Issue |
RAIRO-Oper. Res.
Volume 55, Number 5, September-October 2021
|
|
---|---|---|
Page(s) | 3049 - 3072 | |
DOI | https://doi.org/10.1051/ro/2021136 | |
Published online | 13 October 2021 |
Forecasting the wind power generation in China by seasonal grey forecasting model based on collaborative optimization
School of Business, Jiangnan University, Wuxi, Jiangsu 214122, P.R. China
* Corresponding author: wuyongqian@jiangnan.edu.cn
Received:
8
March
2021
Accepted:
29
August
2021
Renewable energy represented by wind energy plays an increasingly important role in China’s national energy system. The accurate prediction of wind power generation is of great significance to China’s energy planning and power grid dispatch. However, due to the late development of the wind power industry in China and the lag of power enterprise information, there are little historical data available at present. Therefore, the traditional large sample prediction method is difficult to be applied to the forecasting of wind power generation in China. For this kind of small sample and poor information problem, the grey prediction method can give a good solution. Thus, given the seasonal and long memory characteristics of the seasonal wind power generation, this paper constructs a seasonal discrete grey prediction model based on collaborative optimization. On the one hand, the model is based on moving average filtering algorithm to realize the recognition of seasonal and trend features. On the other hand, based on the optimization of fractional order and initial value, the collaborative optimization of trend and season is realized. To verify the practicability and accuracy of the proposed model, this paper uses the model to predict the quarterly wind power generation of China from 2012Q1 to 2020Q1, and compares the prediction results with the prediction results of the traditional GM(1,1) model, SGM(1,1) model and Holt-Winters model. The results are shown that the proposed model has a strong ability to capture the trend and seasonal fluctuation characteristics of wind power generation. And the long-term forecasts are valid if the existing wind power expansion capacity policy is maintained in the next four years. Based on the forecast of China’s wind power generation from 2021Q2 to 2024Q2 in the future, it is predicted that China’s wind power generation will reach 239.09 TWh in the future, which will be beneficial to the realization of China’s energy-saving and emission reduction targets.
Mathematics Subject Classification: 90B99 / 62P30
Key words: Discrete grey forecasting model / fractional-order accumulation generation / seasonal adjustment / wind power generation
© The authors. Published by EDP Sciences, ROADEF, SMAI 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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