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A Risk Assessment Framework of Hybrid Offshore Wind–Solar PV Power Plants under a Probabilistic Linguistic Environment

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  • Qinghua Mao

    (School of Economics and Management, Yanshan University, Qinhuangdao 066004, China)

  • Mengxin Guo

    (School of Economics and Management, Yanshan University, Qinhuangdao 066004, China)

  • Jian Lv

    (School of Economics and Management, Yanshan University, Qinhuangdao 066004, China)

  • Jinjin Chen

    (School of Economics and Management, Yanshan University, Qinhuangdao 066004, China)

  • Pengzhen Xie

    (School of Economics and Management, Yanshan University, Qinhuangdao 066004, China)

  • Meng Li

    (School of Economics and Management, Yanshan University, Qinhuangdao 066004, China)

Abstract

Hybrid offshore wind–solar PV power plants have attracted much attention in recent years due to its advantages of saving land resources, high energy efficiency, high power generation efficiency, and stable power output. However, due to the project still being in its infancy, investors will face a series of risks. Hence, a multi-criteria group decision-making framework for hybrid offshore wind–solar PV power plants risk assessment is constructed in this paper. Firstly, 19 risk indicators are identified and divided into five groups. Secondly, probabilistic linguistic term sets are then introduced to evaluate the criteria values to depict uncertainty and fuzziness. Thirdly, the expert weight determination model is built by combining subjective and objective weights based on expert information, the entropy and interaction-entropy measures of probabilistic linguistic term sets. Fourthly, the expert evaluation information is aggregated by transforming probabilistic linguistic term sets into triangular fuzzy numbers based on generalized weighted ordered weighted averaging operator. Additionally, the risk level is determined using the fuzzy synthetic evaluation method. Finally, the proposed method is applied to a case study and the risk level is slightly high with the similarity measure result of 0.938. Then, the risk indicator system and corresponding countermeasures can provide scientific reference for investment decisions and risk prevention.

Suggested Citation

  • Qinghua Mao & Mengxin Guo & Jian Lv & Jinjin Chen & Pengzhen Xie & Meng Li, 2022. "A Risk Assessment Framework of Hybrid Offshore Wind–Solar PV Power Plants under a Probabilistic Linguistic Environment," Sustainability, MDPI, vol. 14(7), pages 1-29, April.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:7:p:4197-:d:785130
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