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An application of Genetic Algorithm and Least Squares Support Vector Machine for tracing the transmission loss in deregulated power system

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6 Author(s)
M. W. Mustafa ; Faculty of Electrical Engineering, Universiti Teknologi Malaysia, Johor 81310, Malaysia ; M. H. Sulaiman ; H. Shareef ; S. N. Abd. Khalid
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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.

Published in:

Power Engineering and Optimization Conference (PEOCO), 2011 5th International

Date of Conference:

6-7 June 2011