Artificial neural network based generation scheduling: a case study for Belgium's national grid

Modern power system energy management system involves generation scheduling as one of the core components. Generation scheduling function has to satisfy the main objective of economics, which involves an optimization of cost over a future period of time. Also it depends on the availability of the various types of generation. The present paper describes an artificial neural network (ANN) based method for scheduling of generation for the national grid of Belgium. The supervised multilayer perceptron based training produces satisfactory results in scheduling of non-renewable energy sources, with prior information on the availability of renewable energy sources. Keywords:Artificial neural network, generation scheduling, non-renewable energy, renewable sources