DocumentCode :
3679393
Title :
Optimal energy management of a battery-supercapacitor based light rail vehicle using genetic algorithms
Author :
Victor Isaac Herrera;Haizea Gaztañaga;Aitor Milo;Andoni Saez-de-Ibarra;Ion Etxeberria-Otadui;Txomin Nieva
Author_Institution :
IK4-IKERLAN Technology Research Centre, Arrasate-Mondragon, Gipuzkoa - Spain
fYear :
2015
Firstpage :
1359
Lastpage :
1366
Abstract :
In this paper an optimal energy management strategy (EMS) for a light rail vehicle with an onboard energy storage system combining battery (BT) and supercapacitor (SC) is presented. The optimal targets for the proposed EMS are obtained by an optimization process with multi-objective genetic algorithms (GA). The fitness functions are expressed in economic terms, and correspond to the costs related to the energy absorbed from the catenary as well as the BT and SC cycling cost. The case study selected is the tramway of Sevilla. The aim was to minimize the daily operating cost of the tramway taking into account the BT and SC degradation approach and fulfilling the performance of the tramway in the catenary-less zone. A sizing analysis is done taking as optimization variables the BT and SC sizing to evaluate the impact on the daily operating cost. A comparison between the optimal solutions and a base scenario is presented.
Keywords :
"Energy management","Genetic algorithms","Discharges (electric)","Optimization","Batteries","Mathematical model","Resistance"
Publisher :
ieee
Conference_Titel :
Energy Conversion Congress and Exposition (ECCE), 2015 IEEE
ISSN :
2329-3721
Electronic_ISBN :
2329-3748
Type :
conf
DOI :
10.1109/ECCE.2015.7309851
Filename :
7309851
Link To Document :
بازگشت