Forecasting Renewable Energy Consumption Using a Novel Fractional Grey Reverse Accumulation Model
The accumulation operation is the most fundamental method for processing data in grey models, playing a decisive role in the accuracy of model predictions. However, the traditional forward accumulation method does not adhere to the principle of prioritizing new information. Therefore, we propose a n...
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MDPI AG
2025-01-01
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| author | Yipeng Zhang Huiping Wang |
| author_facet | Yipeng Zhang Huiping Wang |
| author_sort | Yipeng Zhang |
| collection | DOAJ |
| description | The accumulation operation is the most fundamental method for processing data in grey models, playing a decisive role in the accuracy of model predictions. However, the traditional forward accumulation method does not adhere to the principle of prioritizing new information. Therefore, we propose a novel fractional reverse accumulation, which increases the accumulation coefficient for new data to fully utilize the new information carried by the latest data. This led to the development of a novel grey model, termed the FGRM(1,1). This model was validated using renewable energy consumption data from France, Spain, the UK, and Europe, and the results demonstrated that the FGRM(1,1) outperformed other models in terms of simulation error, prediction error, and comprehensive error. The predictions indicated significant growth in renewable energy consumption for France and Spain, moderate growth for the UK, and robust growth for Europe overall. These findings highlight the effectiveness of the proposed model in utilizing new information and provide insights into energy transition and emission reduction potential in Europe. |
| format | Article |
| id | doaj-art-d89c1b678eeb47309baa73ac15f66a6f |
| institution | Kabale University |
| issn | 2079-8954 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | MDPI AG |
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| series | Systems |
| spelling | doaj-art-d89c1b678eeb47309baa73ac15f66a6f2025-01-24T13:50:37ZengMDPI AGSystems2079-89542025-01-011315110.3390/systems13010051Forecasting Renewable Energy Consumption Using a Novel Fractional Grey Reverse Accumulation ModelYipeng Zhang0Huiping Wang1School of Economics, Wuhan University of Technology, Wuhan 430070, ChinaResource Environment and Regional Economic Research Center, Xi’an University of Finance and Economics, Xi’an 710100, ChinaThe accumulation operation is the most fundamental method for processing data in grey models, playing a decisive role in the accuracy of model predictions. However, the traditional forward accumulation method does not adhere to the principle of prioritizing new information. Therefore, we propose a novel fractional reverse accumulation, which increases the accumulation coefficient for new data to fully utilize the new information carried by the latest data. This led to the development of a novel grey model, termed the FGRM(1,1). This model was validated using renewable energy consumption data from France, Spain, the UK, and Europe, and the results demonstrated that the FGRM(1,1) outperformed other models in terms of simulation error, prediction error, and comprehensive error. The predictions indicated significant growth in renewable energy consumption for France and Spain, moderate growth for the UK, and robust growth for Europe overall. These findings highlight the effectiveness of the proposed model in utilizing new information and provide insights into energy transition and emission reduction potential in Europe.https://www.mdpi.com/2079-8954/13/1/51forecastingrenewable energy consumptionfractional reverse accumulationgrey model |
| spellingShingle | Yipeng Zhang Huiping Wang Forecasting Renewable Energy Consumption Using a Novel Fractional Grey Reverse Accumulation Model Systems forecasting renewable energy consumption fractional reverse accumulation grey model |
| title | Forecasting Renewable Energy Consumption Using a Novel Fractional Grey Reverse Accumulation Model |
| title_full | Forecasting Renewable Energy Consumption Using a Novel Fractional Grey Reverse Accumulation Model |
| title_fullStr | Forecasting Renewable Energy Consumption Using a Novel Fractional Grey Reverse Accumulation Model |
| title_full_unstemmed | Forecasting Renewable Energy Consumption Using a Novel Fractional Grey Reverse Accumulation Model |
| title_short | Forecasting Renewable Energy Consumption Using a Novel Fractional Grey Reverse Accumulation Model |
| title_sort | forecasting renewable energy consumption using a novel fractional grey reverse accumulation model |
| topic | forecasting renewable energy consumption fractional reverse accumulation grey model |
| url | https://www.mdpi.com/2079-8954/13/1/51 |
| work_keys_str_mv | AT yipengzhang forecastingrenewableenergyconsumptionusinganovelfractionalgreyreverseaccumulationmodel AT huipingwang forecastingrenewableenergyconsumptionusinganovelfractionalgreyreverseaccumulationmodel |