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Comparative technological road-mapping for renewable energy

Author

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  • Cowan, Kelly R.
  • Daim, Turgrul

Abstract

A comparative technology assessment and roadmapping process is used to examine key characteristics for leading electricity generation technologies and predict trends in cost reduction and growth potential. The role of renewable energy in generation portfolios is assessed, as well as resource integration strategies to minimize cost and environmental damage. The level of adoption of each technology is then linked to cost reduction and growth trends using a cost-prioritized adoption rule. Estimated levels of adoption are then matched to the projected growth of energy demand to determine both adequacy of supply and impact under this model. This study is applicable on both a national and regional energy planning level.

Suggested Citation

  • Cowan, Kelly R. & Daim, Turgrul, 2009. "Comparative technological road-mapping for renewable energy," Technology in Society, Elsevier, vol. 31(4), pages 333-341.
    • Handle: RePEc:eee:teinso:v:31:y:2009:i:4:p:333-341
    DOI: 10.1016/j.techsoc.2009.10.003
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    Cited by:

    1. Dincbas, Tugba & Ergeneli, Azize & Yigitbasioglu, Hakan, 2021. "Clean technology adoption in the context of climate change: Application in the mineral products industry," Technology in Society, Elsevier, vol. 64(C).
    2. Doğan, Buhari & Ghosh, Sudeshna & Hoang, Dung Phuong & Chu, Lan Khanh, 2022. "Are economic complexity and eco-innovation mutually exclusive to control energy demand and environmental quality in E7 and G7 countries?," Technology in Society, Elsevier, vol. 68(C).
    3. Cowan, Kelly R. & Daim, Tugrul U., 2011. "Review of technology acquisition and adoption research in the energy sector," Technology in Society, Elsevier, vol. 33(3), pages 183-199.
    4. Hyunsook Shim & Taeyeon Kim & Gyunghyun Choi, 2019. "Technology Roadmap for Eco-Friendly Building Materials Industry," Energies, MDPI, vol. 12(5), pages 1-14, February.
    5. Scholten, Daniel & Bosman, Rick, 2016. "The geopolitics of renewables; exploring the political implications of renewable energy systems," Technological Forecasting and Social Change, Elsevier, vol. 103(C), pages 273-283.
    6. Yu, Shiwei & Zhou, Shuangshuang & Zheng, Shuhong & Li, Zhenxi & Liu, Lancui, 2019. "Developing an optimal renewable electricity generation mix for China using a fuzzy multi-objective approach," Renewable Energy, Elsevier, vol. 139(C), pages 1086-1098.
    7. Daim, Tugrul & Cowan, Kelly, 2010. "Assessing renewable energy portfolio futures with multiple perspectives: The case of the northwest US," Technology in Society, Elsevier, vol. 32(4), pages 255-263.
    8. Martinez, Lauro J. & Lambert, James H. & Karvetski, Christopher W., 2011. "Scenario-informed multiple criteria analysis for prioritizing investments in electricity capacity expansion," Reliability Engineering and System Safety, Elsevier, vol. 96(8), pages 883-891.

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