An application of genetic algorithm and least squares support vector machine for tracing the transmission loss in deregulated power system
This paper proposes a new method to trace the transmission loss in deregulated power system by applying Genetic Algorithm (GA) and Least Squares Support Vector Machine (LS-SVM). The idea is to use GA as an optimizer to find the optimal values of hyper-parameters of LS-SVM and adopt a supervised lear...
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| Format: | Conference or Workshop Item |
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2011
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| _version_ | 1796858773330984960 |
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| author | Mustafa, Mohd. Wazir Sulaiman, M. H. Shareef, H. Abd. Khalid, S. N. Abd. Rahim, S. R. Alima, O. |
| author_facet | Mustafa, Mohd. Wazir Sulaiman, M. H. Shareef, H. Abd. Khalid, S. N. Abd. Rahim, S. R. Alima, O. |
| author_sort | Mustafa, Mohd. Wazir |
| collection | ePrints |
| description | This paper proposes a new method to trace the transmission loss in deregulated power system by applying Genetic Algorithm (GA) and Least Squares Support Vector Machine (LS-SVM). The idea is to use GA as an optimizer to find the optimal values of hyper-parameters of LS-SVM and adopt a supervised learning approach to train the LS-SVM model. The well known proportional sharing method (PSM) is used to trace the loss at each transmission line which is then utilized as a teacher in the proposed hybrid technique called GA-SVM method. Based on load profile as inputs and PSM output for transmission loss allocation, the GA-SVM model is expected to learn which generators are responsible for transmission losses. In this paper, IEEE 14-bus system is used to show the effectiveness of the proposed method. |
| first_indexed | 2024-03-05T19:17:24Z |
| format | Conference or Workshop Item |
| id | utm.eprints-45552 |
| institution | Universiti Teknologi Malaysia - ePrints |
| last_indexed | 2024-03-05T19:17:24Z |
| publishDate | 2011 |
| record_format | dspace |
| spelling | utm.eprints-455522017-09-20T08:02:59Z http://eprints.utm.my/45552/ An application of genetic algorithm and least squares support vector machine for tracing the transmission loss in deregulated power system Mustafa, Mohd. Wazir Sulaiman, M. H. Shareef, H. Abd. Khalid, S. N. Abd. Rahim, S. R. Alima, O. This paper proposes a new method to trace the transmission loss in deregulated power system by applying Genetic Algorithm (GA) and Least Squares Support Vector Machine (LS-SVM). The idea is to use GA as an optimizer to find the optimal values of hyper-parameters of LS-SVM and adopt a supervised learning approach to train the LS-SVM model. The well known proportional sharing method (PSM) is used to trace the loss at each transmission line which is then utilized as a teacher in the proposed hybrid technique called GA-SVM method. Based on load profile as inputs and PSM output for transmission loss allocation, the GA-SVM model is expected to learn which generators are responsible for transmission losses. In this paper, IEEE 14-bus system is used to show the effectiveness of the proposed method. 2011 Conference or Workshop Item PeerReviewed Mustafa, Mohd. Wazir and Sulaiman, M. H. and Shareef, H. and Abd. Khalid, S. N. and Abd. Rahim, S. R. and Alima, O. (2011) An application of genetic algorithm and least squares support vector machine for tracing the transmission loss in deregulated power system. In: The 5th International Power Engineering And Optimization Conference (PEOCO 2011). http://dx.doi.org/10.1109/PEOCO.2011.5970400 |
| spellingShingle | Mustafa, Mohd. Wazir Sulaiman, M. H. Shareef, H. Abd. Khalid, S. N. Abd. Rahim, S. R. Alima, O. An application of genetic algorithm and least squares support vector machine for tracing the transmission loss in deregulated power system |
| title | An application of genetic algorithm and least squares support vector machine for tracing the transmission loss in deregulated power system |
| title_full | An application of genetic algorithm and least squares support vector machine for tracing the transmission loss in deregulated power system |
| title_fullStr | An application of genetic algorithm and least squares support vector machine for tracing the transmission loss in deregulated power system |
| title_full_unstemmed | An application of genetic algorithm and least squares support vector machine for tracing the transmission loss in deregulated power system |
| title_short | An application of genetic algorithm and least squares support vector machine for tracing the transmission loss in deregulated power system |
| title_sort | application of genetic algorithm and least squares support vector machine for tracing the transmission loss in deregulated power system |
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