Affiliation:
1. College of Information and Management Science, Henan Agricultural University, Zhengzhou 450046, China
Abstract
Since the installed capacity of wind power is greatly affected by the subsidy policy, this paper predicts the installed wind power capacity in China under different policy scenarios. Firstly, a new two-parameter variable-weight buffer operator is proposed to quantify the impact of the policy shock, whose optimal parameters are obtained by the genetic algorithm, and combined with the grey GM(1,1) model to predict the installed capacity of wind power in China under the cessation of subsidy policy. Then, the GM(1,1) model with optimized background value is used to predict the installed capacity under continued subsidy. Finally, two policy subsidy strategy models are constructed based on the forecast data to simulate the future trend of wind power installed capacity under different subsidy policies and explore the strength of wind power subsidies in China during the “14th Five-Year Plan” period (2021–2025). The results show that both the GM(1,1) model based on the two-parameter variable-weight buffer operator and the GM(1,1) model with optimized background value have high fitting accuracy, with errors of 0.15% and 4.93%, respectively. Furthermore, in the case of the central government’s subsidy cancellation, the local government should take over the central government’s subsidy policy and adjust the subsidy intensity to 0.57–1 times of that during the “13th Five-Year Plan” period (2015–2020) to achieve the national planning target.
Funder
Soft Science Research Plan Project of Henan Province
Cited by
1 articles.
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