Simultaneous optimization of sizing and energy management—Application to hybrid train

Marie Poline, Laurent Gerbaud, Julien Pouget and Frédéric Chauvet

Mathematics and Computers in Simulation (MATCOM), 2019, vol. 158, issue C, 355-374

Abstract: The increasing railway traffic and the environmental issue demand to find new solutions to provide energy to autonomous train (train with embedded energy sources such as diesel power supply). Using hybrid diesel train with embedded storage elements is an interesting technical solution but this kind of multisource system presents new scientific and methodology challenges. Thus, in the paper, the problematic focus on the design and the energy management of the different sources for this system. Moreover, these two fields are linked to each other. Indeed, there is a strong influence of the sizing on the energy management but the reverse is also true. The paper deals with a new optimization approach to perform the design of both the hybrid sources sizing and their energy management. The multi-sources system is represented by a power flow model and the energy management strategy is based on a frequency approach and on dynamic programming. This direct optimization problem is solved by the Sequential Quadratic Programming (SQP) algorithm. Thus, in the paper, this optimization approach is applied to a real railway study case. A comparison is made between two cases with different energy management methods.

Keywords: Co-optimization; Sizing; Energy management; Determinist algorithm; Hybrid diesel train (search for similar items in EconPapers)
Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:eee:matcom:v:158:y:2019:i:c:p:355-374

DOI: 10.1016/j.matcom.2018.09.021

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