Since the electrification of individual traffic may cause a critical load to power grids, methods have to be investigated that are capable of handling its highly stochastic behaviour. From a power grid's point of view, forecasting applications are needed for computing optimal power generation schedules that satisfy end-user's energy needs while considering installed capacities in the grid. In this paper, an optimization framework is being proposed, that uses metaheuristic algorithms for finding these schedules based on individual traffic simulation using discrete-event methodology. Evolution Strategy implemented in HeuristicLab is used as optimization algorithm, where the used parameterization and the achieved results will be shown. © 2012 Springer-Verlag.
CITATION STYLE
Hutterer, S., Affenzeller, M., & Auinger, F. (2012). Heuristic power scheduling of electric vehicle battery charging based on discrete event simulation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6927 LNCS, pp. 311–318). https://doi.org/10.1007/978-3-642-27549-4_40
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