Multi-criteria fuzzy-logic optimized supervision for hybrid railway power substations
Petronela Pankovits, DhakerAbbes, Christophe Saudemont, Stephane Brisse, Julien Pouget,Benoit Robyns, Mathematics and Computers in Simulation, Volume 130, December 2016, Pages 236-250
RÉSUMÉ / 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.
MOTS CLES / KEYWORDS :
Hybrid railway power substation (HRPS) ; Supervision design ; Fuzzy logic (FL) energy management ; Design of experiments (DoE) ; Genetic algorithm (GA)
HRPS supervision system