Heuristic power scheduling of electric vehicle battery charging based on discrete event simulation

Authors:
Stephan Hutterer;Michael Affenzeller;Franz Auinger
Affiliations:
Upper Austria University of Applied Sciences, Austria;Upper Austria University of Applied Sciences, Austria;Upper Austria University of Applied Sciences, Austria
Venue:
EUROCAST'11 Proceedings of the 13th international conference on Computer Aided Systems Theory - Volume Part I
Year:
2011

Citing 2
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Genetic Algorithms and Genetic Programming: Modern Concepts and Practical Applications

Genetic Algorithms and Genetic Programming: Modern Concepts and Practical Applications
Overview: a simulation based metaheuristic optimization approach to optimal power dispatch related to a smart electric grid

LSMS/ICSEE'10 Proceedings of the 2010 international conference on Life system modeling and simulation and intelligent computing, and 2010 international conference on Intelligent computing for sustainable energy and environment: Part II

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Abstract

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.