IDEAS home Printed from https://ideas.repec.org/a/eee/rensus/v150y2021ics1364032121006420.html
   My bibliography  Save this article

Digitalisation in wind and solar power technologies

Author

Listed:
  • Kangas, H.L.
  • Ollikka, K.
  • Ahola, J.
  • Kim, Y.

Abstract

Smart energy transition includes a widespread deployment of clean energy technologies and intelligent energy management with information and communication technologies (ICTs). In this paper, the smart energy transition is studied from the viewpoint of the technology convergence of renewable energy sources (RESs) and ICTs. Two important, fast-growing and weather-dependent renewable energy generation technologies: wind power and solar PV (photovoltaic) are studied. This paper provides technology convergence analyses of RES and ICT inventions based on international patent data. Digitalisation is changing the whole of society, and according to the results, this transition can also be seen in the studied renewable energy generation technologies. The digitalisation of RES production covers technologies that control, manage and optimise electricity production in different intelligent ways. Differences between wind power and solar PV technologies are found: in the case of wind power, the development from virtually no ICT solutions to partial technology convergence with the ICT sector is straightforward. However, in the case of solar PV, the development of basic technologies has been even faster than the development of the solar PV ICT solutions, which may indicate the immature nature of solar PV technologies during the studied years. The digitalisation of the renewable energy sector poses challenges for RES companies in following and predicting ICT development and opportunities for innovations and collaborations with ICT companies. This conclusion can also be expanded to society and policy levels because focusing on only a narrow field when planning innovation policy instruments can negatively impact the country's competitiveness.

Suggested Citation

  • Kangas, H.L. & Ollikka, K. & Ahola, J. & Kim, Y., 2021. "Digitalisation in wind and solar power technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 150(C).
    • Handle: RePEc:eee:rensus:v:150:y:2021:i:c:s1364032121006420
    DOI: 10.1016/j.rser.2021.111356
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1364032121006420
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.rser.2021.111356?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. Lupangu, C. & Bansal, R.C., 2017. "A review of technical issues on the development of solar photovoltaic systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 73(C), pages 950-965.
    2. Jae Young Choi & Seongkyoon Jeong & Kyunam Kim, 2015. "A Study on Diffusion Pattern of Technology Convergence: Patent Analysis for Korea," Sustainability, MDPI, vol. 7(9), pages 1-24, August.
    3. Gambardella, Alfonso & Torrisi, Salvatore, 1998. "Does technological convergence imply convergence in markets? Evidence from the electronics industry," Research Policy, Elsevier, vol. 27(5), pages 445-463, September.
    4. Dreidy, Mohammad & Mokhlis, H. & Mekhilef, Saad, 2017. "Inertia response and frequency control techniques for renewable energy sources: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 144-155.
    5. Karvonen, Matti & Kässi, Tuomo, 2013. "Patent citations as a tool for analysing the early stages of convergence," Technological Forecasting and Social Change, Elsevier, vol. 80(6), pages 1094-1107.
    6. Faran Ahmed & Muhammad Naeem & Muhammad Iqbal, 2017. "ICT and renewable energy: a way forward to the next generation telecom base stations," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 64(1), pages 43-56, January.
    7. Kim, Tae San & Sohn, So Young, 2020. "Machine-learning-based deep semantic analysis approach for forecasting new technology convergence," Technological Forecasting and Social Change, Elsevier, vol. 157(C).
    8. Jordehi, A. Rezaee, 2016. "Maximum power point tracking in photovoltaic (PV) systems: A review of different approaches," Renewable and Sustainable Energy Reviews, Elsevier, vol. 65(C), pages 1127-1138.
    9. Yoon‐Hee Ha & John Byrne & Hae‐Seok Lee & Ye‐Jin Lee & Dong‐Hwan Kim, 2020. "Assessing the impact of R&D policy on PV market development: The case of South Korea," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 9(2), March.
    10. Hoseinzadeh, Siamak & Ghasemi, Mohammad Hadi & Heyns, Stephan, 2020. "Application of hybrid systems in solution of low power generation at hot seasons for micro hydro systems," Renewable Energy, Elsevier, vol. 160(C), pages 323-332.
    11. de Rassenfosse, Gaétan & Dernis, Hélène & Guellec, Dominique & Picci, Lucio & van Pottelsberghe de la Potterie, Bruno, 2013. "The worldwide count of priority patents: A new indicator of inventive activity," Research Policy, Elsevier, vol. 42(3), pages 720-737.
    12. Thomas G. Allen & James Bullock & Xinbo Yang & Ali Javey & Stefaan De Wolf, 2019. "Passivating contacts for crystalline silicon solar cells," Nature Energy, Nature, vol. 4(11), pages 914-928, November.
    13. Alizadeh, S.M. & Ozansoy, C., 2016. "The role of communications and standardization in wind power applications – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 54(C), pages 944-958.
    14. Takashi Inaba & Mariagrazia Squicciarini, 2017. "ICT: A new taxonomy based on the international patent classification," OECD Science, Technology and Industry Working Papers 2017/1, OECD Publishing.
    15. Triki-Lahiani, Asma & Bennani-Ben Abdelghani, Afef & Slama-Belkhodja, Ilhem, 2018. "Fault detection and monitoring systems for photovoltaic installations: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 2680-2692.
    16. Maria Carvalho & Antoine Dechezlepretre & Matthieu Glachant, 2017. "Understanding the dynamics of global value chains for solar photovoltaic technologies," WIPO Economic Research Working Papers 40, World Intellectual Property Organization - Economics and Statistics Division.
    17. Jeeeun Kim & Sungjoo Lee, 2017. "Forecasting and identifying multi-technology convergence based on patent data: the case of IT and BT industries in 2020," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(1), pages 47-65, April.
    18. B. Golembiewski & N. Sick & S. Bröring, 2015. "Patterns of Convergence Within the Emerging Bioeconomy — The Case of the Agricultural and Energy Sector," International Journal of Innovation and Technology Management (IJITM), World Scientific Publishing Co. Pte. Ltd., vol. 12(03), pages 1-22.
    19. Ivan Haščič & Mauro Migotto, 2015. "Measuring environmental innovation using patent data," OECD Environment Working Papers 89, OECD Publishing.
    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. Grunevald, Isabel & Kipper, Liane Mahlmann & Ribas Moraes, Jorge Andre & Haupt, Leandro, 2023. "Scientific contributions on cleaner production through the use of patent information: A bibliometric analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 188(C).
    2. Zhong, Mei-Rui & Cao, Meng-Yuan & Zou, Han, 2022. "The carbon reduction effect of ICT: A perspective of factor substitution," Technological Forecasting and Social Change, Elsevier, vol. 181(C).
    3. Robert Szydło & Sylwia Wiśniewska & Małgorzata Tyrańska & Anna Dolot & Urszula Bukowska & Marek Koczyński, 2021. "Employer Expectations Regarding the Competencies of Employees on the Energy Market in Poland," Energies, MDPI, vol. 14(21), pages 1-21, November.
    4. Zhang, Hongyan & Gao, Shuaizhi & Zhou, Peng, 2023. "Role of digitalization in energy storage technological innovation: Evidence from China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 171(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. Park, Mingyu & Geum, Youngjung, 2022. "Two-stage technology opportunity discovery for firm-level decision making: GCN-based link-prediction approach," Technological Forecasting and Social Change, Elsevier, vol. 183(C).
    2. Seo, Wonchul & Afifuddin, Mokh, 2024. "Developing a supervised learning model for anticipating potential technology convergence between technology topics," Technological Forecasting and Social Change, Elsevier, vol. 203(C).
    3. Jong Wook Lee & So Young Sohn, 2021. "Patent data based search framework for IT R&D employees for convergence technology," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(7), pages 5687-5705, July.
    4. Sick, Nathalie & Bröring, Stefanie, 2022. "Exploring the research landscape of convergence from a TIM perspective: A review and research agenda," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    5. Dejing Kong & Jianzhong Yang & Lingfeng Li, 2020. "Early identification of technological convergence in numerical control machine tool: a deep learning approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(3), pages 1983-2009, December.
    6. Zhao, Shengchao & Zeng, Deming & Li, Jian & Feng, Ke & Wang, Yao, 2023. "Quantity or quality: The roles of technology and science convergence on firm innovation performance," Technovation, Elsevier, vol. 126(C).
    7. Qian Xu & Hua Cheng, 2021. "Research on the Evolution of Textile Technological Convergence in China," Sustainability, MDPI, vol. 13(5), pages 1-13, February.
    8. Zhu, Chen & Motohashi, Kazuyuki, 2022. "Identifying the technology convergence using patent text information: A graph convolutional networks (GCN)-based approach," Technological Forecasting and Social Change, Elsevier, vol. 176(C).
    9. Jungpyo Lee & So Young Sohn, 2021. "Recommendation system for technology convergence opportunities based on self-supervised representation learning," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(1), pages 1-25, January.
    10. ZHU Chen & MOTOHASHI Kazuyuki, 2022. "Government R&D spending as a driving force of technology convergence," Discussion papers 22030, Research Institute of Economy, Trade and Industry (RIETI).
    11. Sick, Nathalie & Preschitschek, Nina & Leker, Jens & Bröring, Stefanie, 2019. "A new framework to assess industry convergence in high technology environments," Technovation, Elsevier, vol. 84, pages 48-58.
    12. Yun, Siyeong & Song, Kisik & Kim, Chulhyun & Lee, Sungjoo, 2021. "From stones to jewellery: Investigating technology opportunities from expired patents," Technovation, Elsevier, vol. 103(C).
    13. Wenjing Zhu & Bohong Ma & Lele Kang, 2022. "Technology convergence among various technical fields: improvement of entropy estimation in patent analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(12), pages 7731-7750, December.
    14. Ying Tang & Xuming Lou & Zifeng Chen & Chengjin Zhang, 2020. "A Study on Dynamic Patterns of Technology Convergence with IPC Co-Occurrence-Based Analysis: The Case of 3D Printing," Sustainability, MDPI, vol. 12(7), pages 1-26, March.
    15. Sajad Ashouri & Anne-Laure Mention & Kosmas X. Smyrnios, 2021. "Anticipation and analysis of industry convergence using patent-level indicators," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(7), pages 5727-5758, July.
    16. Chen Zhu & Kazuyuki Motohashi, 2023. "Government R&D spending as a driving force of technology convergence: a case study of the Advanced Sequencing Technology Program," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(5), pages 3035-3065, May.
    17. Seongkyoon Jeong & Jong-Chan Kim & Jae Young Choi, 2015. "Technology convergence: What developmental stage are we in?," Scientometrics, Springer;Akadémiai Kiadó, vol. 104(3), pages 841-871, September.
    18. Patricia Laurens & Christian Le Bas & Stéphane Lhuillery & Antoine Schoen, 2017. "The determinants of cleaner energy innovations of the world’s largest firms: the impact of firm learning and knowledge capital," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 26(4), pages 311-333, May.
    19. Carmona-Lavado, Antonio & Gimenez-Fernandez, Elena M. & Vlaisavljevic, Vesna & Cabello-Medina, Carmen, 2023. "Cross-industry innovation: A systematic literature review," Technovation, Elsevier, vol. 124(C).
    20. Jing Wang & Yubing Xu, 2022. "How Does Digitalization Affect Haze Pollution? The Mediating Role of Energy Consumption," IJERPH, MDPI, vol. 19(18), pages 1-15, September.

    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:150:y:2021:i:c:s1364032121006420. 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.