Transmission loss allocation using combined game theory and artificial neural network

Abstract

An artificial neural network based method is suggested for allocation of transmission loss in a deregulated power system involving bilateral contract based power transactions between power suppliers and the distribution companies. The proposed method allocates transmission losses to operating transactions on the basis of Shapley value game theoretic approach. For this, bilateral transactions for power system are simulated and corresponding losses are obtained through load flow analysis. Shapley value approach is used to calculate the loss allocations. A large number of such simulation cases are generated and a large data pool stores these possible bilateral transactions and the corresponding loss allocations following Shapley value approach. For allocating losses to the transactions of an operating system environment the required neural network is developed online. A simple filtering technique is used to extract the suitable training data that are close enough to the actual operating condition from the generated data pool and neural network is trained online. The performance of such a network when tested on standard power networks has been found to be very encouraging.