Abstract: An artificial neural network based cascade correlation algorithms is investigated for the short term generation scheduling of thermal units considering the real power limit of generators, real power demand, spinning reserve, minimum up and down times of the units. In order to expedite the execution, an Artificial neural network is used to generate a possible unit commitment schedule and a heuristic procedure is employed to modify the unit commitment to achieve a feasible and near optimal solution. The cascade correlation algorithm employs several novel modifications, including the ability to add units when necessary. The results of this method are promising when compared to other existing methods.
T. Sree Renga Raja , N.S. Marimuthu and R. Shankara Narayanan , 2005. Short Term Generation Scheduling Using Cascade Correlation Algorithms with Transmission Constraints . Asian Journal of Information Technology, 4: 895-900.