Open Access
E3S Web Conf.
Volume 53, 2018
2018 3rd International Conference on Advances in Energy and Environment Research (ICAEER 2018)
Article Number 01001
Number of page(s) 6
Section Energy Engineering, Materials and Technology
Published online 14 September 2018
  1. National renewable energy center. The development roadmap of Chinese renewable energy 2050 [R]. The renewable energy development project management office of Zhong Dan. [Google Scholar]
  2. Liu Jianan. Research on optimal strategy of wind-PV-ES hybrid operation in electricity market[J]. Journal of eiectric power science and technology, 2017, 32(1): 11-15. [Google Scholar]
  3. XIE Ting. tudy on coupling power technology for 600 MW supercritical coal-firedgenerating units and distributed photovoltaic energy systems[J]. Journal of eiectric power science and technology, 2015, 30(1): 90-104. [Google Scholar]
  4. Duan Hongbo, Zhu Lei, Fan Ying. Analysis of the laws and policies of China's wind energy technology diffusion [J]. Management science, 2013, 26(4): 113-120. [Google Scholar]
  5. Shi Cailing, Long Ruyin, Li Huijuan. Research on the diffusion prediction of solar pv technology in China[J]. Industrial and technical economy,. 2007, 8: 60-65. [Google Scholar]
  6. Zhou Siqing, Ma Chaoqun, Li Lin. Theory and research on sustainable development of solar photovoltaic industry [J]. The progress and countermeasures of Scientific and technology, 2007, 24(7): 88-90. [Google Scholar]
  7. Yan Huizhen. The application of Gompertz model to population growth prediction [J]. Journal of dalian university of technology, 2015, 34(2): 150-152. [Google Scholar]
  8. Bass, F. M.. A new product growth model for consumer durables [J]. Management Science,,. 1969, 15: 215-227. [Google Scholar]
  9. Chow, G. C. Technological change and the demand for computers [J]. American Economic Review,, 1967, 57(5): 1117-1130. [Google Scholar]
  10. Sundqvist, S., Frank, L. Puumalainen, K The effects of country characteristics, culture similarity and adoption timing on the diffusion of wireless communications [J]. Journal of Business Research,., 2005.58: 107-110. [CrossRef] [Google Scholar]
  11. Mansfield, E. Technical change and the rate of imitation [J]. Econometrica,, 1961, 29(4): 741-766. [CrossRef] [Google Scholar]
  12. Grilliches, Z., Hybrid corn: an exploration in the economics of technological change [J]. 1957, Econometrica, 25(4): 501-522. [CrossRef] [Google Scholar]
  13. Wu, F. S., Chu, W. L.. Diffusion models of mobile telephone [J]. Journal of Business Research,. 2010, 63: 497-501. [CrossRef] [Google Scholar]
  14. Gruber, H., Verboven, F.. The diffusion of mobile telecommunications services in the European Union [J]. European Economic Review,. 2001, 45: 577-588. [CrossRef] [Google Scholar]
  15. Lee, M., Cho, T. The diffusion of mobile telecommunications service in Korea [J]. Applied Economic Letters,,. 2007, 14: 477-481. [CrossRef] [Google Scholar]
  16. Valle, A. D., Furlan, C.. Forecasting accuracy of wind power technology diffusion models across countries [J]. International Journal of Forecasting,,. 2011, 27: 592-601. [CrossRef] [Google Scholar]

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