Stationary ultracapacitors storage device for improving energy saving and voltage profile of light transportation networks

Iannuzzi, Diego; Ciccarelli, Flavio; Lauria, D.

doi:10.1016/j.trc.2011.11.002

Cited by 83 publications

(44 citation statements)

References 24 publications

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“…For this reason, the traffic conditions are even more simplified, and sometimes only a single train is included in the studies. Accordingly, the study by [20] uses a simple train load-regeneration profile because its focus is set on the control parameters of the ultracapacitor ESS. However, although it falls outside the scope of the study, the authors explain the importance of taking traffic (timetable) stochastic variables into account.…”

Section: Optimisation Study Scope Headways Remarksmentioning

confidence: 99%

Improving the Traffic Model to Be Used in the Optimisation of Mass Transit System Electrical Infrastructure

et al. 2017

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Among the different approaches for minimising the energy consumption of mass transit systems (MTSs), a common concern for MTS operators is the improvement of the electrical infrastructure. The traffic on the lines under analysis is one of the most important inputs to the studies devoted to improving MTS infrastructure, since it represents where and how frequently it is possible to save energy. However, on the one hand, MTS electrical studies usually simplify the traffic model, which may lead to a misrepresentation of the energy interactions between trains. On the other hand, if the stochastic traffic is rigorously modelled, the size of the simulation problem could grow excessively, which in turn could make the time to obtain results unmanageable. To cope with this issue, this paper presents a method to obtain a reduced-size set of representative scenarios. Firstly, a traffic model including the most representative stochastic traffic variables is developed. Secondly, a function highly correlated with energy savings is proposed to make it possible to properly characterise the traffic scenarios. Finally, this function is used to select the most representative scenarios. The representative scenario set obtained by the application of this method is shown to be sufficiently accurate with a limited number of scenarios. The traffic approach in this paper improves the accuracy with respect to the usual traffic approach used in the literature.

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Section: Optimisation Study Scope Headways Remarksmentioning

confidence: 99%

Improving the Traffic Model to Be Used in the Optimisation of Mass Transit System Electrical Infrastructure

et al. 2017

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“…This is typically useful for studies of on-vehicle [5][6][7] and railside energy storage [5,8,9]. When is it optimal to charge/discharge?…”

Section: Contributionmentioning

confidence: 99%

An SOS2-based moving trains, fixed nodes, railway power system simulator

Abrahamsson¹,

Söder²

2014

WIT Transactions on the Built Environment

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This paper presents and proposes an optimization model for railway power supply system simulations. It includes detailed power systems modeling, train movements in discretized time considering running resistance and other mechanical constraints, and the voltage-drop-induced reduction of possible train tractive forces. The model has a fixed number of stationary power system nodes. The proposed model uses SOS2 (special ordered sets of type 2) variables to distribute the train loads to the two most adjacent power system nodes available.The impact of the number of power system nodes along the contact line and the discretized time step length impacts on model accuracy and computation times are investigated.The program is implemented in GAMS (General Algebraic Modeling System). Experiences from various solver choices are also presented. The train traveling times are minimized in the example. Other studies could, e.g. consider energy consumption minimization. The numerical example is representative for a Swedish non-centralized, rotary-converter fed railway power supply system. The proposed concept is however generalizable and could be applied for all kinds of moving load power system studies.

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“…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].…”

Section: Introductionmentioning

confidence: 99%

“…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.…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2015

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Abstract:The installation of stationary super-capacitor energy storage system (ESS) in metro systems can recycle the vehicle braking energy and improve the pantograph voltage profile. This paper aims to optimize the energy management, location, and size of stationary super-capacitor ESSes simultaneously and obtain the best economic efficiency and voltage profile of metro systems. Firstly, the simulation platform of an urban rail power supply system, which includes trains and super-capacitor energy storage systems, is established. Then, two evaluation functions from the perspectives of economic efficiency and voltage drop compensation are put forward. Ultimately, a novel optimization method that combines genetic algorithms and a simulation platform of urban rail power supply system is proposed, which can obtain the best energy management strategy, location, and size for ESSes simultaneously. With actual parameters of a Chinese metro line applied in the simulation comparison, certain optimal scheme of ESSes' energy management strategy, location, and size obtained by a novel optimization method can achieve much better performance of metro systems from the perspectives of two evaluation functions. The simulation result shows that with the increase of weight coefficient, the optimal energy management strategy, locations and size of ESSes appear certain regularities, and the best compromise between economic efficiency and voltage drop compensation can be obtained by a novel optimization method, which can provide a valuable reference to subway company. OPEN ACCESSEnergies 2015, 8 11619

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Stationary ultracapacitors storage device for improving energy saving and voltage profile of light transportation networks

Cited by 83 publications

References 24 publications

Improving the Traffic Model to Be Used in the Optimisation of Mass Transit System Electrical Infrastructure

Improving the Traffic Model to Be Used in the Optimisation of Mass Transit System Electrical Infrastructure

An SOS2-based moving trains, fixed nodes, railway power system simulator

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

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