Combined Economic and Emission Dispatch using Radial Basis Function

This paper proposes an Artificial Neural Network approach for solving the Combined Economic and Emission Dispatch (CEED) problem using Radial Basic Function (RBF) based neural network. The goal of CEED is to minimize both the operating fuel cost and emission level simultaneously, while satisfying load demand and operational constraints. This multi-objective CEED problem is converted into a single objective function using a modified price penalty factor approach. In this paper, centres which are chosen randomly from input space are chosen such that they are fairly far apart from each other, and covering the whole of input space. Here, centres and weights memorization is done which resulted in improving RBF Network convergence and computation time. The proposed approach is implemented on two test systems and the obtained results are compared with conventional technique.