A novel combined model based on advanced optimization algorithm for short-term wind speed forecasting
•A combined model based on advanced optimization algorithm is successfully proposed.•Design three experiments from the real wind farm to verify the effectiveness.•The proposed combined model can enhance the forecasting accuracy significantly.•Experiments demonstrate the availability and reliability...
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| Published in: | Applied energy Vol. 215; pp. 643 - 658 |
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| Main Authors: | , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Elsevier Ltd
01.04.2018
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| Subjects: | |
| ISSN: | 0306-2619, 1872-9118 |
| Online Access: | Get full text |
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| Abstract | •A combined model based on advanced optimization algorithm is successfully proposed.•Design three experiments from the real wind farm to verify the effectiveness.•The proposed combined model can enhance the forecasting accuracy significantly.•Experiments demonstrate the availability and reliability of the developed model.
Short-term wind speed forecasting has a significant influence on enhancing the operation efficiency and increasing the economic benefits of wind power generation systems. A substantial number of wind speed forecasting models, which are aimed at improving the forecasting performance, have been proposed. However, some conventional forecasting models do not consider the necessity and importance of data preprocessing. Moreover, they neglect the limitations of individual forecasting models, leading to poor forecasting accuracy. In this study, a novel model combining a data preprocessing technique, forecasting algorithms, an advanced optimization algorithm, and no negative constraint theory is developed. This combined model successfully overcomes some limitations of the individual forecasting models and effectively improves the forecasting accuracy. To estimate the effectiveness of the proposed combined model, 10-min wind speed data from the wind farm in Peng Lai, China are used as case studies. The experiment results demonstrate that the developed combined model is definitely superior compared to all other conventional models. Furthermore, it can be used as an effective technique for smart grid planning. |
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| AbstractList | Short-term wind speed forecasting has a significant influence on enhancing the operation efficiency and increasing the economic benefits of wind power generation systems. A substantial number of wind speed forecasting models, which are aimed at improving the forecasting performance, have been proposed. However, some conventional forecasting models do not consider the necessity and importance of data preprocessing. Moreover, they neglect the limitations of individual forecasting models, leading to poor forecasting accuracy. In this study, a novel model combining a data preprocessing technique, forecasting algorithms, an advanced optimization algorithm, and no negative constraint theory is developed. This combined model successfully overcomes some limitations of the individual forecasting models and effectively improves the forecasting accuracy. To estimate the effectiveness of the proposed combined model, 10-min wind speed data from the wind farm in Peng Lai, China are used as case studies. The experiment results demonstrate that the developed combined model is definitely superior compared to all other conventional models. Furthermore, it can be used as an effective technique for smart grid planning. •A combined model based on advanced optimization algorithm is successfully proposed.•Design three experiments from the real wind farm to verify the effectiveness.•The proposed combined model can enhance the forecasting accuracy significantly.•Experiments demonstrate the availability and reliability of the developed model. Short-term wind speed forecasting has a significant influence on enhancing the operation efficiency and increasing the economic benefits of wind power generation systems. A substantial number of wind speed forecasting models, which are aimed at improving the forecasting performance, have been proposed. However, some conventional forecasting models do not consider the necessity and importance of data preprocessing. Moreover, they neglect the limitations of individual forecasting models, leading to poor forecasting accuracy. In this study, a novel model combining a data preprocessing technique, forecasting algorithms, an advanced optimization algorithm, and no negative constraint theory is developed. This combined model successfully overcomes some limitations of the individual forecasting models and effectively improves the forecasting accuracy. To estimate the effectiveness of the proposed combined model, 10-min wind speed data from the wind farm in Peng Lai, China are used as case studies. The experiment results demonstrate that the developed combined model is definitely superior compared to all other conventional models. Furthermore, it can be used as an effective technique for smart grid planning. |
| Author | Wang, Jianzhou Lu, Haiyan Song, Jingjing |
| Author_xml | – sequence: 1 givenname: Jingjing surname: Song fullname: Song, Jingjing organization: School of Statistics, Dongbei University of Finance and Economics, Dalian, China – sequence: 2 givenname: Jianzhou surname: Wang fullname: Wang, Jianzhou email: wjz@lzu.edu.cn organization: School of Statistics, Dongbei University of Finance and Economics, Dalian, China – sequence: 3 givenname: Haiyan surname: Lu fullname: Lu, Haiyan organization: School of Software, Faculty of Engineering and Information Technology, University of Technology, Sydney, Australia |
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| Snippet | •A combined model based on advanced optimization algorithm is successfully proposed.•Design three experiments from the real wind farm to verify the... Short-term wind speed forecasting has a significant influence on enhancing the operation efficiency and increasing the economic benefits of wind power... |
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| SubjectTerms | Advanced optimization algorithm algorithms case studies China Combined model Data preprocessing technique electrical equipment financial economics planning power generation wind farms wind power wind speed Wind speed forecasting |
| Title | A novel combined model based on advanced optimization algorithm for short-term wind speed forecasting |
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