upfront resource requirements for large-scale exploitation schemes of new renewable technologies," Renewable Energy, Elsevier, vol. 32(3), pages 442-458.
    4. Carl E. Walsh, 2003. "Monetary Theory and Policy, 2nd Edition," MIT Press Books, The MIT Press, edition 2, volume 1, number 0262232316, April.
    5. Dinica, Valentina, 2006. "Support systems for the diffusion of renewable energy technologies--an investor perspective," Energy Policy, Elsevier, vol. 34(4), pages 461-480, March.
    6. Hu, Zheng & Hu, Zhaoguang, 2013. "Production function with electricity consumption and its applications," Energy Economics, Elsevier, vol. 39(C), pages 313-321.
    7. Chris Bataille & Noel Melton & Mark Jaccard, 2015. "Policy uncertainty and diffusion of carbon capture and storage in an optimal region," Climate Policy, Taylor & Francis Journals, vol. 15(5), pages 565-582, September.
    8. Ardente, Fulvio & Beccali, Marco & Cellura, Maurizio & Lo Brano, Valerio, 2008. "Energy performances and life cycle assessment of an Italian wind farm," Renewable and Sustainable Energy Reviews, Elsevier, vol. 12(1), pages 200-217, January.
    9. Waite, Michael & Modi, Vijay, 2019. "Impact of deep wind power penetration on variability at load centers," Applied Energy, Elsevier, vol. 235(C), pages 1048-1060.
    10. Barrington-Leigh, Christopher & Ouliaris, Mark, 2017. "The renewable energy landscape in Canada: A spatial analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 75(C), pages 809-819.
    11. Jacobsson, Staffan & Johnson, Anna, 2000. "The diffusion of renewable energy technology: an analytical framework and key issues for research," Energy Policy, Elsevier, vol. 28(9), pages 625-640, July.
    12. Stram, Bruce N., 2016. "Key challenges to expanding renewable energy," Energy Policy, Elsevier, vol. 96(C), pages 728-734.
    13. Usha Rao, K. & Kishore, V.V.N., 2009. "Wind power technology diffusion analysis in selected states of India," Renewable Energy, Elsevier, vol. 34(4), pages 983-988.
    14. Cheng, Yaohua & Zhang, Ning & Kirschen, Daniel S. & Huang, Wujing & Kang, Chongqing, 2020. "Planning multiple energy systems for low-carbon districts with high penetration of renewable energy: An empirical study in China," Applied Energy, Elsevier, vol. 261(C).
    15. Hwang, Jenn Jiang, 2010. "Promotional policy for renewable energy development in Taiwan," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(3), pages 1079-1087, April.
    16. Oryani, Bahareh & Koo, Yoonmo & Rezania, Shahabaldin & Shafiee, Afsaneh, 2021. "Investigating the asymmetric impact of energy consumption on reshaping future energy policy and economic growth in Iran using extended Cobb-Douglas production function," Energy, Elsevier, vol. 216(C).
    17. Zou, Peng & Chen, Qixin & Yu, Yang & Xia, Qing & Kang, Chongqing, 2017. "Electricity markets evolution with the changing generation mix: An empirical analysis based on China 2050 High Renewable Energy Penetration Roadmap," Applied Energy, Elsevier, vol. 185(P1), pages 56-67.
    18. Han, Xingning & Chen, Xinyu & McElroy, Michael B. & Liao, Shiwu & Nielsen, Chris P. & Wen, Jinyu, 2019. "Modeling formulation and validation for accelerated simulation and flexibility assessment on large scale power systems under higher renewable penetrations," Applied Energy, Elsevier, vol. 237(C), pages 145-154.
    19. Collantes, Gustavo O, 2007. "Incorporating stakeholders' perspectives into models of new technology diffusion: The case of fuel-cell vehicles," Institute of Transportation Studies, Working Paper Series qt9bm1w968, Institute of Transportation Studies, UC Davis.
    20. del Río, Pablo & Unruh, Gregory, 2007. "Overcoming the lock-out of renewable energy technologies in Spain: The cases of wind and solar electricity," Renewable and Sustainable Energy Reviews, Elsevier, vol. 11(7), pages 1498-1513, September.
    21. Neij, Lena, 1997. "Use of experience curves to analyse the prospects for diffusion and adoption of renewable energy technology," Energy Policy, Elsevier, vol. 25(13), pages 1099-1107, November.
    22. Wei, Taoyuan, 2007. "Impact of energy efficiency gains on output and energy use with Cobb-Douglas production function," Energy Policy, Elsevier, vol. 35(4), pages 2023-2030, April.
    23. 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.
    24. Radpour, Saeidreza & Gemechu, Eskinder & Ahiduzzaman, Md & Kumar, Amit, 2021. "Development of a framework for the assessment of the market penetration of novel in situ bitumen extraction technologies," Energy, Elsevier, vol. 220(C).
    25. Isoard, Stephane & Soria, Antonio, 2001. "Technical change dynamics: evidence from the emerging renewable energy technologies," Energy Economics, Elsevier, vol. 23(6), pages 619-636, November.
    26. Agrawal, Nikhil & Ahiduzzaman, Md & Kumar, Amit, 2018. "The development of an integrated model for the assessment of water and GHG footprints for the power generation sector," Applied Energy, Elsevier, vol. 216(C), pages 558-575.
    27. Gaete-Morales, Carlos & Gallego-Schmid, Alejandro & Stamford, Laurence & Azapagic, Adisa, 2019. "A novel framework for development and optimisation of future electricity scenarios with high penetration of renewables and storage," Applied Energy, Elsevier, vol. 250(C), pages 1657-1672.
    28. Pinto, Hugo, 2011. "The role of econometrics in economic science: An essay about the monopolization of economic methodology by econometric methods," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 40(4), pages 436-443, August.
    29. Jin, Xiaolong & Wu, Qiuwei & Jia, Hongjie, 2020. "Local flexibility markets: Literature review on concepts, models and clearing methods," Applied Energy, Elsevier, vol. 261(C).
    30. Matschoss, Patrick & Bayer, Benjamin & Thomas, Heiko & Marian, Adela, 2019. "The German incentive regulation and its practical impact on the grid integration of renewable energy systems," Renewable Energy, Elsevier, vol. 134(C), pages 727-738.
    31. Gaete-Morales, Carlos & Gallego-Schmid, Alejandro & Stamford, Laurence & Azapagic, Adisa, 2019. "A novel framework for development and optimisation of future electricity scenarios with high penetration of renewables and storage," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 250, pages 1657-1672.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Shi, Y.Y. & Wei, Z.X. & Shahbaz, M., 2023. "Analyzing the co-evolutionary dynamics of consumers’ attitudes and green energy technologies based on a triple-helix model," Renewable and Sustainable Energy Reviews, Elsevier, vol. 171(C).
    2. Kamali Saraji, Mahyar & Aliasgari, Elahe & Streimikiene, Dalia, 2023. "Assessment of the challenges to renewable energy technologies adoption in rural areas: A Fermatean CRITIC-VIKOR approach," Technological Forecasting and Social Change, Elsevier, vol. 189(C).
    3. Ahmad, Munir & Jabeen, Gul, 2023. "Biogas technology adoption and household welfare perspectives for sustainable development," Energy Policy, Elsevier, vol. 181(C).
    4. Hamed, Mohammad M. & Mohammed, Ali & Olabi, Abdul Ghani, 2023. "Renewable energy adoption decisions in Jordan's industrial sector: Statistical analysis with unobserved heterogeneity," Renewable and Sustainable Energy Reviews, Elsevier, vol. 184(C).
    5. Zhao, Jing & Zhang, Qin & Zhou, Dequn, 2023. "Can marketed on-grid price drive the realization of energy transition in China’s power industry under the background of carbon neutrality?," Energy, Elsevier, vol. 276(C).

    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. Xu, Jiuping & Li, Li & Zheng, Bobo, 2016. "Wind energy generation technological paradigm diffusion," Renewable and Sustainable Energy Reviews, Elsevier, vol. 59(C), pages 436-449.
    2. 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.
    3. 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.
    4. 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).
    5. Cong, Rong-Gang, 2013. "An optimization model for renewable energy generation and its application in China: A perspective of maximum utilization," Renewable and Sustainable Energy Reviews, Elsevier, vol. 17(C), pages 94-103.
    6. Xin-gang, Zhao & Wei, Wang & Jieying, Wang, 2022. "The policy effects of demand-pull and technology-push on the diffusion of wind power: A scenario analysis based on system dynamics approach," Energy, Elsevier, vol. 261(PA).
    7. Greaker, Mads & Lund Sagen, Eirik, 2008. "Explaining experience curves for new energy technologies: A case study of liquefied natural gas," Energy Economics, Elsevier, vol. 30(6), pages 2899-2911, November.
    8. 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.
    9. Negro, Simona O. & Alkemade, Floortje & Hekkert, Marko P., 2012. "Why does renewable energy diffuse so slowly? A review of innovation system problems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(6), pages 3836-3846.
    10. Strupeit, Lars, 2017. "An innovation system perspective on the drivers of soft cost reduction for photovoltaic deployment: The case of Germany," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 273-286.
    11. Harijan, Khanji & Uqaili, Mohammad A. & Memon, Mujeebuddin & Mirza, Umar K., 2011. "Forecasting the diffusion of wind power in Pakistan," Energy, Elsevier, vol. 36(10), pages 6068-6073.
    12. Radpour, Saeidreza & Hossain Mondal, Md Alam & Kumar, Amit, 2017. "Market penetration modeling of high energy efficiency appliances in the residential sector," Energy, Elsevier, vol. 134(C), pages 951-961.
    13. Radpour, Saeidreza & Gemechu, Eskinder & Ahiduzzaman, Md & Kumar, Amit, 2021. "Development of a framework for the assessment of the market penetration of novel in situ bitumen extraction technologies," Energy, Elsevier, vol. 220(C).
    14. Yu, C.F. & van Sark, W.G.J.H.M. & Alsema, E.A., 2011. "Unraveling the photovoltaic technology learning curve by incorporation of input price changes and scale effects," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(1), pages 324-337, January.
    15. Wei Jin & ZhongXiang Zhang, 2015. "Levelling the Playing Field: On the Missing Role of Network Externality in Designing Renewable Energy Technology Deployment Policies," Working Papers 2015.76, Fondazione Eni Enrico Mattei.
    16. Patrik Söderholm & Ger Klaassen, 2007. "Wind Power in Europe: A Simultaneous Innovation–Diffusion Model," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 36(2), pages 163-190, February.
    17. Lu, Ze-Yu & Li, Wen-Hua & Xie, Bai-Chen & Shang, Li-Feng, 2015. "Study on China’s wind power development path—Based on the target for 2030," Renewable and Sustainable Energy Reviews, Elsevier, vol. 51(C), pages 197-208.
    18. Lindman, Åsa & Söderholm, Patrik, 2012. "Wind power learning rates: A conceptual review and meta-analysis," Energy Economics, Elsevier, vol. 34(3), pages 754-761.
    19. Kahouli, Sondès, 2011. "Effects of technological learning and uranium price on nuclear cost: Preliminary insights from a multiple factors learning curve and uranium market modeling," Energy Economics, Elsevier, vol. 33(5), pages 840-852, September.
    20. Ackah, Ishmael & Kizys, Renatas, 2015. "Green growth in oil producing African countries: A panel data analysis of renewable energy demand," Renewable and Sustainable Energy Reviews, Elsevier, vol. 50(C), pages 1157-1166.

    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:rensus:v:152:y:2021:i:c:s1364032121009382. 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.elsevier.com/wps/find/journaldescription.cws_home/600126/description#description .

    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.