Knowledge Management System Of Guangzhou Institute of Energy Conversion, CAS
| Comprehensive Evaluation of Electric Power Prediction Models Based on D-S Evidence Theory Combined with Multiple Accuracy Indicators | |
Cui, Qiong1,2 ; Zhu, Jizhong1,2; Shu, Jie2; Huang, Lei2; Ma, Zetao2
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| 2022-05-01 | |
| Source Publication | JOURNAL OF MODERN POWER SYSTEMS AND CLEAN ENERGY
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| ISSN | 2196-5625 |
| Volume | 10Issue:3Pages:597-605 |
| Corresponding Author | Zhu, Jizhong(zhujz@scut.edu.cn) |
| Abstract | A comprehensive evaluation method of electric power prediction models using multiple accuracy indicators is proposed. To obtain the preferred models, this paper selects a number of accuracy indicators that can reflect the accuracy of single-point prediction and the correlation of predicted data, and carries out a comprehensive evaluation. First, according to Dempster-Shafer (D-S) evidence theory, a new accuracy indicator based on the relative error (RE) is proposed to solve the problem that RE is inconsistent with other indicators in the quantity of evaluation values and cannot be adopted at the same time. Next, a new dimensionless method is proposed, which combines the efficiency coefficient method with the extreme value method to unify the accuracy indicator into a dimensionless positive indicator, to avoid the conflict between pieces of evidence caused by the minimum value of zero. On this basis, the evidence fusion is used to obtain the comprehensive evaluation value of each model. Then, the principle and the process of consistency checking of the proposed method using the entropy method and the linear combination formula are described. Finally, the effectiveness and the superiority of the proposed method are validated by an illustrative instance. |
| Keyword | Predictive models Evidence theory Biological system modeling Power systems Finite element analysis Correlation Analytical models Dempster-Shafer (D-S) evidence theory multiple accuracy indicators electric power prediction model comprehensive evaluation |
| DOI | 10.35833/MPCE.2020.000470 |
| Indexed By | SCI |
| Language | 英语 |
| Funding Project | National Key R&D Program of China[2016YFB0901405] ; Guangdong Provincial Science and Technology Planning Project of China[2020A0505100004] ; Guangdong Provincial Science and Technology Planning Project of China[2018A050506069] ; Guangdong Provincial Special Fund Project for Marine Economic Development of China[[2020]020] |
| WOS Research Area | Engineering |
| Funding Organization | National Key R&D Program of China ; Guangdong Provincial Science and Technology Planning Project of China ; Guangdong Provincial Special Fund Project for Marine Economic Development of China |
| WOS Subject | Engineering, Electrical & Electronic |
| WOS ID | WOS:000797467700006 |
| Publisher | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://ir.giec.ac.cn/handle/344007/36675 |
| Collection | 中国科学院广州能源研究所 |
| Corresponding Author | Zhu, Jizhong |
| Affiliation | 1.South China Univ Technol, Sch Elect Power, Guangzhou, Peoples R China 2.Chinese Acad Sci, Guangzhou Inst Energy Convers, Key Lab Renewable Energy, Guangzhou, Peoples R China |
| First Author Affilication | GuangZhou Institute of Energy Conversion,Chinese Academy of Sciences |
| Recommended Citation GB/T 7714 | Cui, Qiong,Zhu, Jizhong,Shu, Jie,et al. Comprehensive Evaluation of Electric Power Prediction Models Based on D-S Evidence Theory Combined with Multiple Accuracy Indicators[J]. JOURNAL OF MODERN POWER SYSTEMS AND CLEAN ENERGY,2022,10(3):597-605. |
| APA | Cui, Qiong,Zhu, Jizhong,Shu, Jie,Huang, Lei,&Ma, Zetao.(2022).Comprehensive Evaluation of Electric Power Prediction Models Based on D-S Evidence Theory Combined with Multiple Accuracy Indicators.JOURNAL OF MODERN POWER SYSTEMS AND CLEAN ENERGY,10(3),597-605. |
| MLA | Cui, Qiong,et al."Comprehensive Evaluation of Electric Power Prediction Models Based on D-S Evidence Theory Combined with Multiple Accuracy Indicators".JOURNAL OF MODERN POWER SYSTEMS AND CLEAN ENERGY 10.3(2022):597-605. |
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