Stationary super-capacitor energy storage system to save regenerative braking energy in a metro line

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

“…Compared to previous work [16][17][18][19][20][21][22], the improved energy management strategy can manage and coordinate the energy flow of multiple ESSes, which can achieve smoother changes of voltages and currents in the system and improve the energy savings of ESSes effectively, and the new proposed optimization algorithm can further improve the performance of ESSes by optimizing energy management parameters, location, and size of ESSes simultaneously, which has rarely been studied in previous work about the optimization of ESSes, and the evaluation functions of proposed optimization algorithm in this paper are more appropriate, which are put forward from the perspectives of economic efficiency and voltage drop compensation.…”

“…Reference [13] proposes a optimization procedure based on a linearized modeling of the electrical LRV network, the target of the control strategy is the optimal tracking of the storage device voltage subject to the minimization of the substations supplied power. Optimal location and size of ESSes are also investigated in detail in [15][16][17][18][19][20][21][22].…”

“…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.…”

Control strategy for wayside supercapacitor energy storage system in railway transit network

“…But, the metro network has not been modeled. Maximum regenerative energy of each station depends on the energy consumption of the auxiliary equipment, resistive forces, traffic conditions, and energy exchange between trains [2,18].…”

“…Regenerative braking energy can be absorbed by the other train in some timing, the can further reduce energy consumption and improver the energy-saving efficiency [2][3][4]. In PSCAD software environment a railway transit network model is built in [5], regenerative current value is simulated in each substation, and has deployed the supercapacitor (SC) in accordance with the capacity and the economic evaluation; In the Matlab environment urban rail traction power supply is simulated and the capacity configuration and energy saving are analyzed in [6]. In [7] and [8], through applying the ESS, the electrical train have been as a useful public transportation that their efficiencies can be improved.…”