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| Review and prospect of data cleaning in renewable energy power prediction |
| Wu Jiahui1,2, Shao Zhenguo1,2, Yang Shaohua1,2, Xiao Songyong3, Wu Guochang4 |
1. College of Electrical Engineering and Automation,Fuzhou University,Fuzhou 350108;
2. Fujian Smart Electrical Engineering Technology Research Center,Fuzhou 350108;
3. State Grid Putian Electric Power Supply Company,Putian,Fujian 351100;
4. Putian Li Yuan Group Company,Putian,Fujian 351100 |
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Abstract Power prediction is an essential technique for the safe and stable use of renewable energy, which can improve the control performance when the penetration of renewable energy power generation in the system becomes significant. However, large amounts of abnormal data lead to a decrease in prediction accuracy. Through efficient data cleaning, the precision of power prediction can be improved. Therefore, this paper focuses on the review and prospect of data cleaning for the renewable energy power prediction. Firstly, this paper introduces the methods of data cleaning. After the abnormal data are classified, the basic ideas and the application conditions of data cleaning are elaborated and analyzed from two perspectives, which are the rejection of the abnormal values and reconstruction of the missing values. Finally, the key problems in data cleaning for renewable energy are proposed.
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Received: 22 April 2020
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| Cite this article: |
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Wu Jiahui,Shao Zhenguo,Yang Shaohua等. Review and prospect of data cleaning in renewable energy power prediction[J]. Electrical Engineering, 2020, 21(11): 1-6.
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| URL: |
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http://dqjs.cesmedia.cn/EN/Y2020/V21/I11/1
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2020, Vol. 21 
