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Regional differences in China's electric vehicle sales forecasting: Under supply-demand policy scenarios

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  • Liu, Bingchun
  • Song, Chengyuan
  • Liang, Xiaoqin
  • Lai, Mingzhao
  • Yu, Zhecheng
  • Ji, Jie

Abstract

Policy incentives are the key driving force for the electric vehicle (EV) market cultivation. During the EV market cultivation in different regions, the supply-side and demand-side policies have different effects. Accurately forecasting the stage characteristics and response sensitivity of EV sales under supply-demand side policy scenarios, which is crucial to the EV promotion policies design. This study selects the EV sales in 31 provinces with data available, as the basis for decision-making, and proposes a multi-factor prediction model integrating grey relation analysis (GRA), discrete wavelet transform (DWT), and bidirectional long short-term memory. Combined with the development difference of 31 provinces, the penetration of China's EV market under the benchmark, supply, demand, and ideal scenarios are verified. The experimental results show that the average Mean Absolute Percentage Error (MAPE) of the GRA-DWT-BiLSTM model is 9.884, and the 31 samples show good applicability for EV sales forecasting. In 2027, the growth rate of China's EV sales in the demand-side scenario will exceed the supply-side scenario. Under the ideal scenario, China's EV penetration rate will reach 27.31%, 42.40%, and 52.97% in 2025, 2030, and 2035 respectively. The forecast results provide a decision-making basis for China's EV market sequential supply-demand side policies.

Suggested Citation

  • Liu, Bingchun & Song, Chengyuan & Liang, Xiaoqin & Lai, Mingzhao & Yu, Zhecheng & Ji, Jie, 2023. "Regional differences in China's electric vehicle sales forecasting: Under supply-demand policy scenarios," Energy Policy, Elsevier, vol. 177(C).
    • Handle: RePEc:eee:enepol:v:177:y:2023:i:c:s0301421523001398
    DOI: 10.1016/j.enpol.2023.113554
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    2. Hamid Ahaggach & Lylia Abrouk & Eric Lebon, 2024. "Systematic Mapping Study of Sales Forecasting: Methods, Trends, and Future Directions," Forecasting, MDPI, vol. 6(3), pages 1-31, July.

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