2011 2nd Power Electronics, Drive Systems and Technologies Conference
Energy Recovery in a Metro Network using Stationary supercapacitors Reza Teymourfar
Razieh Nejati fard
Behzad Asaei
Hossein Iman-Eini
ECE Department University of Tehran Tehran, Iran
[email protected]
ECE Department University of Tehran Tehran, Iran
[email protected]
ECE Department University of Tehran Tehran, Iran
[email protected]
ECE Department University of Tehran Tehran, Iran Imaneini@ ut.ac.ir
both onboard and stationary systems have been addressed in [12]. However, the control algorithm, the optimal positioning and ESS sizing have not been discussed in these papers. References [13], [14] have employed “Quasi-static backwards looking method” in order to simulate energy consumption in a metro trains.
Abstract—In this paper, the metro supply network and metro trains are modeled using real official data obtained from Tehran metro. This data includes speed cycles of trains, travelling times of trains and technical characteristics of electric trains with considering the return line, which are necessary to design an appropriate energy storage system (ESS). Regenerative current in each station is analyzed and possible energy savings per year are estimated. Stationary supercapacitors are employed to store regenerative currents and necessary capacitance for each station is calculated.
Different possibilities of energy savings in electrical railway systems have been overviewed in [15]. The effect of supercapacitors as energy storage systems on the line voltage and current has been studied in [16]. But, the driving cycle and technical characteristic of the studied system has not been explained in detail. Installation of stationary supercapacitors, the influence of ESS sizing and distribution along the metro lines were evaluated in [17]. However, the variation of regenerative current which is one of the important factors in design of stationary ESS has not been analyzed.
Keywords: Energy Storage System, Supercapacitor, Metro vehicles.
I.
INTRODUCTION
In recent years, the need to find clean energy sources and efforts to decrease the energy consumption has increased due to reduction of fossil fuel sources, increase in the cost of energy, and general concerns about the environment. So in many cities, the use of Electric (or Hybrid) Vehicles has increased to reduce the emissions and energy consumption.
In this article, the models of a DC-750 V metro supply network and metro trains are presented based on real data obtained from Tehran line-3 metro officials. Meanwhile, the variation of regenerative currents is depicted in PSCAD environment. The recovery energy is estimated and necessary capacitance is calculated for each station. The configuration of supercapacitors (as energy storage systems) is also determined for each station.
The recovery of braking energy is significantly important on vehicles such as metro trains which make frequent start and stops. Since most of the power converters at the stations cannot return the braking energy to the supply network, this energy should be wasted in braking resistors or saved in storage systems. Therefore, to use energy better, an energy storage system should be designed for stations.
II.
An effective energy storage system (ESS) should recover braking energy and reduce the energy consumption. It should stabilize the line voltage and reduce the peak input power, resulting in lower losses in the electric lines [1], [2]. Fortunately, supercapacitors are good candidates for energy storage systems. Because, the instantaneous currents are high in metro network and supercapacitors can either sink or source these currents. Additionally, supercapacitors have unique features such as long life, rapid charging, low internal resistance, high power density, and simple charging method which make them suitable for energy storage systems [3-5].
A. Assumptions •
• •
Benefits of onboard ESS in electric trains have been investigated in [6-11]. General benefits of different ESSs for
978-1-61284-421-3/11/$26.00 ©2011 IEEE
CASE STUDY
This study is applied to the line-3 of Tehran Metro network. The total length of the line is about 33 km. It connects the south west of Tehran to the north east of it with 26 stations.
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Total weight of a train with the passengers will be around 355000 Kg (counting on 5 persons per square meter and a weight of 75 kg for each passenger). Total train auxiliaries' consumption is equal to 351 kW, according to the measured value in reality. Driving cycle used for simulations is based on the real measurements and is demonstrated in Fig. 1. The maximum speed during acceleration is 70 km/h and the maximum acceleration is 1 m/s2.
•
80
Line parameters and the efficiency of different components used in the simulations are given in Table. I, and Table. II, respectively.
70
60
III.
Speed(Km/h)
50
MODELING
30
A. Network Model A metro model includes trains, unidirectional substations, energy storage systems (ESSs), and connecting lines which is shown in Fig. 2. Substations are modeled by ideal DC voltage sources with internal resistance of 6 mΩ/ km. The connecting lines are modeled by electric resistances. Since trains are moving among the stations, the electrical resistance between the train, initial station, and next station is time variant. Therefore, in each time step, these values should be calculated according to (1), (2). ′ "
40
20
10
0
0
Figure 1.
200
400
600 t(s)
800
1000
1200
Driving cycle of a train (on line-3) in 10 stations
TABLE I. LINE PARAMETERS
(1) (2)
where, R' is the electrical resistance of train and initial station (Ω/km) and R" is the electrical resistance of train and next station (Ω/km). K represents resistive coefficient which is 0.033 (Ω/km), d is the distance between initial and next stations (km), and x(t) is the distance between train and initial station in each time step.
substation dc voltage(V)
750
Rail electric resistance (mΩ/km)
33
Substations internal resistance (mΩ/km)
6
TABLE II.
Gearbox efficiency (%)
97
Motor efficiency (%)
90
Motor drive efficiency (%)
95
DC/DC converter efficiency (%)
95
Figure 2. Modelling of Metro Network
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COMPONENT EFFICIENCIES
The network model includes first 10 stations of line-3 as a sample of the whole line. In addition, some of the stations do not have rectifier and the stationary ESS, e.g., station 7 doesn’t have any rectifier or stationary ESS. Time span between two trains is 5 minutes, so the cycle of the braking or supplying energy is repeated every 5 minutes in each station. Accordingly, our investigation is limited to time duration of “9:13:49 to 9:18:49”.
The power that is drawn from substation or delivered to supercapacitors, i.e. Pvehicle, is determined by the following equation
P
TABLE IV. station no.10 no.9 no.8 no.7 no.6 no.5 no.4 no.3 no.2 no.1
train no.2 09:05:00 09:07:18 09:09:37 09:11:56 09:14:11 09:16:33 09:18:48 09:21:01 09:23:15 09:24:53
train no.3 09:10:00 09:12:18 09:14:37 09:16:56 09:19:11 09:21:33 09:23:48 09:26:01 09:28:15 09:29:53
P
C. Energy storage system model Fig. 4 shows the stationary ESS model which includes supercapacitors, DC/DC converter and power flow controller. At the charging time, supercapacitors will receive the regenerative power from trains and at the discharging time, they will deliver power to the trains, therefore they can be modeled as ideal current sources. A power flow controller commands the Dc/Dc converter to charge or discharge the supercapacitors, which can be studied in [17].
train no.4 09:15:00 09:17:18 09:19:37 09:21:56 09:24:11 09:26:33 09:28:48 09:31:01 09:33:15 09:34:53
TIME SCHEDUAL OF METRO TRAINS IN RETURN PATH
train no.1 09:00:00 09:01:37 09:03:50 09:06:03 09:08:19 09:10:41 09:12:57 09:15:16 09:17:35 09:19:54
train no.2 09:05:00 09:06:37 09:08:50 09:11:03 09:13:19 09:15:41 09:17:57 09:20:16 09:22:35 09:24:54
train no.3 09:10:00 09:11:37 09:13:50 09:16:03 09:18:19 09:20:41 09:22:57 09:25:16 09:27:35 09:29:54
(3)
(4)
TIME SCHEDUAL OF METRO TRAINS IN FORWARD PATH
train no.1 09:00:00 09:02:18 09:04:37 09:06:56 09:09:11 09:11:33 09:13:49 09:16:01 09:18:15 09:19:53
.
the train speed [ ], and , and represent the gear box efficiency, the motor efficiency and the inverter efficiency, respectively. So, the current which is drawn from substation (or delivered to it) is calculated by the following equation,
B. Train model Trains are modeled as current sources that consume power at the accelerating time (Pvehicle-acc)or generate power at the regenerating time (Pvehicle-reg). The model of the train is depicted in Fig. 3. For modeling the trains as current sources, resistive forces are calculated by the formula proposed in [18].
station no.1 no.2 no.3 no.4 no.5 no.6 no.7 no.8 no.9 no.10
V
F .
where Paccessories is the power required for illumination and cooling (or heating) which is considered to be 351,000 W, M is the total mass of the train with the passengers [Kg], is the train acceleration [ ], Fr is total resistive forces [N.m], V is
Table. III and Table. IV demonstrate the leaving time of trains in forward and return path. The shaded cells (selected times) are in the studied time duration. As it can be seen from Table. III and Table. IV, during the specified time duration, there are 4 trains in the forward path and 4 trains in the return path.
TABLE III.
M
train no.4 09:15:00 09:16:37 09:18:50 09:21:03 09:23:19 09:25:41 09:27:57 09:30:16 09:32:35 09:34:54
Figure 4. stationary ESS model
Figure 3. Schematic of train model
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A. Simulation results
0.5k 0.0 -0.5k -1.0k -1.5k -2.0k -2.5k -3.0k -3.5k
i2(A)
Fig. 5 and Fig. 6 demonstrate regenerative currents for 10 stations in the time interval of 9:13:49 and 9:18:49, when 4 trains are in forward path and 4 trains in return path. It is worth noting that station 7 doesn’t have any rectifier or ESS. According to Fig. 5 and 6, The peak of regenerative currents vary from 619 A at t=168 s in station 1 to 8.4 kA at t=87 s in station 8. Stations 8 and 9 have the highest regenerative currents.
0.5k 0.0 -0.5k -1.0k -1.5k -2.0k -2.5k -3.0k
i3(A)
In station 8, first there is a peak current of 4.84 kA at t=87 s, because at t=76 s the first train on the forward path brakes at station 8 and with a delay of 11 seconds, third train on the return path brakes at station 7 that affects the receiving current of station 8. Another regenerative peak current is at t=256 s, because fourth train on the backward path brakes at t=253 s in station 8 and with a delay of 3 seconds, second train on the forward path brakes in station 7, which affects on the regenerative current of station 8.
i4(A)
0.5k 0.0 -0.5k -1.0k -1.5k -2.0k -2.5k -3.0k 0.5k 0.0 -0.5k -1.0k -1.5k -2.0k -2.5k -3.0k -3.5k -4.0k
i5(A)
In the station 9, there is significant peak current of 6.2 kA at t=217 s since according to driving cycle, trains have the most braking speed (about 66 km/h) when they reach to station 9. At this time, first train brakes with the speed of 66 km/h which result in such a peak current. Additionally, in station 9 there is a negative gradient of -4.252 which intensifies the regenerative peak current.
station1
100 0 -100 -200 -300 -400 -500 -600 -700
i1(A)
IV. SIMULATIONS In this part, several simulations are caried out for the case study described in previous parts. PSCAD software is used to complete the investigation.
t(s)
station2
station3
station4
station5
0
50
100
150
200
250
300
Figure 5. Regenerative current of station 1 to 5
Regenerative energy is calculated for each station and the result is depicted in Fig. 7. Regenerative energy varies from 131.7 MWh/year at the station 1 to 2,206.42 MWh/year at the station 8. This station saves the most energy since it has the most regenerative current which was analyzed in the previous part. Station 1 receives minimum regenerative energy because it has the least traffic. In addition, there is no station behind it and it only receives energy from its following stations.
station6
0.0 -1.0k i6(A)
-2.0k -3.0k -4.0k
i8(A)
-5.0k
Energy saving for each station is computed and is illustrated in Fig. 8. The result shows that energy savings per year is altering between 4% at station 4 and 31% at station 2. Station 2 has the most energy saving because in contrast to other stations, it’s regenerative energy is high (around 1,109.39 MWh/year) and it’s consuming energy is low (around 3,598.17 MWh/year). Station 8 and 9 also have high percentage of energy savings because their regenerative energies are too high according to Fig. 6.
0.0 -1.0k -2.0k -3.0k -4.0k -5.0k -6.0k -7.0k -8.0k -9.0k
staion8
station9
0.0 -1.0k
i9(A)
-2.0k -3.0k -4.0k -5.0k -6.0k -7.0k station10 0.0
i10(A)
B. Proposed ESS configurations Because of low voltage and limited energy of supercapacitors, it is necessary to arrange them in series in order to satisfy operating voltage and to parallel several strings to achieve required energy capacity and power capability.
-1.0k
-2.0k t(s)
0
50
100
150
200
250
Figure 6. Regenerative current of station 6 to 10
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300
1) Criteria 2500
• State of charge (SOC) variation of the supercapacitors will be kept between 25% and 100%, hence the voltage variation will be between 50% and 100% of it’s maximum voltage. So the total energy stored in supercapacitors is determined as follows
2,206.42
2000 MWh/year
1,459.63
1500
1,109.39 1,079.45
1000 500
1,242.38
.
608.97 251.19
131.7
319
•
0 1
2
3
4
5 6 Stations
8
9
10 •
Figure 7. Regenerative energy per year
(3)
The maximum continuous current of supercapacitor cells will be 150 A, and the maximum peak current of the cells (for a duration of 1 second) will be 2,215 A to keep the charging and discharging efficiency over 93%. Maximum voltage of the ESS will be lower than the network voltage, in order to simplify the design of DC/DC converter. So maximum ESS voltage will be 600V.
energy savings /year [%]
2) Proposed modules
•
35 30 25 20 15 10 5 0
31
30
30
18
To save the regenerative energy in each station, suppercapacitors with the capacity of 3000(F) and voltage of 2.7(V) are utilized. In order to tolerate the operating voltage of 600 V, it is necessary to arrange 222 cells in series. It is also necessary to parallel several strings to provide necessary energy in each station. Table. V and Table. VI show the proposed configurations for different stations.
17
16 11
5
I.
4
In this paper, the metro supply network and metro trains were modeled using real data obtained from Tehran line-3 metro officials. The investigation shows that the regenerative current is different from station to station and has the maximum peak of 8.3 kA at the station 8. Energy saving varies from 131.7 MWh/year at station 1 to 2,206.42 MWh/year at station 8. To save the regenerative energy in each station, suppercapacitors of 3000(F) and 2.7(V) were utilized. According to estimated regenerative energies in different substations and necessary capacitance, the appropriate structure for energy storage systems was proposed.
1 2continuous 3 4current 5 of 6supercapacitor 8 9 cells 10 The maximum Stations will be 150 A, and the maximum peak current of the cells (for a duration of 8. 1 second) will per be year 2,215 A to keep the Figure Energy savings cha TABLE V.
REQUIRED CAPACITANCE FOR STATION 1 TO 4
Stations Cells configuration
1
2
3
4
Number of parallel Strings
2
9
6
5
Number of series cells
222
222
222
222
REFERENCES [1]
TABLE VI.
A. Rufer, D. Hotellier and P. Barrade , “A supercapacitor-based energystorage substation for voltage-compensation in weak transportation networks,” Power Tech Conference Proceedings, 2003 IEEE Bologna , vol.3, pp. 8, 23-26 June 2003. [2] A. Rufer, P. Barrade, D. Hotellier and S. Hauser, “Sequential supply for electrical transportation vehicles: properties of the fast energy transfer between supercapacitive tanks,” Industry Applications Conference, 38th IAS Annual Meeting, vol.3, pp. 1530- 1537, 12-16 Oct. 2003. [3] A. Burke, “Ultracapacitors: why, how, and where is the Technology”. J. Power Sources, 2000, 91(1), 37–50
REQUIRED CAPACITANCE FOR STATION 5 TO 10
Stations Cells configuration
5
6
8
9
10
Number of parallel Strings
6
8
20
14
3
Number of series cells
222
222
222
222
222
CONCLUSION
1) Criteria
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[4]
[5]
[6]
[7] [8]
[9]
[10]
[11] [12]
[13]
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[15] W.Gunselmann,“Technologies for increased energy efficiency
in railway systems,” In Proceedings of the EPE2005, Dresden, 2005. [16] Yi-cheng Zhang; Lu-lu Wu; Bo Wang; Hai-quan Liang; , "Modeling and simulation of the 1500V metro supply network and vehicles," Vehicle Power and Propulsion Conference, 2008. VPPC '08. IEEE , pp.1-4, 3-5 Sept. 2008 [17] R.Barrero,X. Tackoen, J.Van Mierlo, "Improving energy efficiency in public transport: Stationary supercapacitor based Energy Storage Systems for a metro network," Vehicle Power and Propulsion Conference, 2008. VPPC '08. IEEE , pp.1-8, 3-5 Sept. 2008 [18] H.William Walter “Rail road engineering,” wiley & sons, chap. 6 and 9, 1982.
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