TY - JOUR
T1 - Heuristic power scheduling of electric vehicle battery charging based on discrete event simulation
AU - Hutterer, Stephan
AU - Affenzeller, Michael
AU - Auinger, Franz
PY - 2012/1
Y1 - 2012/1
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84856941343&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-27549-4_40
DO - 10.1007/978-3-642-27549-4_40
M3 - Article
SN - 0302-9743
VL - 6927
SP - 311
EP - 318
JO - Lecture Notes in Computer Science
JF - Lecture Notes in Computer Science
IS - PART 1
ER -