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|Title: ||An application of genetic algorithm and least squares support vector machine for tracing the transmission loss in deregulated power system|
|Authors: ||Mohd. Herwan, Sulaiman|
Siti Rafidah, Abdul Rahim
Mohd Wazir, Mustafa
Hussain, Shareef, Dr.
Saifulnizam, Abd. Khalid, Dr.
Proportional sharing method
Support vector machine
Transmission loss allocation
|Issue Date: ||6-Jun-2011 |
|Publisher: ||Institute of Electrical and Electronics Engineers (IEEE)|
|Citation: ||p. 375-380|
|Series/Report no.: ||Proceedings of the 5th International Power Engineering and Optimization Conference (PEOCO 2011)|
|Abstract: ||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.|
|Description: ||Link to publisher's homepage at http://ieeexplore.ieee.org/|
|Appears in Collections:||Conference Papers|
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