TY - GEN
T1 - Determination of generators' contributions to loads in pool based power system using least squares support vector machine
AU - Mustafa, M. W.
AU - Sulaiman, M. H.
AU - Shareef, H.
AU - Abd Khalid, S. N.
PY - 2010
Y1 - 2010
N2 - This paper attempts to allocate the generators' contributions to loads in pool based power system by incorporating the Least Squares Support Vector Machine (LSSVM). The idea is to use supervised learning approach to train the LS-SVM. The technique that uses proportional tree method (PTM) which is applying the convention of proportional sharing principle is utilized as a teacher. Based on converged load flow and followed by PTM for power tracing procedure, the description of inputs and outputs of the training data for the LSSVM are created. The LS-SVM will learn to identify which generators are supplying to which loads. The proposed technique is demonstrated using IEEE 14-bus system to illustrate the effectiveness of the LS-SVM technique compared to that of the PTM. The comparison result with Artificial Neural Network (ANN) technique is also will be discussed.
AB - This paper attempts to allocate the generators' contributions to loads in pool based power system by incorporating the Least Squares Support Vector Machine (LSSVM). The idea is to use supervised learning approach to train the LS-SVM. The technique that uses proportional tree method (PTM) which is applying the convention of proportional sharing principle is utilized as a teacher. Based on converged load flow and followed by PTM for power tracing procedure, the description of inputs and outputs of the training data for the LSSVM are created. The LS-SVM will learn to identify which generators are supplying to which loads. The proposed technique is demonstrated using IEEE 14-bus system to illustrate the effectiveness of the LS-SVM technique compared to that of the PTM. The comparison result with Artificial Neural Network (ANN) technique is also will be discussed.
KW - Artificial neural network (ann)
KW - Least squares support vector machine (ls-svm)
KW - Pool based power system
KW - Proportional tree method (ptm)
KW - Supervised learning
UR - http://www.scopus.com/inward/record.url?scp=77958015941&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=77958015941&partnerID=8YFLogxK
U2 - 10.1109/PEOCO.2010.5559183
DO - 10.1109/PEOCO.2010.5559183
M3 - Conference contribution
AN - SCOPUS:77958015941
SN - 9781424471287
T3 - PEOCO 2010 - 4th International Power Engineering and Optimization Conference, Program and Abstracts
SP - 226
EP - 231
BT - PEOCO 2010 - 4th International Power Engineering and Optimization Conference, Program and Abstracts
T2 - 4th International Power Engineering and Optimization Conference, PEOCO 2010
Y2 - 23 June 2010 through 24 June 2010
ER -