Energy management of electrified mass transit systems with Energy Storage devices

Advanced Energy Management Control for Energy Storage System

“…The minimum supercapacitor voltage is restricted due to current limits in the converter and the achievable conversion ratio. The series RESR and leakage REPR resistance of the supercapacitor modules are 7.1mΩ and 10kΩ respectively [9]. The converter filter inductor LESS is 100µH.…”

“…Limiting the rate-of-change in source output power, to minimise wear thereby increasing the lifetime [2], can be achieved using an ESS with either a fixed rate limiter [6] set to the maximum permissible rate-of-change for the power source, or adding a low-pass [7], [8] or Kalman [9] filter element to the control. The rate limiter or filter cause the ESS to source or sink power during mismatches in source power and load demand, protecting the power source from the sudden load transients.…”

Simulación, Implementación y Pruebas de un Sistema de Compensación en Corriente Directa basado en Ultra Capacitores, para Sistemas Ferroviarios

“…Ahorro de energía: la energía no se disipa en resistencias, sino que es reutilizada para la tracción. Mejor utilización de la infraestructura del sistema de alimentación: al darse un aplanamiento en la curva de demanda y una mejora en la regulación de voltaje, la cantidad de trenes que se pueden alimentar con un mismo sistema se incrementa, y eventualmente, ante una expansión, la distancia de operación podría aumentarse (Battistelli et al, 2012). Este artículo trata sobre el diseño de un sistema de compensación estacionario para el Metro de Medellín, presentando el procedimiento para el dimensionamiento y ubicación del mismo, y el desempeño del prototipo que ha sido instalado.…”

Optimal Energy Management, Location and Size for Stationary Energy Storage System in a Metro Line Based on Genetic Algorithm

“…Several papers have dealt in depth with optimization of energy management strategies of stationary ESSes [12][13][14]. Among them [12] proposes a control strategy based on the maximum kinetic energy recovery throughout braking operations of the running vehicles.…”

“…Firstly, some of the references involve only small amounts of substations and vehicles when modeling the urban railway network [12][13][14][15] and some of them do not take into account the time-variation (network topology change with vehicle movement) and nonlinearity (nonlinearity of substation and regenerative braking) of the network structure. Secondly, and most importantly, the optimization research of energy management strategy and configuration for ESSes will influence each other, and they both affect the performances of urban railway network, while the configuration optimization research of ESSes in reference [16][17][18][19][20][21][22] is on the premise that energy management strategy of ESSes is fixed and invariable.…”