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
         
        
        
        
        
            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"
         
        
        
            Conference_Titel : 
Energy Conversion Congress and Exposition (ECCE), 2015 IEEE
         
        
        
            Electronic_ISBN : 
2329-3748
         
        
        
            DOI : 
10.1109/ECCE.2015.7309851