Towards railway-smartgrid: Energy management optimization for hybrid railway power substations

In order to analyze the feasibility of implementing Smart Grid technologies at railway network scale, this paper presents an optimization study of hybrid railway power substations energy management. Fuzzy logic supervision strategy is developed to achieve renewable energy sources and storage units' coordination in the railway power substation. Objectives such as limitation of the exceeding subscribed power by favoring local renewable energy consumption are considered through empirically defined supervision parameters. Declared as optimization variables, these are the inputs and outputs of the fuzzy logic membership functions. Then, adapted economic indicators chosen to quantify supervision's performance are defined as the objective functions in the optimization model. To solve the problem, experimental design and genetic algorithm are iteratively implemented in an optimization interface. Eventually, to illustrate the influence of the optimization procedure on the system supervision, the simulation results of the optimal solution are analyzed.

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