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access icon openaccess Management and development performance assessment for electric distribution company based on data mining

In this study, the Statistical Product and Service Solutions software is applied to analyse the massive data of electric distribution companies. A comprehensive evaluation of grid development and production and operation of basic electric distribution companies is the key to a company's investment and development strategies. This study proposes a comprehensive evaluation index system for electric distribution companies. In the method, the weight of each index is calculated using the improved analytic hierarchy process based on the Delphi method. Then, according to the actual operation situation of each enterprise, the differential weight of various indices is constructed, and the comprehensive evaluation and score of differentiation for electric distribution companies are realised, which can be used for locating the weak line of the power grid of each enterprise and putting forward an investment strategy of the power grid. Through the demonstration application of 98 electric distribution companies in Shanxi Province of China, this method exhibits a promotion of value and accuracy in carrying out a comprehensive evaluation for electric distribution companies.

References

    1. 1)
      • 12. Peijian, W.: ‘Dynamic data center operations with demand-responsive electricity prices in smart grid’, IEEE Trans. Smart Grid, 2012, 3, (4), pp. 17431754.
    2. 2)
      • 6. Xinhua, G., Zheng, Y.: ‘Comprehensive assessment of smart grid construction based on principal component analysis and cluster analysis’, Power Syst. Technol., 2013, 37, (8), pp. 22382243.
    3. 3)
      • 2. Dong, H., Zheng, Y., Yiqun, S., et al: ‘Dynamic assessment method for smart grid based on system dynamics’, Autom. Electr. Power Syst., 2012, 36, (3), pp. 1621.
    4. 4)
      • 4. Jun, X., Yanyan, C., Jianmin, W., et al: ‘A hierarchical performance assessment method on the distribution network planning’, Autom. Electr. Power Syst., 2008, 32, (15), pp. 3640.
    5. 5)
      • 13. Zhentao, H., Zhiwei, H., Shaoyun, G., et al: ‘A comprehensive evaluation system of urban distribution network’, Power Syst. Technol., 2012, 36, (8), pp. 9599.
    6. 6)
      • 1. Hairui, Z., Dong, H., Yu, L., et al: ‘Smart grid evaluation based on anti-entropy weight method’, Power Syst. Prot. Control, 2012, 40, (11), pp. 2429.
    7. 7)
      • 8. Shanshan, Z.: ‘CPI analysis based on system clustering in SPSS’, Xinxiang. Henan Normal University, 2013.
    8. 8)
      • 10. Yaqi, S., Guoliang, Z., Yongli, Z.: ‘Present status and challenges of big data processing in smart grid’, Power Syst. Technol., 2013, 37, (4), pp. 927935.
    9. 9)
      • 17. Zhenghang, H., Zhiqing, Y., Shaohua, L., et al: ‘The contribution of double-fed wind farms to transient voltage and damping of power grids’, Power Syst. Prot. Control, 2015, 22, (1), pp. 4344.
    10. 10)
      • 11. Dongxia, Z., Xin, M., Liping, L., et al: ‘Research on development strategy for smart grid big data’, Proc. CSEE, 2015, 35, (1), pp. 212.
    11. 11)
      • 5. Weixing, L., Peng, W., Zhimin, L., et al: ‘Reliability evaluation of complex radial distribution systems considering restoration sequence and network constrains’, IEEE Trans. Power Deliv., 2004, 19, (2), pp. 753758.
    12. 12)
      • 16. Gantz, J., Reinsel, D.: ‘Extracting value from chaos’. Proc. IDC iView.Framingham, USA: [s.n.], 2011, pp. 112.
    13. 13)
      • 14. Xinhua, G., Zheng, Y.: ‘The smart grid's evaluation index system with technology maturity characteristic’, South. Power Syst. Technol., 2014, 1, pp. 812.
    14. 14)
      • 9. Qingshan, X., Wendi, W., Zhangsui, L., et al: ‘Establishment and application of EMI indicator system orienting to massive industrial data mining’, Electr. Power Autom. Equip., 2015, 35, (7), pp. 1521.
    15. 15)
      • 7. Runlong, H.: ‘Statistical analysis of data-SPSS principle and application’ (Higher Education Press, Beijing, 2010).
    16. 16)
      • 3. Yang, C., Hanhui, M., Li, Z., et al: ‘A comprehensive evaluation of new rural low-voltage distribution networks based on analytic hierarchy process’, Power Syst. Technol., 2007, 31, (8), pp. 6872.
    17. 17)
      • 15. Guang, L., Qizong, W.: ‘Research on data standardization in comprehensive evaluation based on consistent result’, Math. Pract. Theory, 2014, 3, pp. 812.
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