Evaluation and Prediction of Wind Power Utilization Efficiency Based on Super-SBM and LSTM Models: A Case Study of 30 Provinces in China

Complexity 2020:1-13 (2020)
  Copy   BIBTEX

Abstract

Although China’s wind industry has made great progress in recent years, the wind abandonment phenomenon caused by the unbalanced development of regional wind power is still prominent. It is particularly important for the scientific development of wind power to accurately measure the utilization efficiency of wind power and understand its regional differences in China. This study establishes the improved super-efficiency slack-based measure model and long short-term memory network models, systematically and comprehensively measures and predicts the wind power utilization efficiency of 30 regions in China from 2013 to 2020, and explores regional differences in wind power utilization efficiency. Our results show the following: China’s overall wind power utilization efficiency is relatively low but has been on a steady upward trend since 2013. Regional differences are obvious, showing that the spatial distribution pattern of wind power utilization efficiency is greatest in Northeast China, followed by North China, East China, South China, Northwest China, and Central China. The “Three-North” region with abundant wind energy resources has relatively high wind power utilization efficiency and exhibits a good development trend. East China, South China, and Central China, where wind energy resources are relatively poor, have low wind power utilization efficiency, and their development trends are not stable and are more prone to change. The utilization efficiency of wind power in coastal areas is generally better than that in inland areas. There are also differences among the thirty Chinese regions studied. Inner Mongolia and Shandong have achieved real efficiency in wind power utilization efficiency, with optimal allocation of input and output, and a good development trend. The other 28 regions have varying degrees of inefficiency, and there is still room for improvement.

Links

PhilArchive



    Upload a copy of this work     Papers currently archived: 91,846

External links

Setup an account with your affiliations in order to access resources via your University's proxy server

Through your library

Similar books and articles

Design and Application of Wind Power Peak Control Technology.Songyi Zhu - 2014 - Journal of Power and Energy Engineering 2:23-28.
Wind Power in Ontario: Its Contribution to the Electricity Grid.Carey Jernigan & Ian H. Rowlands - 2008 - Bulletin of Science, Technology and Society 28 (6):436-453.
Renewable Hybrid Power Generation System.Shirshak Dutta, Arpita Sen, Sananda Biswas, Abhinaba Halder, Soumya Das, Pratyusha Biswas Deb & Ijarw Ijeais - 2018 - International Journal of Engineering and Information Systems (IJEAIS) 2 (2):1-5.
Wind Power in Australia: Overcoming Technological and Institutional Barriers.Andrea Bunting & Gerard Healey - 2008 - Bulletin of Science, Technology and Society 28 (2):115-127.
Renewable Energy Technologies for Microgrids.Marcelo G. Molina & Pedro E. Mercado - 2018 - In Antonio Carlos Zambroni de Souza & Miguel Castilla (eds.), Microgrids Design and Implementation. Springer Verlag. pp. 27-67.
For the wind was against them.Anthony Gittins - 2015 - The Australasian Catholic Record 92 (1):41.
Optical Response of MoSe2 Crystals.H. S. Patel - 2017 - International Journal of Trend in Scientific Research and Development 1 (3):1-6.

Analytics

Added to PP
2020-12-22

Downloads
2 (#1,803,862)

6 months
1 (#1,469,946)

Historical graph of downloads
How can I increase my downloads?

Author's Profile

Peng Zhou
University of Bologna

Citations of this work

No citations found.

Add more citations

References found in this work

No references found.

Add more references