International Journal of Artificial Intelligence and Neural Networks
Author(s) : M.K.RAI , PAWAN KUMAR
A new transmission loss allocation tool based on artificial neural network has been developed and presented in this paper. The proposed artificial neural network computes loss allocation much faster than other methods. A relatively short execution time of the proposed method makes it a suitable candidate for being a part of a real time decision making process. Most independent system variables can be used as inputs to this neural network which in turn makes the loss allocation procedure responsive to practical situations. Moreover, transmission line status (available or failed) was included in neural network inputs to make the proposed network capable of allocating loss even during the failure of a transmission line. The proposed neural networks were utilized to allocate losses in two types of energy transactions: bilateral contracts and power pool operation. Circuit Theory and Orthogonal Projection loss allocation methods were utilized to develop training and testing patterns. The 6-bus reliability network was utilized to conduct studies and illustrate numerical examples for bilateral transactions. Techniques were developed to expedite the training of the neural networks and to improve the accuracy of results.