ECONOMIC LOAD DISPATCH BY INTEGRATION OF LAGRANGE NEURAL NETWORK AND FEEDFORWARD NEURAL NETWORK - Mohatram, Mohammad (IJRDO -Journal of Computer Science Engineering, 2016)
This paper presents a novel integrated approach to find the load dispatch for economicpower generation in a grid of thermal power plants. A synergy of feedforward neural network(FNN) and Lagrange neural network (LNN) has been introduced in an innovative way.Backpropagation algorithm is used for training the FNN. The data required for training and testingFNN is obtained by LNN. Transmission loss, equality and inequality constraints of economic powergeneration are appropriately considered in the formulation of solution algorithm. The cost ofelectricity generation by a generating unit is expressed exponentially with respect to active poweroutput of the corresponding generating unit. The generation schedule obtained by LNN is mosteconomical whereas a FNN trained by backpropagation algorithm produced results practically inno time. Therefore, the proposed approach produced most economical results in less computationtime