Application of neural networks to unit commitment

Abstract

In this paper, an improved Hopfield neural network which was described in [1] is applied to unit commitment problem. A new mapping process has been used and a computational method for obtaining the weights and biases is described using a slack variable technique for handling inequality constraints.