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Control Research of Supercapcitor Energy Storage System for Urban Rail Transit Network


Control Research of Supercapcitor Energy Storage System for Urban Rail Transit Network
ZongYu Gao1,2
1 College of Automation ,Beijing Union University, 2: School of Electrical Engin

eering, Beijing Jiaotong University, 3: Beijing,China 4: e-mail: zdhtzongyu@buu.edu.cn

Jianjun Fang1 , YiNong Zhang1, Di Sun1 , Lan Jiang1 , Xiaoling Yang1
1.College of Automation ,Beijing Union University, 2. School of Electrical Engineering, Beijing Jiaotong University 3: Beijing,China 4: e-mail: gzy19750510@163.com in reducing energy loss and stabilizing the line voltage, because of its high power density, long cycle-life [4]. Paper [5] in Pscad environment for urban rail network model, regenerative current value on each substation simulation, and has carried on the SC capacity in accordance with the configuration and the economic evaluation; Paper [6] in the Matlab environment for urban rail traction power supply simulation, and respectively under different control strategies for vehicular and ground type SC energy storage system are analyzed in capacity configuration and energy saving. In [7] and [8], electrical trains have been considered as a useful public transportation that their efficiencies can be improved by applying the ESS, however, ESS sizing and network modeling have not been discussed in these references. In [9], different mechanical and electrical techniques have been overviewed in order to improve the energy efficiency in electrical railway systems. In this paper, the characteristic curves of the vehicle and characteristics of the SC are studied, and the characteristics matching relationship of them is analyzed. A new control strategy for the energy storage system based on the power distribution between the SC and the substation is proposed. This strategy has a good effect in suppressing voltage fluctuation, preventing the failure of regenerative braking, and saving energy consumption of vehicle operation. Simulation and experiment have verified the feasibility of this strategy. II.
CHARACTERISTICS OF NETWORK AND CONTROL STRATEGY

Abstract—In order to prevent regenerative energy failure for the metro-trains, this paper proposes a new circuit configuration of an energy storage systems. The system enables improved performance of the powering and the regenerative braking at the high speed region without regeneration failure. Suggests a novel energy management control algorithm for metro trains based on acceleration measurement and estimation. The energy management control is integrated with the motor drive control. The algorithm is based on two nested loops on voltage and current of SC. The voltage and current references are calculated on the basis of the estimation of the train inertial force and motor torque. A simplified mathematical model of the whole electrical drive has been developed, the main features of the circuit configuration and the control strategy have been presented. Numerical simulations show the efficacy of suggested configuration and the energy saving obtained for metro trains. Experimental tests made on an electromechanical simulator fully confirm theoretical results. Keywords—SC; regeneration Regenerative braking failure; control strategy;

I.

INTRODUCTION (Heading 1)

____________________________________ 978-1-4799-3197-2/14/$31.00 ?2014 IEEE

Currently, the " energy saving and emission reduction " and "low-carbon economy" have become the hot issues of social development. Subway system has attracted more and more attentions, due to its advantages of environmental protection and energy saving. With the rapid development of power electronics, AC traction drive technology and regenerative braking have been widely used on the rail vehicle [1]. Regenerative braking energy can be absorbed by the other powering vehicles in the same power supply interval, which can further reduce energy consumption and make the energysaving advantages of the rail transit more prominent. However, when the vehicles operate at a low density, the probability that the regenerative energy is absorbed by other vehicles will be greatly reduced. If there are not enough loads on the line to absorb the regenerative energy, it can easily lead the vehicle pantograph voltage to rise beyond the allowable value [2,3]. Then the main circuit must be cut off, and regenerative braking fails. How to effectively use the surplus energy of regenerative braking, prevent regeneration failure has been a hot point in recent years. The SC has demonstrated excellent performance

Fig.1 Vehicle traction motor characteristic



Fig. 1 shows the characteristic curves of railway vehicle, including voltage, current, torque speed and power. In theory, motor operation states can be divided into three modes: constant torque, constant power and natural characteristics while the vehicle works at powering, coasting and braking condition. When powering, the vehicle absorbs energy from the feeder line, causing the voltage drop; when braking, the vehicle feeds energy to the feeder, leading to voltage rise. The unexpected voltage fluctuation deteriorates the characteristic of the vehicle. The Electrical Driving cycle used for this study is based on the real measurements of beijing metro line5 and is demonstrated in Fig.2. This figure shows the details of driving cycle between two station. Fig.3 shows the running character of whole line. The maximum speed is 80km/h during acceleration and the maximum acceleration is 1m/s2.

A. Train and substation model A train is modeled by a controlled current source. In this model, set the regenerative current limits, it can limit the regenerative current of pantograph. To compute the train power, the resistive forces are calculated by the formula proposed in Ref. Fig.5 is the train model, the line resistance is decided by the distance of two components. Rf is filter resistance of train, Lf is filter inductance of train, Ufc is filter capacitor of train, Pedc is discharge power or charge power of SC, Paux is auxiliary supply power, P is determined by the following equation:

m?

Fig.5 the train model Fig.2 Voltage fluctuation of DC system
su bs tat io n tra in io n su bs ta tio n sta t i o tra n in sta t tra ion in su bs tat su bs tat io n

dI/dt=((Ufc-Uin)-R(I+Iin)-RfI-L*Iin/dt)/(L+Lf) dUfc/dt=(-I-Iinv-Pedlc/Ufc-Paux/Ufc)/Cf Uout=Uin+RIout+LdIout/dt Iout=Iin+I

(3) (4) (5) (6)

upline A

tra in

0km

2.17km

B

5.85km 7.25 km
:Train(coasting)

C

D

9.39 km
:train(braking)

E

11.68km

F

downline

:substation

:Train(powering)

Fig.3 The sketch of a domestic metro line

The metro network model includes trains, unidirectional substations, ESS, and connecting lines that is shown in Fig. 4. Substations are modeled by ideal DC voltage sources. The connecting lines are modeled by electric resistances. Since the trains are moving between the stations, the resistance between the train, the initial station and the next station is time variant. Therefore, in each time step, these values should be calculated according to (1), (2). (1) R'=k*[ W  R''=k* G[ W  (2) where, R' is the resistance between the train and the last station(?/km), and R'' is the resistance between the train and the next station(?/km). k represents the resistive coefficient, the value is 0.019 (? /km), d is the distance between the initial and next stations, and x(t) is the distance between the train and initial station. In simulation environment, the value of resistors can change during the simulation. The network model includes all 24 stations of the line-5 as a sample.
I u11
su11
su12

Fig.6 Traction substation model with SC

I u12
su13

I u ( n ?1)1
su ( n ?1)1
su ( n ?1)2 sd ( n ?1)2

I u ( n?1)2
su ( n ?1)3
sd ( n ?1)3

I sub1

sd 11

sd 12

sd13
I d 12

I sub 2

I sub ( n?1)

sd ( n ?1)1

I subn

I d 11

I d ( n ?1)1

I d ( n ?1)2

Traction substation is uncontrolled rectifier, current is unidirectional. Fig.6 is the model, switch S1 is closed when substation output current is forward direction. Switch S1 is opened when substation output current is negative. In order to model SC charged, substation parallel connection a braking resistor. Switch S2 closed during Vsub ? Uchar , analog SC charging. Switch S2 opened during Vsub ? Uchar , analog SC stopping charge. Through control the closed and open of S2, the remaining energy flowing is controlled between SC with Dc line network. Line network voltage is uprised when emerging renewable brake energy, when line network voltage under Uchar, the energy is absorbed by adjacent train. When line network voltage exceeded Uchar, some renewable energy is absorbed by adjacent train, the remaining renewable energy is absorbed by SC. Ir is renewable current when Isubis negative, the remaining renewable power of substation is Pr=Uout*Ire,remaining renewable energy is Er=?Prdt. Pr and Er is important factor for the SC configuration.

Fig.4 modeling of the metro network



B. Control Strategy Description The hierarchical structure of the EMU control is deduced from the block diagram depicted in Fig.7. Three control parts are considered: Motion Control (MC), Field Oriented Control (FOC), and Energy Saving Control (ESC). The MC and FOC set up the traction drive control; they are focused on the train acceleration and motor torque control respectively. On the contrary the ESC is focused on control of SC-SOC in order to maximize the recovery of kinetic energy during the electrical braking.

Since only a part of the kinetic energy can be actually recovered due to friction and electrical losses, and by keeping in mind that the maximum energy stored in SC is proportional to their weight by means of the coefficient a (energy density), the following equation can be written:
1 2 2 2 3 3 Esc ,ref = C0 (Vsc C1 (Vsc ,max ? usc , ref ) + ,max ? usc , ref 2 3 E · 1 § = k ¨ mt + sc ,max ? (υ0 + at t )2 2 ? α ?

) (9)

φr , ref


1 Lm

isd , ref+

_

isd
Ft , ref

vt ,ref

+ _
vt



÷

1 kT i

+ _
sq , ref

isq

+ _


k

? sgn( Ft ,ref )

vt

<

+ _
Rv
1


vt
kV vdc 1 + sTV



Psc, ref

s vt

usc , ref + _
k

Ru



psc

_

+

isc,ref

Ri

÷
vsc
isc ,max

+ _
isc

vsc,ref

ρ
kA 1 + sTA
kV 1 + sTV

vsc

vsc

Fig. 7. Block diagram of the control system strategies The MC calculates the total force reference, Ft,ref, from the acceleration measurement, at, and reference, at,ref, using a PI controller R?:

Ft ,ref = k I(

Rω )

? (a
t 0

ref t

( Rω ) ? at )dt + k p ( atref ? at ) (7)

The FOC calculates the voltage stator references in (d,q) frame for traction motors on the basis of actual values of train acceleration and traction force. The reference rotor flux of the motor, ?r,ref, is obtained from the actual train acceleration by means of the non-linear-block, R?. The output signal of the SC controller is multiplied with the voltage command signal of the vector controller and the share ratio of the burdens between the main inverter and auxiliary inverters is adjusted. Control circuits of initial charging of SC banks and voltage balancing among three SC banks were developed and implemented as well. The stator voltage in (d,q) frame, then, are transformed in (x,y) stationary frame on the basis of the estimation of rotor flux position, ψ , in order to get the commands for the inverter. The main target of the ESC is the recovery of the kinetic energy available during train braking and the limitation of the line current during acceleration, by properly taking into account the SC-SOC. It consists of cascade SC voltage and current control. The reference can be determined from the consideration that SC voltage has to be changing function of the vehicle acceleration, which is directly related to the kinetic energy of the moving mass. With respect to the full load EMU translating mass and by bearing in mind the (8), the energy stored in the SC can be computed as: 1 2 2 2 3 3 (8) Esc = C0 (Vsc C1 (Vsc ,max ? usc ) + ,max ? u sc ) 2 3
s r ∧

where Vsc,max is the SC rated voltage, usc,ref is the SC reference internal voltage and k is a constant taking into account friction and electrical losses dependent on the previously mentioned efficiencies. The nature of the coefficients of this equation points out that there is one real and two complex roots in the normal range variation of the coefficients, so that the solution of (10) is unique. Eq. (9) points out that SC reference voltage allows the evaluation of SC reference power. From the mathematical model of SC, presented in the previous section, the power output of SC is: du psc = ? ( C0 + 2C1usc ) usc sc (10) dt Making the time derivative of (9) end by substituting it in (10), this reference is equal to:  E § · § <· p sc ,ref = f ¨ vt , vt ? = kat (υ0 + at t ) ¨ mt + sc ,max ? (11) α ? ? ? ? By means of (11), the SC control requires the knowledge of train acceleration. The train acceleration is available from the measure of an encoder placed on the motor shaft and the knowledge of the transmission ratio. According to Fig. 7, the actual value of the acceleration is obtained by integration of the angular velocity, estimated by a digital filter with a PI regulator Rv. The control of SC is integrated with that of the electrical motors, since both are based on the same reference acceleration. The reference current of the modules, isc,ref, is obtained as the algebraic sum of a term that concerns the power  associated to the inertial forces, p sc ,ref , and a compensating term, p sc , which takes into account the error in the evaluation of SC model parameters. The first term, p sc ,ref , is obtained by






(11) using the estimation of train acceleration, at , the knowledge of train acceleration, at, the sign of the traction effort, Ft,ref, and the evaluation of usc,ref given by the solution of  (9). The term p sc is obtained from the PI regulator Ru. Therefore, the optimal current set-point can be finally determined on the basis of (11). control simulation C. Simulation Parameters In order to verify the feasibility of the previous algorithm, a model of single vehicle and substation is built by Matlab/Simulink software. Based on this model, the whole working conditions of the vehicle, including powering, coasting and braking conditions, are simulated. Table I shows the parameters of simulation platform and table II shows the parameters of the SC.

<



TABLE I.

PARAMETERS OF SIMULINK PLATFORM 2000kW 1500V 1100V-1300V 1600V-1800V 3M3T VVVF inverter 1C2M 0.009?/km 0.015?

Rate Power DC-link Voltage Powering Voltage Action Range Braking Voltage Action Range Train gand-up The control mode Steel rail resistance Pantograph resistance

substation simulation system, vehicle simulation systems, and SC energy storage system.
Il

Id IS

L1

R1

L2

LA
C1

LB
CB

R3

T3
C2

R2

Rd
L3
T1
I SC

C3
T2

Lsc

U sc

r

TABLE II.

PARAMETERS OF SC Vmax=2.5V 48F 0.2? 5.1kWh 1000V Fig.9Block diagram of 3kW SC platform

Cell Total capacity Internal resistance Energy Maximum Voltage

D. Simulation platform The new urban rail transit system with SC included four parts: urban rail vehicles; traction substation; SESS(SC Energy Storage System) ; SESS model structure shown as Fig.8. SESS included three parts: Input part, output part and simulation operation part. simulation operation part include train traction computing module, power flow calculation module and SC energy storage module.

The substation simulation system converts 210V AC to 300V DC through the diode rectifier. 210V AC is turned into 380V AC through an auto-regulator and a three-phase isolation transformer (ensure the vehicle simulation system and substation systems connecting to the grid at the same time).Vehicle simulation system is realized by a PWM converter, whose current is fed back to the grid through LCL filter. PWM converter uses grid voltage oriented control method. The reference value Id is calculated according to the characteristics of the vehicle. When the Id > 0, the PWM converter operates in rectifier state, which means the vehicle works in braking condition; when Id <0, the PWM converter operates in inverter state, which means the vehicle is powering or coasting. The SC bank is the product of Beijing Supreme Power Systems Co., Ltd. Parameters are as follows: rate voltage 320V, capacity 1.5F and internal resistance 2.75 ? . The picture of experimental platform is shown in Fig.10.

Fig.10 Prototype of 3kW SC platform

Fig.8 The simulation model block diagram of SESS

This traction computing model include route condition, train parameter and run map message. This route condition include gradient and curve i.e. train parameter is the load of train, auxiliary power, traction and braking curve, run map provided station distribute message, run and stop times of the train. Through this model, the speed, the distance and the power can been got. III. PREPARE YOUR PAPER BEFORE STYLING

B. Experimental results Fig.11 is the simulation result of pantograph current and voltage for vehicle, through the "a" range of Fig.11 that the pantograph voltage is restrained in the value of 1750V during renewable braking, the remaining renewable current of SC is the D-value of expecting renewable current(red line) and grid current(green line). the "b" shown that the train is in the end area of traction and be entering into coasting. At the same time, only the auxiliary power part got energy through Dc supply network and energy consumption is low. but other train is in the area of renewable brake and the pantograph voltage would rise because of the shortage of renewable load.

A. Experimental Platform Based on the above analysis, a 3kW SC experimental platform was set up. The block diagram of the experimental platform is shown in Fig.9. The platform consists of three parts:



intervals

Through previous simulation result, the remaining renewable energy and power can been got for different departure intervals. Fig.13 and 14 shown that SC need to absorb the smaller energy and power when the departure intervals is the shorter. at the same time, capacity configuration not only consider the highest speed but also need to consider multiple factors.
Fig.11The voltge and current in pantograph of train

Fig.12 are the simulation result of different departure interval for multiple trains, these figures shown the result for the current and voltage of pantograph, and remaining renewable energy and power when the Dc Supply network is running. Because the design goal of SC is to absorb remaining renewable energy, so the capacity of SC is decided by the biggest remaining renewable energy and power is decided by the biggest remaining power. Case1-1? headway is 270s

IV.

CONCLUSION

In this paper, the Beijing line-5 metro supply network and vehicle were modeled. For the study, real data of metro line and trains were obtained from metro office. An efficient control strategy was proposed to obtain the maximum instantaneous regenerative energy of each station. Appropriate ESS configurations were proposed for different departure intervals. At last, the simulation model and experimental platform are set up. Simulation and experiment has verified that the control strategy has a significant effect in suppressing the voltage fluctuation and preventing the regeneration failure. ACKNOWLEDGMENT (Heading 5) This work was supported by a grant from the Major State Basic Research Development Program of China (973 Program: 2011CB711100) and new starting point fund (11102591103) REFERENCES
[1] [2] Michael Fronhlich, M. Klohr, and J. Rost, “Energy Storage on Board of Railway Vehicle,” PCIM 2010.Nuremberg,Germany: pp. 391–397. Wang Xuedi, Yang Zhongping,“Study of Electric Double Layer Capacitors
to Improve Electric Network Voltage Fluctuation for Urban Railway Transit,” Electric Drive,vol.39:77-80, 2009.

(a) train pantograph voltage and current of upline (b) layoutplan of upline remaining power and energy

(c) train pantograph voltage and current of downline (d) layoutplan of downline remaining power and energy Fig.12 Multi-trains running simulation results when headway 270s

[3]

C. Analysing of train remaining renewable energy and power
[4]

[5]

[6] Fig.13 The surplus regenerative power of train in different indeparture intervals [7]

[8]

[9]

S.D’Arco,D.Iannuzzi,E.Pagano,P.Tricoli, “Energy management of electric road vehicles equipped with supercaps,”Conf.Rec.of Innovative Power Trains Systems,VDI-Berichte 1852,pp.507-519,2004. Y.Taguchi,M.Ogasa,H.Ijima,S.Ohtsuyama,T.Funaki, “Simulation results of novel energy storage equipment series-connected to the traction inverter,”European Conference on Power Electronics and Applications,pp.1-9,2007. Reza Teymourfar, Behzad Asaei, “Stationary super-capacitor energy storage system to save regenerative braking energy in a metro line” , in:Proc. Energy Conversion and Management,Vol.56,, pp. 206–214, 2012. D. Iannuzzi, F. Murolo, and P. Tricoli,, “A sample application of SC storage system for suburban transit,” in Proc. Int. Conf. Elect. Syst. for Aircraft, Railway and Ship Propulsion, Bologna, Italy, Oct. 19– 21, pp. 1–7,2010. R. A. Smith, “Railways: how they may contribute to a sustainable future” , Proc. IMechE, Part F: J. Rail and Rapid Transit,Vol.217, No. 2, pp. 243–248, 2003. S.Kamata, “JR East takes up the challenge of 'searching for a railway that is kinder to the Earth'”, Proc.IMechE, Part F: J. Rail and Rapid Transit, Vol. 214, No. 2, pp117–122,2000. W.Gunselmann, “Technologies for increased energy efficiency in railway systems”, In:Proceedings of theEPE, 2005.

Fig.14 The surplus regenerative energy of train in different indeparture




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