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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.
Omar, Aliman
???metadata.dc.contributor.url???: wazir@fke.utm.my
Keywords: Deregulation;Genetic algorithm;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/
URI: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5970400
ISBN: 978-1-4577-0354-6
Appears in Collections:Conference Papers

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