The application of various artificial intelligent(AI) techniques,namely artificial neural network(ANN),adaptive neuro fuzzy interface system(ANFIS),genetic algorithm optimized least square support vector machine(GA-LS...The application of various artificial intelligent(AI) techniques,namely artificial neural network(ANN),adaptive neuro fuzzy interface system(ANFIS),genetic algorithm optimized least square support vector machine(GA-LSSVM) and multivariable regression(MVR) models was presented to identify the real power transfer between generators and loads.These AI techniques adopt supervised learning,which first uses modified nodal equation(MNE) method to determine real power contribution from each generator to loads.Then the results of MNE method and load flow information are utilized to estimate the power transfer using AI techniques.The 25-bus equivalent system of south Malaysia is utilized as a test system to illustrate the effectiveness of various AI methods compared to that of the MNE method.展开更多
基金the Ministry of Higher Education,Malaysia (MOHE) for the financial funding of this projectUniversiti Kebangsaan Malaysia and Universiti Teknologi Malaysia for providing infrastructure and moral support for the research work
文摘The application of various artificial intelligent(AI) techniques,namely artificial neural network(ANN),adaptive neuro fuzzy interface system(ANFIS),genetic algorithm optimized least square support vector machine(GA-LSSVM) and multivariable regression(MVR) models was presented to identify the real power transfer between generators and loads.These AI techniques adopt supervised learning,which first uses modified nodal equation(MNE) method to determine real power contribution from each generator to loads.Then the results of MNE method and load flow information are utilized to estimate the power transfer using AI techniques.The 25-bus equivalent system of south Malaysia is utilized as a test system to illustrate the effectiveness of various AI methods compared to that of the MNE method.
