Comprehensive Evaluation of Electric Power Prediction Models Based on D-S Evidence Theory Combined with Multiple Accuracy Indicators
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...
Main Authors: | , , , , |
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Format: | Article |
Language: | English |
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IEEE
2022-01-01
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Series: | Journal of Modern Power Systems and Clean Energy |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/9433492/ |
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author | Qiong Cui Jizhong Zhu Jie Shu Lei Huang Zetao Ma |
author_facet | Qiong Cui Jizhong Zhu Jie Shu Lei Huang Zetao Ma |
author_sort | Qiong Cui |
collection | DOAJ |
description | 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. |
first_indexed | 2024-04-14T05:40:05Z |
format | Article |
id | doaj.art-4ad2ae4ce4b94c088c4b68ab31d9d8a6 |
institution | Directory Open Access Journal |
issn | 2196-5420 |
language | English |
last_indexed | 2024-04-14T05:40:05Z |
publishDate | 2022-01-01 |
publisher | IEEE |
record_format | Article |
series | Journal of Modern Power Systems and Clean Energy |
spelling | doaj.art-4ad2ae4ce4b94c088c4b68ab31d9d8a62022-12-22T02:09:29ZengIEEEJournal of Modern Power Systems and Clean Energy2196-54202022-01-0110359760510.35833/MPCE.2020.0004709433492Comprehensive Evaluation of Electric Power Prediction Models Based on D-S Evidence Theory Combined with Multiple Accuracy IndicatorsQiong Cui0Jizhong Zhu1Jie Shu2Lei Huang3Zetao Ma4School of Electric Power, South China University of Technology,Guangzhou,ChinaSchool of Electric Power, South China University of Technology,Guangzhou,ChinaKey Laboratory of Renewable Energy, Guangzhou Institute of Energy Conversion, Chinese Academy of Sciences,Guangzhou,ChinaKey Laboratory of Renewable Energy, Guangzhou Institute of Energy Conversion, Chinese Academy of Sciences,Guangzhou,ChinaKey Laboratory of Renewable Energy, Guangzhou Institute of Energy Conversion, Chinese Academy of Sciences,Guangzhou,ChinaA 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.https://ieeexplore.ieee.org/document/9433492/Dempster-Shafer (D-S) evidence theorymultiple accuracy indicatorselectric power prediction modelcomprehensive evaluation |
spellingShingle | Qiong Cui Jizhong Zhu Jie Shu Lei Huang Zetao Ma 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 Dempster-Shafer (D-S) evidence theory multiple accuracy indicators electric power prediction model comprehensive evaluation |
title | Comprehensive Evaluation of Electric Power Prediction Models Based on D-S Evidence Theory Combined with Multiple Accuracy Indicators |
title_full | Comprehensive Evaluation of Electric Power Prediction Models Based on D-S Evidence Theory Combined with Multiple Accuracy Indicators |
title_fullStr | Comprehensive Evaluation of Electric Power Prediction Models Based on D-S Evidence Theory Combined with Multiple Accuracy Indicators |
title_full_unstemmed | Comprehensive Evaluation of Electric Power Prediction Models Based on D-S Evidence Theory Combined with Multiple Accuracy Indicators |
title_short | Comprehensive Evaluation of Electric Power Prediction Models Based on D-S Evidence Theory Combined with Multiple Accuracy Indicators |
title_sort | comprehensive evaluation of electric power prediction models based on d s evidence theory combined with multiple accuracy indicators |
topic | Dempster-Shafer (D-S) evidence theory multiple accuracy indicators electric power prediction model comprehensive evaluation |
url | https://ieeexplore.ieee.org/document/9433492/ |
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