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Developing a novel risk-based methodology for multi-criteria decision making in marine renewable energy applications

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  • Abaei, Mohammad Mahdi
  • Arzaghi, Ehsan
  • Abbassi, Rouzbeh
  • Garaniya, Vikram
  • Penesis, Irene

Abstract

Research and development of alternative energy resources such as wave energy has always attracted significant attention due to their abundant and sustainable nature. The uncertainties associated with the marine environment and the significant costs required for implementation of Wave Energy Converters (WECs) require a sound decision making methodology. This paper presents a novel risk-based methodology for selecting sites for WEC installation to minimize the overall economic risk. It provides WEC developers, investors, governments and policy makers a methodology for evaluating influencing parameters for potential site locations whilst also optimizing wave energy extraction. A Bayesian network is developed to model the probabilistic influencing parameters and then it is extended to an influence diagram for estimating the expected utility of installing the WEC equipment in a selected location. To demonstrate the application of the developed methodology, three sites in the south coast of Tasmania are considered. Based on actual sea state data, the optimum location for installing WEC equipment is determined as location 2 and the economic risk associated with energy extraction is minimized by suggesting a specific wave height (HS = 5 m) as a design criteria.

Suggested Citation

  • Abaei, Mohammad Mahdi & Arzaghi, Ehsan & Abbassi, Rouzbeh & Garaniya, Vikram & Penesis, Irene, 2017. "Developing a novel risk-based methodology for multi-criteria decision making in marine renewable energy applications," Renewable Energy, Elsevier, vol. 102(PB), pages 341-348.
    • Handle: RePEc:eee:renene:v:102:y:2017:i:pb:p:341-348
    DOI: 10.1016/j.renene.2016.10.054
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    4. Rockstuhl, Sebastian & Wenninger, Simon & Wiethe, Christian & Häckel, Björn, 2021. "Understanding the risk perception of energy efficiency investments: Investment perspective vs. energy bill perspective," Energy Policy, Elsevier, vol. 159(C).
    5. Sellak, Hamza & Ouhbi, Brahim & Frikh, Bouchra & Palomares, Iván, 2017. "Towards next-generation energy planning decision-making: An expert-based framework for intelligent decision support," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 1544-1577.
    6. Vanegas-Cantarero, María M. & Pennock, Shona & Bloise-Thomaz, Tianna & Jeffrey, Henry & Dickson, Matthew J., 2022. "Beyond LCOE: A multi-criteria evaluation framework for offshore renewable energy projects," Renewable and Sustainable Energy Reviews, Elsevier, vol. 161(C).
    7. Teniwut, Wellem Anselmus & Hamid, Syahibul Kahfi & Makailipessy, Marvin Mario, 2022. "Developing a masterplan for a sustainable marine sector in a small islands region: Integrated MCE spatial analysis for decision making," Land Use Policy, Elsevier, vol. 122(C).
    8. Shao, Meng & Han, Zhixin & Sun, Jinwei & Xiao, Chengsi & Zhang, Shulei & Zhao, Yuanxu, 2020. "A review of multi-criteria decision making applications for renewable energy site selection," Renewable Energy, Elsevier, vol. 157(C), pages 377-403.
    9. Kazak, Jan & van Hoof, Joost & Szewranski, Szymon, 2017. "Challenges in the wind turbines location process in Central Europe – The use of spatial decision support systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 76(C), pages 425-433.
    10. Ebrahimi, Mehri & Rahmani, Donya, 2019. "A five-dimensional approach to sustainability for prioritizing energy production systems using a revised GRA method: A case study," Renewable Energy, Elsevier, vol. 135(C), pages 345-354.
    11. Arzaghi, Ehsan & Abaei, Mohammad Mahdi & Abbassi, Rouzbeh & O'Reilly, Malgorzata & Garaniya, Vikram & Penesis, Irene, 2020. "A Markovian approach to power generation capacity assessment of floating wave energy converters," Renewable Energy, Elsevier, vol. 146(C), pages 2736-2743.

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