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Multi-criteria fuzzy-logic optimized supervision for hybrid railway power substations

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  • Pankovits, Petronela
  • Abbes, Dhaker
  • Saudemont, Christophe
  • Brisset, Stephane
  • Pouget, Julien
  • Robyns, Benoit

Abstract

Renewable energy sources and storage units’ integration in the railway power substations is an alternative solution to handle the energy consumption, due to railway traffic increase and electricity market liberalization. To integrate this technology change in the railway network, an adapted energy management system has to be established. However, when considering only energy efficiency aspects on the energy management strategy, an economical viable solution cannot be ensured. This paper proposes a supervision strategy based on multi-criteria approach including energetic, environmental and economic constraints. The energy management objectives such as reducing the network power demand, favoring local renewable consumption and ensuring storage availability are treated in different time levels. Economic aspects are first integrated in predictive mode based on forecast data. Then a supervision strategy is developed based on fuzzy logic approach and graphical tool to build it. An optimization study of the supervision strategy is proposed in order to conclude on system performance. Simulation results are discussed for different scenarios cases and the reaction of the hybrid railway power substation is detailed. Results show that this methodology can be successfully applied for hybrid systems energy management in order to improve their energy efficiency.

Suggested Citation

  • Pankovits, Petronela & Abbes, Dhaker & Saudemont, Christophe & Brisset, Stephane & Pouget, Julien & Robyns, Benoit, 2016. "Multi-criteria fuzzy-logic optimized supervision for hybrid railway power substations," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 130(C), pages 236-250.
    • Handle: RePEc:eee:matcom:v:130:y:2016:i:c:p:236-250
    DOI: 10.1016/j.matcom.2016.05.002
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    References listed on IDEAS

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    1. Robyns, Benoît & Davigny, Arnaud & Saudemont, Christophe, 2013. "Methodologies for supervision of Hybrid Energy Sources based on Storage Systems – A survey," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 91(C), pages 52-71.
    2. Breban, Stefan & Saudemont, Christophe & Vieillard, Sébastien & Robyns, Benoît, 2013. "Experimental design and genetic algorithm optimization of a fuzzy-logic supervisor for embedded electrical power systems," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 91(C), pages 91-107.
    3. Zhou, Wei & Lou, Chengzhi & Li, Zhongshi & Lu, Lin & Yang, Hongxing, 2010. "Current status of research on optimum sizing of stand-alone hybrid solar-wind power generation systems," Applied Energy, Elsevier, vol. 87(2), pages 380-389, February.
    4. Courtecuisse, Vincent & Sprooten, Jonathan & Robyns, Benoît & Petit, Marc & Francois, Bruno & Deuse, Jacques, 2010. "A methodology to design a fuzzy logic based supervision of Hybrid Renewable Energy Systems," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 81(2), pages 208-224.
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    Cited by:

    1. Almaksour, Khaled & Krim, Youssef & Kouassi, N’guessan & Navarro, Nicolas & François, Bruno & Letrouvé, Tony & Saudemont, Christophe & Taunay, Lionel & Robyns, Benoit, 2021. "Comparison of dynamic models for a DC railway electrical network including an AC/DC bi-directional power station," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 184(C), pages 244-266.
    2. Loy-Benitez, Jorge & Safder, Usman & Nguyen, Hai-Tra & Li, Qian & Woo, TaeYong & Yoo, ChangKyoo, 2021. "Techno-economic assessment and smart management of an integrated fuel cell-based energy system with absorption chiller for power, hydrogen, heating, and cooling in an electrified railway network," Energy, Elsevier, vol. 233(C).

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