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access icon openaccess Prediction and analysis of energy demand of high energy density AC/DC park based on spatial static load forecasting method

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References

    1. 1)
      • 1. Li, Y.: ‘Research on the development plan of Beidaihe new district power grid’ (Yanshan University, Qinhuangdao, China, 2013).
    2. 2)
      • 2. Jin, H.: ‘Basic principle and trend of development of domestic and international high-tech parks’, J. Party School C. P. C. Qingdao Municipal Committee, 2012, 2, pp. 2327.
    3. 3)
      • 3. Q/GDW 156-2006: ‘The code of planning and design of urban electric network’ (State Grid Corporation of China, Beijing, China, 2006).
    4. 4)
      • 4. Kang, C., Xia, Q., Zhang, B.: ‘Review of power system load forecasting and its development’, Autom. Electr. Power Syst., 2004, 28, (17), pp. 111.
    5. 5)
      • 5. Chen, G.: ‘Analysis and research of load forecasting in power network planning’ (Hunan University, Changsha, China, 2008).
    6. 6)
      • 6. Zhong, Q., Sun, W., Yu, N., et al: ‘Load and power forecasting in active distribution network planning’, Proc. CSEE, 2014, 34, (19), pp. 30503056.
    7. 7)
      • 7. Li, G.: ‘Application of combined forecasting model in medium and long term load forecasting system of electric power industry’ (Zhongshan University, Beijing, China, 2006).
    8. 8)
      • 8. Ge, F., Rong, X., Shi, X., et al: ‘The Anhui annual maximum load forecasting method research based on economic and meteorological factors’, Electr. Power, 2015, 48, (3), pp. 8487.
    9. 9)
      • 9. Yang, T., Chen, Y.: ‘Saturated electricity demand forecast based on amended self-adaptive logistic model’, Electr. Power, 2017, 50, (5), pp. 114120.
    10. 10)
      • 10. Xiao, B., Zhou, C., Mu, G.: ‘Review and prospect of spatial power load forecasting’, Proc. CSEE, 2013, 33, (25), pp. 7892.
    11. 11)
      • 11. Li, Y., Han, D., Yan, Z., et al: ‘Saturated load forecasting model under complex urbanization characteristics’, Power Syst. Technol., 2016, 40, (9), pp. 28242830.
    12. 12)
      • 12. Gao, F., Kang, C., Xia, Q., et al: ‘Multi-model automatic sifting methodology in load forecasting’, Autom. Electr. Power Syst., 2004, 28, (6), pp. 1113.
    13. 13)
      • 13. Li, R., Su, H., Wang, Z., et al: ‘Medium- and long-term load forecasting based on heuristic least square support vector machine’, Power Syst. Technol., 2011, 35, (11), pp. 95199.
    14. 14)
      • 14. Wang, B., Zhao, S., Zhang, S.: ‘A distributed load forecasting algorithm based on cloud computing and extreme learning machine’, Power Syst. Technol., 2014, 38, (2), pp. 526531.
    15. 15)
      • 15. Zhang, X., Chen, G., Zhou, J., et al: ‘Medium and long-term load forecast based on PSO-RSVR’, Power Syst. Prot. Control, 2009, 37, (21), pp. 7880.
    16. 16)
      • 16. Zhao, H., Zhou, J., Li, N., et al: ‘Study on urban saturated power load forecasting based on rolling multi-dimension method’, Electr. Power, 2015, 48, (3), pp. 2126.
    17. 17)
      • 17. Zhu, T.: ‘Research on electromagnetic transient characteristics of HVDC distribution system’ (Tsinghua University, 2016).
    18. 18)
      • 18. Padmakumari, K., Mohandas, K.P., Thiruvengadam, S.: ‘Long term distribution demand forecasting using neuron fuzzy computations’, UK Electr. Power Energy Syst., 1999, 21, (2), pp. 312315.
    19. 19)
      • 19. Shrestha, G., Lie, T.T.: ‘Qualitative use of forecast variables in hybrid load forecasting techniques’. USA IEEE Conf. Publication, Cambridge, USA, 2003, vol. 388, pp. 215220.
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