An intelligent evaluation method for steady-state power quality in distribution networks incorporating dynamic correlations
To accurately and efficiently evaluate the steady-state power quality at key nodes in a distribution network， a hierarchical intelligent evaluation method for steady-state power quality metrics incorporating dynamic correlations is proposed. First， the maximum information coefficient （MIC） is used t...
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zhejiang electric power
2024-12-01
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| Series: | Zhejiang dianli |
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| Online Access: | https://zjdl.cbpt.cnki.net/WKE3/WebPublication/paperDigest.aspx?paperID=8f99f055-380e-4a8a-b263-262ce576d6ce |
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| _version_ | 1850033277675503616 |
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| author | GUO Xiangfu ZHANG Xu LIU Shuming WANG Dedao LI Qionglin JIA Zihao SUN Yuanyuan |
| author_facet | GUO Xiangfu ZHANG Xu LIU Shuming WANG Dedao LI Qionglin JIA Zihao SUN Yuanyuan |
| author_sort | GUO Xiangfu |
| collection | DOAJ |
| description | To accurately and efficiently evaluate the steady-state power quality at key nodes in a distribution network， a hierarchical intelligent evaluation method for steady-state power quality metrics incorporating dynamic correlations is proposed. First， the maximum information coefficient （MIC） is used to analyze the relationships among steady-state power quality metrics at these key nodes； then an integrated evaluation system for steady-state power quality is developed. Next， the CRITIC， an objective weighting method， along with the results from the correlation analysis， is employed to calculate the overall weights of each metric in the evaluation system. Finally， the aggregated evaluation score is used as the expected value， and an integrated intelligent evaluation model for steady-state power quality at key nodes is developed using a long short-term memory （LSTM）. The LSTM is optimized with the measured sample data. Simulation results demonstrate that the proposed method significantly reduces the complexity of the evaluation process while maintaining accuracy， thereby greatly enhancing evaluation efficiency. |
| format | Article |
| id | doaj-art-79d1fabc2e1349be936f7e7a86c313ef |
| institution | DOAJ |
| issn | 1007-1881 |
| language | zho |
| publishDate | 2024-12-01 |
| publisher | zhejiang electric power |
| record_format | Article |
| series | Zhejiang dianli |
| spelling | doaj-art-79d1fabc2e1349be936f7e7a86c313ef2025-08-20T02:58:16Zzhozhejiang electric powerZhejiang dianli1007-18812024-12-014312283710.19585/j.zjdl.2024120031007-1881（2024）12-0028-10An intelligent evaluation method for steady-state power quality in distribution networks incorporating dynamic correlationsGUO Xiangfu0ZHANG Xu1LIU Shuming2WANG Dedao3LI Qionglin4JIA Zihao5SUN Yuanyuan6State Grid Henan Electric Power Company， Zhengzhou 450052， ChinaState Grid Pingdingshan Power Supply Company， Pingdingshan， Henan 467000， ChinaState Grid Henan Electric Power Research Institute， Zhengzhou 450052， ChinaState Grid Pingdingshan Power Supply Company， Pingdingshan， Henan 467000， ChinaState Grid Henan Electric Power Research Institute， Zhengzhou 450052， ChinaState Grid Pingdingshan Power Supply Company， Pingdingshan， Henan 467000， ChinaSchool of Electrical Engineering， Shandong University， Jinan 250061， ChinaTo accurately and efficiently evaluate the steady-state power quality at key nodes in a distribution network， a hierarchical intelligent evaluation method for steady-state power quality metrics incorporating dynamic correlations is proposed. First， the maximum information coefficient （MIC） is used to analyze the relationships among steady-state power quality metrics at these key nodes； then an integrated evaluation system for steady-state power quality is developed. Next， the CRITIC， an objective weighting method， along with the results from the correlation analysis， is employed to calculate the overall weights of each metric in the evaluation system. Finally， the aggregated evaluation score is used as the expected value， and an integrated intelligent evaluation model for steady-state power quality at key nodes is developed using a long short-term memory （LSTM）. The LSTM is optimized with the measured sample data. Simulation results demonstrate that the proposed method significantly reduces the complexity of the evaluation process while maintaining accuracy， thereby greatly enhancing evaluation efficiency.https://zjdl.cbpt.cnki.net/WKE3/WebPublication/paperDigest.aspx?paperID=8f99f055-380e-4a8a-b263-262ce576d6cekey nodes in distribution networksteady-state power qualitymiccriticlstm |
| spellingShingle | GUO Xiangfu ZHANG Xu LIU Shuming WANG Dedao LI Qionglin JIA Zihao SUN Yuanyuan An intelligent evaluation method for steady-state power quality in distribution networks incorporating dynamic correlations Zhejiang dianli key nodes in distribution network steady-state power quality mic critic lstm |
| title | An intelligent evaluation method for steady-state power quality in distribution networks incorporating dynamic correlations |
| title_full | An intelligent evaluation method for steady-state power quality in distribution networks incorporating dynamic correlations |
| title_fullStr | An intelligent evaluation method for steady-state power quality in distribution networks incorporating dynamic correlations |
| title_full_unstemmed | An intelligent evaluation method for steady-state power quality in distribution networks incorporating dynamic correlations |
| title_short | An intelligent evaluation method for steady-state power quality in distribution networks incorporating dynamic correlations |
| title_sort | intelligent evaluation method for steady state power quality in distribution networks incorporating dynamic correlations |
| topic | key nodes in distribution network steady-state power quality mic critic lstm |
| url | https://zjdl.cbpt.cnki.net/WKE3/WebPublication/paperDigest.aspx?paperID=8f99f055-380e-4a8a-b263-262ce576d6ce |
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