Artificial neural network-based methodology for short-term electric load scenario generation

In this paper a novel scenario generation methodology based on artificial neural networks (ANNs) is proposed. The methodology is able to create scenarios for various power system-related stochastic variables. Scenario reduction methodologies can then be applied to effectively reduce the number of scenarios. An application of the methodology for the creation of short-term electric load scenarios for one day up to seven days ahead is presented. Test results on the real-world insular power system of Crete present the effectiveness of the proposed methodology.