Optimal control and energy storage for DC electric train systems using evolutionary algorithms

نویسندگان

چکیده

Abstract Electrified railways are becoming a popular transport medium and these consume large amount of electrical energy. Environmental concerns demand reduction in energy use peak power railway systems. Furthermore, high transmission losses DC systems make local storage an increasingly attractive option. An optimisation framework based on genetic algorithms is developed to optimise electric rail network terms comprehensive set decision variables including size, charge/discharge limits, timetable train driving style/trajectory maximise benefits reducing consumption. Experimental results for the considered real-world networks show consumption range 15%–30% depending style, reduced peaks.

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ژورنال

عنوان ژورنال: Railway Engineering Science

سال: 2021

ISSN: ['2662-4753', '2662-4745']

DOI: https://doi.org/10.1007/s40534-021-00245-y