Power System Transient Stability Assessment Model Construction Using Improved SVM
As computer technology and intelligence progress, many fields begin to develop towards intelligence. Power system is an important component of the whole power grid operation and the work of electronic components and electronic devices, so how to evaluate its stability is an important issue to ensure...
| Main Author: | |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2023-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10320364/ |
| _version_ | 1827355291590590464 |
|---|---|
| author | Qianhui Chen |
| author_facet | Qianhui Chen |
| author_sort | Qianhui Chen |
| collection | DOAJ |
| description | As computer technology and intelligence progress, many fields begin to develop towards intelligence. Power system is an important component of the whole power grid operation and the work of electronic components and electronic devices, so how to evaluate its stability is an important issue to ensure the stable operation of power system. In this study, a power system evaluation model using improved support vector machine algorithm is proposed for the transient state evaluation system of power system. Firstly, the characteristic vector is extracted from the transient steady-state data of power system, and then the traditional support vector machine algorithm is improved by adding Mahalanobis distance. Finally, the algorithm accuracy and precision are compared. It is found that the highest accuracy of the improved algorithm was 96.79%, which was 1.70% higher than that of the lowest algorithm. At the same time, the false alarm rate was lower, which was 0.42% lower than that of the highest algorithm. The accuracy of the improved support vector machine algorithm was 95.62%. Results show a higher accuracy and precision of the improved vector machine algorithm, and it is better in the processing ability and evaluation ability of power system data. |
| first_indexed | 2024-03-08T04:09:36Z |
| format | Article |
| id | doaj.art-7015f06734404c2c95c033cca49b9fc1 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-03-08T04:09:36Z |
| publishDate | 2023-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-7015f06734404c2c95c033cca49b9fc12024-02-09T00:00:49ZengIEEEIEEE Access2169-35362023-01-011113186613187610.1109/ACCESS.2023.333401610320364Power System Transient Stability Assessment Model Construction Using Improved SVMQianhui Chen0https://orcid.org/0009-0002-2788-0784School of Mechanical Engineering, Shangqiu Institute of Technology, Shangqiu, ChinaAs computer technology and intelligence progress, many fields begin to develop towards intelligence. Power system is an important component of the whole power grid operation and the work of electronic components and electronic devices, so how to evaluate its stability is an important issue to ensure the stable operation of power system. In this study, a power system evaluation model using improved support vector machine algorithm is proposed for the transient state evaluation system of power system. Firstly, the characteristic vector is extracted from the transient steady-state data of power system, and then the traditional support vector machine algorithm is improved by adding Mahalanobis distance. Finally, the algorithm accuracy and precision are compared. It is found that the highest accuracy of the improved algorithm was 96.79%, which was 1.70% higher than that of the lowest algorithm. At the same time, the false alarm rate was lower, which was 0.42% lower than that of the highest algorithm. The accuracy of the improved support vector machine algorithm was 95.62%. Results show a higher accuracy and precision of the improved vector machine algorithm, and it is better in the processing ability and evaluation ability of power system data.https://ieeexplore.ieee.org/document/10320364/Power systemtransient statesupport vector machine algorithmassessment capabilityaccuracy |
| spellingShingle | Qianhui Chen Power System Transient Stability Assessment Model Construction Using Improved SVM IEEE Access Power system transient state support vector machine algorithm assessment capability accuracy |
| title | Power System Transient Stability Assessment Model Construction Using Improved SVM |
| title_full | Power System Transient Stability Assessment Model Construction Using Improved SVM |
| title_fullStr | Power System Transient Stability Assessment Model Construction Using Improved SVM |
| title_full_unstemmed | Power System Transient Stability Assessment Model Construction Using Improved SVM |
| title_short | Power System Transient Stability Assessment Model Construction Using Improved SVM |
| title_sort | power system transient stability assessment model construction using improved svm |
| topic | Power system transient state support vector machine algorithm assessment capability accuracy |
| url | https://ieeexplore.ieee.org/document/10320364/ |
| work_keys_str_mv | AT qianhuichen powersystemtransientstabilityassessmentmodelconstructionusingimprovedsvm |