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Research on project post-evaluation of wind power based on improved ANP and fuzzy comprehensive evaluation model of trapezoid subordinate function improved by interval number

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  • Wang, Meng
  • Niu, Dongxiao

Abstract

The safety operation and economic benefits of wind farms are paid more attention by industry and society. Therefore, it's necessary to evaluate the wind power projects to find the deviation between actual situation, forecast target and first-class level. The commonly used methods of post-evaluation are AHP and fuzzy comprehensive evaluation which have three problems to be solved. The first is AHP method can't represent the correlation among the indexes. The second is the uncertainty of project data and experts' judgment. The third is the rectangle membership function can't realize data classification between adjacent levels. ANP can describe the relationship between indicators to eliminate deviation caused by independent calculation. The trapezoidal membership function is useful for rapid classification data between adjacent levels by maximum membership degree. And the interval can utilize imperfect information to solve the limitation of point estimation. So this paper proposes ANP model and fuzzy comprehensive evaluation model based on trapezoid membership which are all improved by interval numbers to evaluate projects. The paper makes a calculation of Pinglu wind farm, and the result shows new model is more stable with accuracy and applicability for post-evaluation which can solve the problems such as incomplete information, data fluctuation and subjective judgment.

Suggested Citation

  • Wang, Meng & Niu, Dongxiao, 2019. "Research on project post-evaluation of wind power based on improved ANP and fuzzy comprehensive evaluation model of trapezoid subordinate function improved by interval number," Renewable Energy, Elsevier, vol. 132(C), pages 255-265.
    • Handle: RePEc:eee:renene:v:132:y:2019:i:c:p:255-265
    DOI: 10.1016/j.renene.2018.08.009
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    Cited by:

    1. Qin, Jiazheng & Song, Junjie & Tang, Yong & Rui, Zhenhua & Wang, Yong & He, Youwei, 2023. "Well applicability assessment based on fuzzy theory for CO2 sequestration in depleted gas reservoirs," Renewable Energy, Elsevier, vol. 206(C), pages 239-250.
    2. Xu, Jiuping & Liu, Tingting, 2020. "Technological paradigm-based approaches towards challenges and policy shifts for sustainable wind energy development," Energy Policy, Elsevier, vol. 142(C).
    3. Xueyan Liu & Xiaolong Gao, 2018. "A New Study on Air Quality Standards: Air Quality Measurement and Evaluation for Jiangsu Province Based on Six Major Air Pollutants," Sustainability, MDPI, vol. 10(10), pages 1-16, October.
    4. Huijia Yang & Weiguang Fan & Guangyu Qin & Zhenyu Zhao, 2021. "A Fuzzy-ANP Approach for Comprehensive Benefit Evaluation of Grid-Side Commercial Storage Project," Energies, MDPI, vol. 14(4), pages 1-17, February.
    5. Hashemizadeh, Ali & Ju, Yanbing & Bamakan, Seyed Mojtaba Hosseini & Le, Hoang Phong, 2021. "Renewable energy investment risk assessment in belt and road initiative countries under uncertainty conditions," Energy, Elsevier, vol. 214(C).
    6. Yadegari, Mahsa & Sahebi, Hadi & Razm, Sobhan & Ashayeri, Jalal, 2023. "A sustainable multi-objective optimization model for the design of hybrid power supply networks under uncertainty," Renewable Energy, Elsevier, vol. 219(P1).
    7. Yanhui Qiao & Yongqian Liu & Yang Chen & Shuang Han & Luo Wang, 2022. "Power Generation Performance Indicators of Wind Farms Including the Influence of Wind Energy Resource Differences," Energies, MDPI, vol. 15(5), pages 1-25, February.
    8. Yan Zhou & Xunpeng Qin & Chenglong Li & Jun Zhou, 2022. "An Intelligent Site Selection Model for Hydrogen Refueling Stations Based on Fuzzy Comprehensive Evaluation and Artificial Neural Network—A Case Study of Shanghai," Energies, MDPI, vol. 15(3), pages 1-23, February.
    9. Handing Guo & Wanzhen Qiao & Yuehong Zheng, 2020. "Effectiveness Evaluation of Financing Platform Operation of Buildings Energy Saving Transformation Using ANP-Fuzzy in China: An Empirical Study," Sustainability, MDPI, vol. 12(7), pages 1-19, April.

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