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Assessing the Environmental Impact Caused by Power Grid Projects in High Altitude Areas Based on BWM and Vague Sets Techniques

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  • Yuanxin Liu

    (School of Economics and Management, North China Electric Power University, Beijing 102206, China
    Beijing Key Laboratory of New Energy and Low-Carbon Development, North China Electric Power University, Changping, Beijing 102206, China)

  • FengYun Li

    (School of Economics and Management, North China Electric Power University, Beijing 102206, China)

  • Yi Wang

    (School of Economics and Management, North China Electric Power University, Beijing 102206, China)

  • Xinhua Yu

    (School of Economics and Management, North China Electric Power University, Beijing 102206, China)

  • Jiahai Yuan

    (School of Economics and Management, North China Electric Power University, Beijing 102206, China)

  • Yuwei Wang

    (School of Economics and Management, North China Electric Power University, Beijing 102206, China)

Abstract

This study constructed a hybrid model for assessing the environmental impact caused by power grid projects (PGP) in high altitude area (HAA). Firstly, this study analyzed the characteristics of the environment in HAA and the possible environmental impacts caused by the PGP in HAA. On this basis, an evaluation indicator system reflecting the particularity of HAA was established, including three perspectives named natural, social and ecological environment. Next, considering the availability of evaluation index data and the scarcity of evaluation samples, the best and worst method (BWM) was employed to obtain the objective and credible indicator weights. Furthermore, the Vague set theory was introduced into the comprehensive evaluation model, overcoming the shortcomings of comprehensive evaluation model based on fuzzy sets. Finally, the practicability and effectiveness of the proposed hybrid model was validated via a practical PGP in Qinghai-Tibet Plateau. Overall, the results of this paper can play an important supporting role in promoting green construction and sustainable development of PGP. Besides, the proposed hybrid evaluation framework requires fewer index values and evaluation samples, having good applicability and promotion value in handling the evaluation issues with uncertain and incomplete information.

Suggested Citation

  • Yuanxin Liu & FengYun Li & Yi Wang & Xinhua Yu & Jiahai Yuan & Yuwei Wang, 2018. "Assessing the Environmental Impact Caused by Power Grid Projects in High Altitude Areas Based on BWM and Vague Sets Techniques," Sustainability, MDPI, vol. 10(6), pages 1-20, May.
    • Handle: RePEc:gam:jsusta:v:10:y:2018:i:6:p:1768-:d:149399
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    References listed on IDEAS

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    1. Chau, C.K. & Leung, T.M. & Ng, W.Y., 2015. "A review on Life Cycle Assessment, Life Cycle Energy Assessment and Life Cycle Carbon Emissions Assessment on buildings," Applied Energy, Elsevier, vol. 143(C), pages 395-413.
    2. Kathryn Hochstetler, 2018. "Environmental impact assessment: evidence-based policymaking in Brazil," Contemporary Social Science, Taylor & Francis Journals, vol. 13(1), pages 100-111, January.
    3. Liu, Hua-Wen & Wang, Guo-Jun, 2007. "Multi-criteria decision-making methods based on intuitionistic fuzzy sets," European Journal of Operational Research, Elsevier, vol. 179(1), pages 220-233, May.
    4. Liang, Zhihong & Yang, Kun & Sun, Yaowei & Yuan, Jiahai & Zhang, Hongwei & Zhang, Zhizheng, 2006. "Decision support for choice optimal power generation projects: Fuzzy comprehensive evaluation model based on the electricity market," Energy Policy, Elsevier, vol. 34(17), pages 3359-3364, November.
    5. Rezaei, Jafar, 2016. "Best-worst multi-criteria decision-making method: Some properties and a linear model," Omega, Elsevier, vol. 64(C), pages 126-130.
    6. Rezaei, Jafar, 2015. "Best-worst multi-criteria decision-making method," Omega, Elsevier, vol. 53(C), pages 49-57.
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    Cited by:

    1. Jian Wang & Jin-Chun Huang & Shan-Lin Huang & Gwo-Hshiung Tzeng & Ting Zhu, 2021. "Improvement Path for Resource-Constrained Cities Identified Using an Environmental Co-Governance Assessment Framework Based on BWM-mV Model," IJERPH, MDPI, vol. 18(9), pages 1-30, May.
    2. Mi, Xiaomei & Tang, Ming & Liao, Huchang & Shen, Wenjing & Lev, Benjamin, 2019. "The state-of-the-art survey on integrations and applications of the best worst method in decision making: Why, what, what for and what's next?," Omega, Elsevier, vol. 87(C), pages 205-225.
    3. Xueliang Li & Bingkang Li & Long Zhao & Huiru Zhao & Wanlei Xue & Sen Guo, 2019. "Forecasting the Short-Term Electric Load Considering the Influence of Air Pollution Prevention and Control Policy via a Hybrid Model," Sustainability, MDPI, vol. 11(10), pages 1-21, May.
    4. Wenjin Li & Bingkang Li & Rengcun Fang & Peipei You & Yuxin Zou & Zhao Xu & Sen Guo, 2021. "Risk Evaluation of Electric Power Grid Enterprise Related to Electricity Transmission and Distribution Tariff Regulation Employing a Hybrid MCDM Model," Mathematics, MDPI, vol. 9(9), pages 1-23, April.
    5. Lunyan Wang & Wenmin Li & Huimin Li, 2020. "Decision-making for ecological landslide prevention in tropical rainforests," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 103(1), pages 985-1008, August.

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