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A Demonstration Project for Installation of Battery Energy Storage System in Mass Rapid Transit
Available online at www.sciencedirect.com Available online at www.sciencedirect.com
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Availableonline onlineatatwww.sciencedirect.com www.sciencedirect.com Available Energy Procedia 00 (2017) 000–000 Energy Procedia 00 (2017) 000–000
ScienceDirect ScienceDirect
www.elsevier.com/locate/procedia www.elsevier.com/locate/procedia
Energy Procedia Procedia 00 138(2017) (2017)000–000 93–98 Energy www.elsevier.com/locate/procedia
2017 International Conference on Alternative Energy in Developing Countries and Emerging Economies 2017 International Conference on Alternative Energy in Developing 2017 AEDCEE, 25-26 May 2017, Bangkok,Countries Thailand and Emerging Economies 2017 AEDCEE, 25-26 May 2017, Bangkok, Thailand
A Demonstration Project for Installation of Battery The 15th International Symposium on District Heating andEnergy Cooling Storage A Demonstration Project for Installation of Battery Energy Storage System in Mass Rapid Transit Assessing theSystem feasibility of using theTransit heat demand-outdoor in Mass Rapid Ratniyomchai, Thanatchai district Kulworawanichpong * temperatureTosaphol function for a long-term heat demand forecast Tosaphol Ratniyomchai, Thanatchai Kulworawanichpong*
School of Electrical Engineering, Suranaree University of Technology, 111 Suranaree Avenue, Muang, Nakhon Ratchasima, 30000, Thailand a,b,c a a b c c a School of Electrical Engineering, Suranaree University of Technology, 111 Suranaree Avenue, Muang, Nakhon Ratchasima, 30000, Thailand a
I. Andrić
a
*, A. Pina , P. Ferrão , J. Fournier ., B. Lacarrière , O. Le Corre
IN+ Center for Innovation, Technology and Policy Research - Instituto Superior Técnico, Av. Rovisco Pais 1, 1049-001 Lisbon, Portugal b
Veolia Recherche & Innovation, 291 Avenue Dreyfous Daniel, 78520 Limay, France Abstract c Département Systèmes Énergétiques et Environnement - IMT Atlantique, 4 rue Alfred Kastler, 44300 Nantes, France Abstract This paper presents an application of the stationary Li-ion battery on behalf of battery energy storage system (BESS) in the mass rapid transitpresents system.an The DC electrified have often-frequent during their journey that mean the regenerative braking This paper application of therailways stationary Li-ion battery on stop behalf of battery energy storage system (BESS) in the mass energytransit from system. the trainThe braking is likely torailways regenerate back to the DC electrified network. This energy couldthe potentially support the rapid DC electrified have often-frequent stop during their journey that mean regenerative braking Abstract auxiliary loads onboard and isthe adjacent trains simultaneously; however, network. the electrical brakingcould resistance onboard would energy from the train braking likely to regenerate back to the DC electrified This energy potentially support the dissipate some the surplus The surplus could be however, absolutely the recovered andbraking stored inresistance the stationary BESS and auxiliary loads ofonboard and energy. the adjacent trains energy simultaneously; electrical onboard would District heating networks are commonly addressed in the literature as one of the most effective solutions for decreasing the then this some potential efficiently supplied to support own train’s for acceleration adjacent dissipate of theenergy surplusisenergy. The surplus energy could bethat absolutely recovered and stored in or theother stationary BESStrains and greenhouse gas emissions from the building sector. These systems require high investments which are returned through the heat simultaneously. The energy modifiedisBangkok Transit System Train Sukhumvit Lineacceleration in Thailandor(from – Bearing then this potential efficiently supplied to (BTS)-Sky support that own train’s for otherMochit adjacent trains sales. Due to the changed climate conditions and building renovation policies, heat demand in the future could decrease, stations) is employed for the demonstration withSystem the multi-train simulator ThisLine system has the service 21.60simultaneously. The modified Bangkok Transit (BTS)-Sky Train (MTS). Sukhumvit in Thailand (from distance Mochit –ofBearing prolonging the investment return period. km with is 22employed passengerfor stations and 8 traction substations. The electrified operation system is 750-V rectifier substations to stations) the demonstration with the multi-train simulator (MTS). This system has theDC service distance of 21.60The main scope of this paper is to assess the feasibility of using the heat demand – outdoor temperature function for heat demand supply power through 3rd rail. substations. Results show thatelectrified the energy saving of the BTS systemDC with the stationary BESS km withthe22electric passenger stations andthe 8 traction The operation system is 750-V rectifier substations to forecast. The district of Alvalade, located in Lisbon (Portugal), was used as a case study. The district is consisted of 665 and with braking energy achieved by 13 show timesthat of the BESS andBTS without regenerative energy. supply theregenerative electric power through the is3rd rail. Results thesystem energywith saving of the system with the braking stationary BESS buildings that vary in both construction period and typology. Three weather scenarios (low, medium, high) and three district © Authors. Published by Elsevier Ltd. by 13 times of the system with BESS and without regenerative braking energy. and2017 withThe regenerative braking energy is achieved renovation scenariosPublished were developed (shallow, intermediate, deep). To estimate the error, obtained heat demand values were © 2017 The Ltd. Peer-review under responsibility of Elsevier the Organizing © 2017 The Authors. Authors. Published by by Elsevier Ltd. Committee of 2017 AEDCEE. Peer-review under responsibility of the scientific committee the 2017 developed International onthe Alternative compared with results from a dynamic heat demand model,of previously andConference validated by authors. Energy in Peer-review under responsibility of the Organizing Committee of 2017 AEDCEE. DThe eveloping Countries andwhen Emerging Economies. results showed that only weather change is considered, the margin of error could be acceptable for some applications Keywords: Battery energy storage system; Li-ion battery; regenerative braking energy; mass rapid transit; energy saving (the error in annual demand was lower than 20% for all weather scenarios considered). However, after introducing renovation Keywords: Battery energy storage system; Li-ion battery; regenerative braking energy; mass rapid transit; energy saving scenarios, the error value increased up to 59.5% (depending on the weather and renovation scenarios combination considered). value of slope coefficient increased on average within the range of 3.8% up to 8% per decade, that corresponds to the 1.The Introduction in the number of heating hours of 22-139h during the heating season (depending on the combination of weather and 1.decrease Introduction renovation scenarios considered). On the other hand,both function intercept for 7.8-12.7% per DC decade (depending on the The transportation by the electrified railways AC high speedincreased and intercity trains) and (mass rapid transit, coupled scenarios). The values suggested could be used to modify the function parameters for the scenarios considered, and Theand transportation by the electrified railways speed and intercityintrains) DC (massquality rapid transit, metro light rail vehicles) systems are one ofboth the AC besthigh ground transportation terms and of quantity, safety, improve the accuracy of heat demand estimations.
metro and light rail vehicles) systems are one of the best ground transportation in terms of quantity, quality safety, © 2017 The Authors. Published by Elsevier Ltd. Peer-review under responsibility of the Scientific Committee of The 15th International Symposium on District Heating and * Corresponding author. Tel.: +66- 88-583-7207; fax: +66-44-224601. Cooling.
E-mail address:author. [email protected] * Corresponding Tel.: +66- 88-583-7207; fax: +66-44-224601. E-mail address: [email protected] Keywords: Heat demand; Forecast; Climate change 1876-6102 © 2017 The Authors. Published by Elsevier Ltd. Peer-review of the Organizing Committee of 2017 AEDCEE. 1876-6102 ©under 2017responsibility The Authors. Published by Elsevier Ltd. Peer-review under responsibility of the Organizing Committee of 2017 AEDCEE.
1876-6102 © 2017 The Authors. Published by Elsevier Ltd. Peer-review under responsibility of the Scientific Committee of The 15th International Symposium on District Heating and Cooling. 1876-6102 © 2017 The Authors. Published by Elsevier Ltd. Peer-review under responsibility of the scientific committee of the 2017 International Conference on Alternative Energy in Developing Countries and Emerging Economies. 10.1016/j.egypro.2017.10.065
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energy saving, less time, environmental friendly for both goods and passenger services. Even the electrified railways is less consume energy than other fuel engines in comparison with the same capacity of the load, they still need to do the research and development to enhance the performance the train services. Considering the DC electrified railway systems as the mass rapid transit, there are many researches to improve the efficiency of the DC power network by reusing the energy from the train braking [1]. This braking energy regenerates from the traction motor that acts like the generator during the train braking. Usually, the regenerative braking energy is used to support the auxiliary load onboard and the adjacent train travelling at the same time. In general, the traction substation of the DC electrified mainly consists of the rectifier transformer that is non-bidirectional in power, therefore, the surplus energy from the regenerative braking energy has to dissipate by the electric resistance onboard. At present, there are many studies on the applications of energy storage devices such as batteries, flywheel, electrochemical double-layer capacitor (EDLC) and hybrid energy storage to store the regenerative braking energy [2]. Those energy storages are one of the solutions for using in the mass rapid transit due to the frequent stops and short track. There are two types of the energy storage installations in the DC electrified railways; (1) onboard application is a temporary accumulation the regenerative braking energy and then regenerated the stored energy to support the own train motoring [3-6], and (2) wayside or stationary application is also a temporary accumulation the regenerative braking energy and then regenerated the stored energy to support the adjacent trains motoring [7-9]. Considering the applications of batteries as a Lithium-ion (Li-ion) battery in the DC electrified railways, Li-ion battery is a new energy storage comparing with the conventional batteries. The characteristic of Li-ion battery is high energy density, high efficiency, long-lift time, light-weight and fast in charge and discharge ability [10]. Li-ion battery is the most favorite battery technology for the portable electric devices, especially in automotive market and electrified railway applications. An energy saving and voltage compensation in the DC electrified railway system are achieved by the application of the stationary Li-ion battery [11]. In addition, the catenary-free operation is also capable by the energy support of the onboard Li-ion battery [12]. In this paper, the stationary BESS based on the Li-ion battery is implemented in the mass rapid transit in the BTSSky Train, Sukhumvit Line, Bangkok, Thailand. The train movement model, BESS model, simulation results and conclusion, consecutively conducts the paper. 2. Train movement model The characteristic of the electrified railways movement is obtained from a standard operation curve as shown in Fig. 1., including train motoring mode, cruising mode, coasting mode and braking mode. The speed of the train is limited at the maximum speed and constant at this speed during the cruising mode. The Newton’s second laws of motion is applied for calculating the characteristic of the train movement taken into account, for example, the gradients, friction force, speed limitation, and train operation modes [13]. The absolute force F applies to accelerate the train expressed in (1), where Meff is the effective mass of the train and α is acceleration rated of the train. With the train motion simulation, an appropriated step time is considered with the various train operation modes during the travelling between two adjacent platforms. However, the train operation modes are based on the consecutive modes in Fig. 1, and controlled by the train speed control strategy, for example, P-controller and hysteresis control [14]. F = FT – FR – FG = Meff α FG = Meff g sin θ FR = A + B·v + C·v2 Meff = Mt(1 + λw) + Ml = Mt(1 + λeff)
(1)
where FT is the tractive effort (N); FR is the train resistance force including friction force (kN); FG is the gradient force (N); v is the train speed (km/h); Mt is the tare mass of the train (kg); Ml is the passenger and freight load (kg); λw is the rotary allowance; λeff is the effective mass factor; A (kN), B (kNh/km), and C (kNh2/km2) are the Davis’s coefficients; g is the gravity of earth, 9.81 m/s2.
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Tosaphol Ratniyomchai, Thanatchai Kulworawanichpong / Energy Procedia 00 (2017) 000–000 Tosaphol Ratniyomchai et al. / Energy Procedia 138 (2017) 93–98
Vm
Motoring mode
Cruising mode
F TEmax
Vm is maximum speed
Speed (km/h)
Constant speed at maximum speed
Tractive effort Tractive effort
Coasting mode
Braking mode
F
TEmax vc1 v F
vc1 Constant force
vc2 Constant power
TEmax vc1vc 2 v2
Speed Reduced power
Distance (km)
Fig. 1. Train’s operation modes
Fig. 2. Characteristic of tractive effort and train speed
From (1), the net force related to the Newton’s second law of motion is the summation of the tractive effort, the friction force and the gradient force. The tractive effort is constant at the rated value during the train motoring and reduces slightly depending on the train operational modes and train speed as shown in Fig. 2, where TE is the tractive effort, vc1 and vc2 are the based speed of the cruising and coasting modes, respectively. The gradient force depends on the gradient slope and angle . The friction force and drag force (including aerodynamic and rolling resistance) takes into account the Davis’s equation as the quadratic function of the train speed [15]. The acting forces can also explain an expression of the train movement calculation on the traction vehicle with the uphill direction as shown in Fig. 3.
M eff
Fig. 3. Train’s movement on a gradient
Fig. 4. B-chop system [16]
3. Battery energy storage system The description of the Battery energy storage system (BESS) and the stationary BESS model in the DC electrified railways system are presented as follows: 3.1 Characteristic of the BESS The BESS implemented for the simulation in this paper is based on the B-chop system, which is the energy storage for traction power supply system, Hitachi, Japan. The Lithium-ion (Li-on) battery is applied in the B-chop system as shown in Fig. 4 [16]. BESS is connected to the traction substation (TSS) through the DC-DC converter. In practical, BESS is recharged energy from the regenerative braking energy during the braking mode of the train operation and then discharged energy back to the DC system to support TSS supplying the motoring mode of the train operation. The reuse of the surplus energy as a regenerative braking energy also achieves the energy saving of the DC power supply or TSS and improves the stopping point accuracy. In addition, the voltage stability of the DC electrified railway system prevents the voltage rise and drop by the BESS. With the mechanical maintenance, the maintenance cost of the mechanical break pad of the vehicle is reduced due to the supporting of the electrical break.
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3.2 DC rolling stock model with BESS A TSS of the DC electrified railways or mass rapid transit systems are illustrated as in Fig. 5. In general, at TSS1 and TSS2 consist of the rectifier transformer to convert the AC electrified to DC electrified systems. In this paper, the TSS of the DC electrified railways system is also the DC power supply for the mass rapid transit system. The train consumes the DC power from the conductor rail via collector shoe. The stationary battery energy storage system (BESS) is modeled by the DC power source at TSS2 as shown in Fig. 5. The BESS current discharges to DC busbar supporting the train motion denoted by IBESS. TSS. 1
1
Conductor rail 3
d Rcond
p
C
IS
RS
Ltss d Rcond
R
TSS. 2 BESS
IBESS
IS
RS
Ltss d Rrail
d Rrail
1 1 GRE GRE 2 2
RSE
q
Train
I tr
2
4
1 1 GRE GRE 2 2
RSE
Running rail
Fig. 5. Traction substations with a stationary BESS
Fig. 6. Equivalent circuit of the DC electrified railway system with BESS
In this paper, the DC power network solver with a computer-based simulation of the train movement requires the train position on the track and the electrical power consumption of the train obtained from the previous section. The train position is significantly conducted to form a system of conductance matrix at each step of the train motion. The total electrical power consumption of the trains is considered as the load bus of the DC power network and applied to provide the total power demand of the DC power supply. To obtain the voltage solutions of each TSS, the nodal analysis is implemented to find the solutions [17]. A simplified model of the TSS with a stationary BESS shown in Fig. 5, has presented by the equivalent circuit as shown in Fig. 6. It includes four main sections, including TSS, transmission line, train and BESS. In Fig. 7, d is the train position, Ltss is the track length between TSSs, Is is the TSS current, It is the train current, Rs is the internal TSS resistance, Rcond and Rrail are the conductor rail and running rail resistances, RSE and GRE are the TSS ground resistance and the rail-to-earth conductance, and IBESS is the BESS current. Applying the power calculation based on the nodal analysis provides the solutions of TSS voltages, train voltages, TSS power consumptions, rail potential and power loss in the DC electrified railway system. A current injection model (CIM) [18] is implemented for the TSS currents, train currents and BESS current with multi-conductor system. All solutions such as TSS voltages, train voltage, energy consumptions and so on, obtain by the MTS, see [18]. 4. Results and discussions
Fig. 7. BTS Sukhumvit Line
E14: Bearing
E13: Bang Na
E12: Udom Suk
E11: Punnawithi
E10: Bang Chak
E9: On Nut
E8: Phra Khanong
E7: Ekkamai
E6: Thong Lo
E5: Phrom Phong
E4: Asok
E3: Nana
E2: Phloen Chit
E1: Chit Lom
CS: Siam
N1: Ratchathewi
N2: Phraya Thai
N3: Victory Monument
N4: Sanam Pao
N5: Ari
N6: Sena Ruam
N7: Saphan Khwai
N8: Mo Chit
The rating and specification of the BESS for the DC electrification of 750 V traction power is that the rated voltage is 820 V, rated capacity is 500 kW and rated current is 600 A. In this paper, the power loss during BESS charge and discharge energy is neglected in the simulation. The track work of the simulation is the modified Bangkok Transit System (BTS)-Sky Train Sukhumvit Line in Thailand (from Mochit – Bearing stations) as shown in Fig. 7. The BTS Sukhumvit Line has 22 platforms and 8 TSS. The train headway is 5 minutes, the service distance is 21.6 km, the maximum speed of the trains is 80 km/h and the traction acceleration rate is 1.0 m/s2. The time step of the simulation is 0.5 sec with the total time of the simulation is 1.0 hour. The results of the simulation for evaluation the application BESS are presented as follows:
Tosaphol Ratniyomchai et al. / Energy Procedia 138 (2017) 93–98 Tosaphol Ratniyomchai, Thanatchai Kulworawanichpong / Energy Procedia 00 (2017) 000–000
Fig. 8. Train speed profile, power and voltage
97 5
Fig. 9. The energy profiles of the BESS installed at RS2
The train speed profile, delivery power and terminal voltage of the train 1 obtained from the MTS are shown in Fig. 8. The speed is limited at the maximum speed of 80 km/h. The time of a train runs from the start to the end of the track is about 1860 sec. The positive train power means the power for train motoring whereas the negative train power means the power from the train braking. The nominal train voltage is about 830 Vdc, and it drops during the train motoring. The TSS RS2, RS3 and RS5 have been consecutively chosen to install the BESS that the energy profiles of the BESS at each TSS are shown in Fig. 9 and Fig. 10.
a
b Fig. 10. The energy profiles of the BESS installed at (a) RS3 (b) RS5
In Fig. 9 and Fig. 10, the maximum energy of the BESS is at 0.19 MWh, which is at 100% full charge of the BESS. In comparison Fig. 9. and Fig. 10, it is clear that the capacity of the BESS at RS2 about 0.03 MWh drops less than those of 0.032 MWh and 0.06 MWh at RS3 and RS5, respectively. Therefore, the TSS at RS2 is suitable for installing the BESS due to it obtains the small capacity. The BESS is fixed at the RS2 to find the optimal capacity as the results presented in Table 1. Table 1. Energy consumption, Energy losses and service voltage range with different BESS modules
In
BESS module
MWh consumed
MWh losses
Max RS2 voltage (V)
Min RS2 voltage (V)
1x500 kWp
4.4684
0.4489
881.17
668.98
5x500 kWp
4.3923
0.4489
881.17
668.98
10x500 kWp
4.2971
0.4489
881.17
668.98
20x500 kWp
4.1068
0.4489
881.17
668.98
BC1: NoRG
4.7240
0.4473
800.00
643.31
BC2: RG
4.4874
0.4489
881.17
668.98
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Tosaphol Ratniyomchai et al. / Energy Procedia 138 (2017) 93–98 Tosaphol Ratniyomchai, Thanatchai Kulworawanichpong/ Energy Procedia 00 (2017) 000–000
Table. 1, the BESS modules consist of 1, 5, 10 and 20 time of the peak power of 500 kW. The based case without BESS consists of the DC electrified railways system with no regenerative braking energy (BC1) and with regenerative braking energy (BC2). The energy losses, and the minimum and the maximum voltage of RS2 are almost the same with all BESS modules. However, the energy consumed by the TSS is reduced by all BESS modules comparison with the base case BC1 and BC2. Considering the BESS module of 1x500 kWp, it is the optimal capacity of the BESS to install at TSS RS2 because it can save energy 0.019 MWh comparison with BC1 and 0.2556 MWh comparison with BC2. Other BESS modules can also save more energy than the first module but their capacity is more than the first module with related to the capital cost. With the additional assumption, the daily service hour of the BTS Sukhumvit Line for one day is 16 hours from 6 am to 10 pm, and the electrical tariff is 3.0 THB/kWh. Therefore, the first BESS module of 500 kWp installed at RS2 can save energy 110.96 MWh/year or 332,880 THB/year comparing with BC1 and 1492.1 MWh/year or 4,478,112 THB/year comparing with BC2. 5. Conclusion This paper presents the application of the stationary BESS based on the Li-ion battery in the mass rapid transit of the BTS-Sky Train Sukhumvit Line, Bangkok, Thailand. The BTS system has 22 platforms, which is suitable to apply the regenerative braking energy with the stationary BESS because it is highly frequent of the train stop. This is confirmed by the results of the simulation that the stationary BESS is chosen to install at the TSS R2. The results present that the energy saving of the BTS system with the stationary BESS is achieved with the system with applied the regenerative braking energy by 0.2566 MWh which is 13 time of the BTS system without applied regenerative braking energy. References [ 1] Gonzalez-Gil A, Palacin R, Batty P. Sustainable urban rail systems: Strategies and technologies for optimal management of regenerative braking energy. J Energy Conversion and Management 2013; 75: 374-388. [2] Ratniyomchai T, Hillmansen S, Tricoli P. Recent developments and applications of energy storage devices in electrified railways. J IET Electrical System in Transportation 2014; 4, 9-20. [3] Barrero R, Mierlo JV, Tackoen X. Energy savings in public transport. IEEE Vehicle Technology Magazine 2008. [4] Iannuzzi D. Tricoli P. Speed-based state-of-charge tracking control for metro trains with onboard supercapacitors. IEEE Power Electrononics 2012; 27: 2129-2140. [5] Steiner M,Scholten J. Published. Energy storage on board of DC fed railway vehicles. IEEE annual Power Electronics Specialists Conference – PESC 2004; Aachen, Germany. [6] Meinert M. New mobile energy storage system for rolling stock. 13th European Conference Power Electronics and Applications (EPE) 2009; Barcelona, Spain:1-10. [7] Barrero R, Tackoen X. Mierlo JV. Stationary or onboard energy storage systems for energy consumption reduction in a metro network. Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit 2010; 224: 207-225. [8] Iannuzzi D, Lauria D. Tricoli P. Optimal design of stationary supercapacitors storage devices for light electrical transportation systems. Optimization and Engineering 2012; 13: 698-704. [9] Ratniyomchai T, Hillmansen S. Tricoli P. Optimal capacity and positioning of stationary supercapacitors for light rail vehicle systems. International Symposium Power Electronic Electrical Drives, Automation and Motion (SPEEDAM) 2014, Ischia, Italy. 807-812. [10] Budde-Meiwes H, Drillkens J, Lunz B, Muennix J, Rothgang S, Kowal J. Sauer DU. A review of current automotive battery technology and future prospects. J of Automobile Engineering 2013; 227: 761-776. [11] Okui A, Hase S, Shigeeda H, Konishi T. Yoshi T. Application of energy storage system for railway transportation in Japan. International Conference Power Electronics Conference (IPEC) 2010; Sapporo, Japan: 3117–3123. [12] Ogasa M. Onboard storage in Japanese electrified lines. 14th International Conference on Power Electronics and Motion Control (EPE/PEMC) 2010; Ohrid, Bulgaria: 9-16. [13] Sumpavakup C, Kulworawanichpong T. Multi-train movement simulation using MATLAB object-oriented programming. Appl. Mech. Mater 2015; 763: 153-158. [14] Kulworawanichpong T. Optimising AC electric railway power flows with power electronic control. PhD Thesis 2003, University of Birmingham, UK. [15] Lu S. Optimising power management strategies for railway traction. PhD Thesis 2011, University of Birmingham, UK. [16] http://www.hitachi-rail.com/products/power_supply/equipment/feature03.html [17] Lee HM, Jeon EJ, Jeong SC. A study on calculation of DC railway loadflow with energy storage system. Int. Conf. Control, Automation and Systems 2010; Gyeonggi-do, Korea: 800-803. [18] Kulworawanichpong T. Multi-train modeling and simulation integrated with traction power supply solver using simplified Newton-Raphson method 2015. J. Mod. Transport; 23(4): 241–251.
ScienceDirect ScienceDirect
Availableonline onlineatatwww.sciencedirect.com www.sciencedirect.com Available Energy Procedia 00 (2017) 000–000 Energy Procedia 00 (2017) 000–000
ScienceDirect ScienceDirect
www.elsevier.com/locate/procedia www.elsevier.com/locate/procedia
Energy Procedia Procedia 00 138(2017) (2017)000–000 93–98 Energy www.elsevier.com/locate/procedia
2017 International Conference on Alternative Energy in Developing Countries and Emerging Economies 2017 International Conference on Alternative Energy in Developing 2017 AEDCEE, 25-26 May 2017, Bangkok,Countries Thailand and Emerging Economies 2017 AEDCEE, 25-26 May 2017, Bangkok, Thailand
A Demonstration Project for Installation of Battery The 15th International Symposium on District Heating andEnergy Cooling Storage A Demonstration Project for Installation of Battery Energy Storage System in Mass Rapid Transit Assessing theSystem feasibility of using theTransit heat demand-outdoor in Mass Rapid Ratniyomchai, Thanatchai district Kulworawanichpong * temperatureTosaphol function for a long-term heat demand forecast Tosaphol Ratniyomchai, Thanatchai Kulworawanichpong*
School of Electrical Engineering, Suranaree University of Technology, 111 Suranaree Avenue, Muang, Nakhon Ratchasima, 30000, Thailand a,b,c a a b c c a School of Electrical Engineering, Suranaree University of Technology, 111 Suranaree Avenue, Muang, Nakhon Ratchasima, 30000, Thailand a
I. Andrić
a
*, A. Pina , P. Ferrão , J. Fournier ., B. Lacarrière , O. Le Corre
IN+ Center for Innovation, Technology and Policy Research - Instituto Superior Técnico, Av. Rovisco Pais 1, 1049-001 Lisbon, Portugal b
Veolia Recherche & Innovation, 291 Avenue Dreyfous Daniel, 78520 Limay, France Abstract c Département Systèmes Énergétiques et Environnement - IMT Atlantique, 4 rue Alfred Kastler, 44300 Nantes, France Abstract This paper presents an application of the stationary Li-ion battery on behalf of battery energy storage system (BESS) in the mass rapid transitpresents system.an The DC electrified have often-frequent during their journey that mean the regenerative braking This paper application of therailways stationary Li-ion battery on stop behalf of battery energy storage system (BESS) in the mass energytransit from system. the trainThe braking is likely torailways regenerate back to the DC electrified network. This energy couldthe potentially support the rapid DC electrified have often-frequent stop during their journey that mean regenerative braking Abstract auxiliary loads onboard and isthe adjacent trains simultaneously; however, network. the electrical brakingcould resistance onboard would energy from the train braking likely to regenerate back to the DC electrified This energy potentially support the dissipate some the surplus The surplus could be however, absolutely the recovered andbraking stored inresistance the stationary BESS and auxiliary loads ofonboard and energy. the adjacent trains energy simultaneously; electrical onboard would District heating networks are commonly addressed in the literature as one of the most effective solutions for decreasing the then this some potential efficiently supplied to support own train’s for acceleration adjacent dissipate of theenergy surplusisenergy. The surplus energy could bethat absolutely recovered and stored in or theother stationary BESStrains and greenhouse gas emissions from the building sector. These systems require high investments which are returned through the heat simultaneously. The energy modifiedisBangkok Transit System Train Sukhumvit Lineacceleration in Thailandor(from – Bearing then this potential efficiently supplied to (BTS)-Sky support that own train’s for otherMochit adjacent trains sales. Due to the changed climate conditions and building renovation policies, heat demand in the future could decrease, stations) is employed for the demonstration withSystem the multi-train simulator ThisLine system has the service 21.60simultaneously. The modified Bangkok Transit (BTS)-Sky Train (MTS). Sukhumvit in Thailand (from distance Mochit –ofBearing prolonging the investment return period. km with is 22employed passengerfor stations and 8 traction substations. The electrified operation system is 750-V rectifier substations to stations) the demonstration with the multi-train simulator (MTS). This system has theDC service distance of 21.60The main scope of this paper is to assess the feasibility of using the heat demand – outdoor temperature function for heat demand supply power through 3rd rail. substations. Results show thatelectrified the energy saving of the BTS systemDC with the stationary BESS km withthe22electric passenger stations andthe 8 traction The operation system is 750-V rectifier substations to forecast. The district of Alvalade, located in Lisbon (Portugal), was used as a case study. The district is consisted of 665 and with braking energy achieved by 13 show timesthat of the BESS andBTS without regenerative energy. supply theregenerative electric power through the is3rd rail. Results thesystem energywith saving of the system with the braking stationary BESS buildings that vary in both construction period and typology. Three weather scenarios (low, medium, high) and three district © Authors. Published by Elsevier Ltd. by 13 times of the system with BESS and without regenerative braking energy. and2017 withThe regenerative braking energy is achieved renovation scenariosPublished were developed (shallow, intermediate, deep). To estimate the error, obtained heat demand values were © 2017 The Ltd. Peer-review under responsibility of Elsevier the Organizing © 2017 The Authors. Authors. Published by by Elsevier Ltd. Committee of 2017 AEDCEE. Peer-review under responsibility of the scientific committee the 2017 developed International onthe Alternative compared with results from a dynamic heat demand model,of previously andConference validated by authors. Energy in Peer-review under responsibility of the Organizing Committee of 2017 AEDCEE. DThe eveloping Countries andwhen Emerging Economies. results showed that only weather change is considered, the margin of error could be acceptable for some applications Keywords: Battery energy storage system; Li-ion battery; regenerative braking energy; mass rapid transit; energy saving (the error in annual demand was lower than 20% for all weather scenarios considered). However, after introducing renovation Keywords: Battery energy storage system; Li-ion battery; regenerative braking energy; mass rapid transit; energy saving scenarios, the error value increased up to 59.5% (depending on the weather and renovation scenarios combination considered). value of slope coefficient increased on average within the range of 3.8% up to 8% per decade, that corresponds to the 1.The Introduction in the number of heating hours of 22-139h during the heating season (depending on the combination of weather and 1.decrease Introduction renovation scenarios considered). On the other hand,both function intercept for 7.8-12.7% per DC decade (depending on the The transportation by the electrified railways AC high speedincreased and intercity trains) and (mass rapid transit, coupled scenarios). The values suggested could be used to modify the function parameters for the scenarios considered, and Theand transportation by the electrified railways speed and intercityintrains) DC (massquality rapid transit, metro light rail vehicles) systems are one ofboth the AC besthigh ground transportation terms and of quantity, safety, improve the accuracy of heat demand estimations.
metro and light rail vehicles) systems are one of the best ground transportation in terms of quantity, quality safety, © 2017 The Authors. Published by Elsevier Ltd. Peer-review under responsibility of the Scientific Committee of The 15th International Symposium on District Heating and * Corresponding author. Tel.: +66- 88-583-7207; fax: +66-44-224601. Cooling.
E-mail address:author. [email protected] * Corresponding Tel.: +66- 88-583-7207; fax: +66-44-224601. E-mail address: [email protected] Keywords: Heat demand; Forecast; Climate change 1876-6102 © 2017 The Authors. Published by Elsevier Ltd. Peer-review of the Organizing Committee of 2017 AEDCEE. 1876-6102 ©under 2017responsibility The Authors. Published by Elsevier Ltd. Peer-review under responsibility of the Organizing Committee of 2017 AEDCEE.
1876-6102 © 2017 The Authors. Published by Elsevier Ltd. Peer-review under responsibility of the Scientific Committee of The 15th International Symposium on District Heating and Cooling. 1876-6102 © 2017 The Authors. Published by Elsevier Ltd. Peer-review under responsibility of the scientific committee of the 2017 International Conference on Alternative Energy in Developing Countries and Emerging Economies. 10.1016/j.egypro.2017.10.065
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energy saving, less time, environmental friendly for both goods and passenger services. Even the electrified railways is less consume energy than other fuel engines in comparison with the same capacity of the load, they still need to do the research and development to enhance the performance the train services. Considering the DC electrified railway systems as the mass rapid transit, there are many researches to improve the efficiency of the DC power network by reusing the energy from the train braking [1]. This braking energy regenerates from the traction motor that acts like the generator during the train braking. Usually, the regenerative braking energy is used to support the auxiliary load onboard and the adjacent train travelling at the same time. In general, the traction substation of the DC electrified mainly consists of the rectifier transformer that is non-bidirectional in power, therefore, the surplus energy from the regenerative braking energy has to dissipate by the electric resistance onboard. At present, there are many studies on the applications of energy storage devices such as batteries, flywheel, electrochemical double-layer capacitor (EDLC) and hybrid energy storage to store the regenerative braking energy [2]. Those energy storages are one of the solutions for using in the mass rapid transit due to the frequent stops and short track. There are two types of the energy storage installations in the DC electrified railways; (1) onboard application is a temporary accumulation the regenerative braking energy and then regenerated the stored energy to support the own train motoring [3-6], and (2) wayside or stationary application is also a temporary accumulation the regenerative braking energy and then regenerated the stored energy to support the adjacent trains motoring [7-9]. Considering the applications of batteries as a Lithium-ion (Li-ion) battery in the DC electrified railways, Li-ion battery is a new energy storage comparing with the conventional batteries. The characteristic of Li-ion battery is high energy density, high efficiency, long-lift time, light-weight and fast in charge and discharge ability [10]. Li-ion battery is the most favorite battery technology for the portable electric devices, especially in automotive market and electrified railway applications. An energy saving and voltage compensation in the DC electrified railway system are achieved by the application of the stationary Li-ion battery [11]. In addition, the catenary-free operation is also capable by the energy support of the onboard Li-ion battery [12]. In this paper, the stationary BESS based on the Li-ion battery is implemented in the mass rapid transit in the BTSSky Train, Sukhumvit Line, Bangkok, Thailand. The train movement model, BESS model, simulation results and conclusion, consecutively conducts the paper. 2. Train movement model The characteristic of the electrified railways movement is obtained from a standard operation curve as shown in Fig. 1., including train motoring mode, cruising mode, coasting mode and braking mode. The speed of the train is limited at the maximum speed and constant at this speed during the cruising mode. The Newton’s second laws of motion is applied for calculating the characteristic of the train movement taken into account, for example, the gradients, friction force, speed limitation, and train operation modes [13]. The absolute force F applies to accelerate the train expressed in (1), where Meff is the effective mass of the train and α is acceleration rated of the train. With the train motion simulation, an appropriated step time is considered with the various train operation modes during the travelling between two adjacent platforms. However, the train operation modes are based on the consecutive modes in Fig. 1, and controlled by the train speed control strategy, for example, P-controller and hysteresis control [14]. F = FT – FR – FG = Meff α FG = Meff g sin θ FR = A + B·v + C·v2 Meff = Mt(1 + λw) + Ml = Mt(1 + λeff)
(1)
where FT is the tractive effort (N); FR is the train resistance force including friction force (kN); FG is the gradient force (N); v is the train speed (km/h); Mt is the tare mass of the train (kg); Ml is the passenger and freight load (kg); λw is the rotary allowance; λeff is the effective mass factor; A (kN), B (kNh/km), and C (kNh2/km2) are the Davis’s coefficients; g is the gravity of earth, 9.81 m/s2.
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Vm
Motoring mode
Cruising mode
F TEmax
Vm is maximum speed
Speed (km/h)
Constant speed at maximum speed
Tractive effort Tractive effort
Coasting mode
Braking mode
F
TEmax vc1 v F
vc1 Constant force
vc2 Constant power
TEmax vc1vc 2 v2
Speed Reduced power
Distance (km)
Fig. 1. Train’s operation modes
Fig. 2. Characteristic of tractive effort and train speed
From (1), the net force related to the Newton’s second law of motion is the summation of the tractive effort, the friction force and the gradient force. The tractive effort is constant at the rated value during the train motoring and reduces slightly depending on the train operational modes and train speed as shown in Fig. 2, where TE is the tractive effort, vc1 and vc2 are the based speed of the cruising and coasting modes, respectively. The gradient force depends on the gradient slope and angle . The friction force and drag force (including aerodynamic and rolling resistance) takes into account the Davis’s equation as the quadratic function of the train speed [15]. The acting forces can also explain an expression of the train movement calculation on the traction vehicle with the uphill direction as shown in Fig. 3.
M eff
Fig. 3. Train’s movement on a gradient
Fig. 4. B-chop system [16]
3. Battery energy storage system The description of the Battery energy storage system (BESS) and the stationary BESS model in the DC electrified railways system are presented as follows: 3.1 Characteristic of the BESS The BESS implemented for the simulation in this paper is based on the B-chop system, which is the energy storage for traction power supply system, Hitachi, Japan. The Lithium-ion (Li-on) battery is applied in the B-chop system as shown in Fig. 4 [16]. BESS is connected to the traction substation (TSS) through the DC-DC converter. In practical, BESS is recharged energy from the regenerative braking energy during the braking mode of the train operation and then discharged energy back to the DC system to support TSS supplying the motoring mode of the train operation. The reuse of the surplus energy as a regenerative braking energy also achieves the energy saving of the DC power supply or TSS and improves the stopping point accuracy. In addition, the voltage stability of the DC electrified railway system prevents the voltage rise and drop by the BESS. With the mechanical maintenance, the maintenance cost of the mechanical break pad of the vehicle is reduced due to the supporting of the electrical break.
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3.2 DC rolling stock model with BESS A TSS of the DC electrified railways or mass rapid transit systems are illustrated as in Fig. 5. In general, at TSS1 and TSS2 consist of the rectifier transformer to convert the AC electrified to DC electrified systems. In this paper, the TSS of the DC electrified railways system is also the DC power supply for the mass rapid transit system. The train consumes the DC power from the conductor rail via collector shoe. The stationary battery energy storage system (BESS) is modeled by the DC power source at TSS2 as shown in Fig. 5. The BESS current discharges to DC busbar supporting the train motion denoted by IBESS. TSS. 1
1
Conductor rail 3
d Rcond
p
C
IS
RS
Ltss d Rcond
R
TSS. 2 BESS
IBESS
IS
RS
Ltss d Rrail
d Rrail
1 1 GRE GRE 2 2
RSE
q
Train
I tr
2
4
1 1 GRE GRE 2 2
RSE
Running rail
Fig. 5. Traction substations with a stationary BESS
Fig. 6. Equivalent circuit of the DC electrified railway system with BESS
In this paper, the DC power network solver with a computer-based simulation of the train movement requires the train position on the track and the electrical power consumption of the train obtained from the previous section. The train position is significantly conducted to form a system of conductance matrix at each step of the train motion. The total electrical power consumption of the trains is considered as the load bus of the DC power network and applied to provide the total power demand of the DC power supply. To obtain the voltage solutions of each TSS, the nodal analysis is implemented to find the solutions [17]. A simplified model of the TSS with a stationary BESS shown in Fig. 5, has presented by the equivalent circuit as shown in Fig. 6. It includes four main sections, including TSS, transmission line, train and BESS. In Fig. 7, d is the train position, Ltss is the track length between TSSs, Is is the TSS current, It is the train current, Rs is the internal TSS resistance, Rcond and Rrail are the conductor rail and running rail resistances, RSE and GRE are the TSS ground resistance and the rail-to-earth conductance, and IBESS is the BESS current. Applying the power calculation based on the nodal analysis provides the solutions of TSS voltages, train voltages, TSS power consumptions, rail potential and power loss in the DC electrified railway system. A current injection model (CIM) [18] is implemented for the TSS currents, train currents and BESS current with multi-conductor system. All solutions such as TSS voltages, train voltage, energy consumptions and so on, obtain by the MTS, see [18]. 4. Results and discussions
Fig. 7. BTS Sukhumvit Line
E14: Bearing
E13: Bang Na
E12: Udom Suk
E11: Punnawithi
E10: Bang Chak
E9: On Nut
E8: Phra Khanong
E7: Ekkamai
E6: Thong Lo
E5: Phrom Phong
E4: Asok
E3: Nana
E2: Phloen Chit
E1: Chit Lom
CS: Siam
N1: Ratchathewi
N2: Phraya Thai
N3: Victory Monument
N4: Sanam Pao
N5: Ari
N6: Sena Ruam
N7: Saphan Khwai
N8: Mo Chit
The rating and specification of the BESS for the DC electrification of 750 V traction power is that the rated voltage is 820 V, rated capacity is 500 kW and rated current is 600 A. In this paper, the power loss during BESS charge and discharge energy is neglected in the simulation. The track work of the simulation is the modified Bangkok Transit System (BTS)-Sky Train Sukhumvit Line in Thailand (from Mochit – Bearing stations) as shown in Fig. 7. The BTS Sukhumvit Line has 22 platforms and 8 TSS. The train headway is 5 minutes, the service distance is 21.6 km, the maximum speed of the trains is 80 km/h and the traction acceleration rate is 1.0 m/s2. The time step of the simulation is 0.5 sec with the total time of the simulation is 1.0 hour. The results of the simulation for evaluation the application BESS are presented as follows:
Tosaphol Ratniyomchai et al. / Energy Procedia 138 (2017) 93–98 Tosaphol Ratniyomchai, Thanatchai Kulworawanichpong / Energy Procedia 00 (2017) 000–000
Fig. 8. Train speed profile, power and voltage
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Fig. 9. The energy profiles of the BESS installed at RS2
The train speed profile, delivery power and terminal voltage of the train 1 obtained from the MTS are shown in Fig. 8. The speed is limited at the maximum speed of 80 km/h. The time of a train runs from the start to the end of the track is about 1860 sec. The positive train power means the power for train motoring whereas the negative train power means the power from the train braking. The nominal train voltage is about 830 Vdc, and it drops during the train motoring. The TSS RS2, RS3 and RS5 have been consecutively chosen to install the BESS that the energy profiles of the BESS at each TSS are shown in Fig. 9 and Fig. 10.
a
b Fig. 10. The energy profiles of the BESS installed at (a) RS3 (b) RS5
In Fig. 9 and Fig. 10, the maximum energy of the BESS is at 0.19 MWh, which is at 100% full charge of the BESS. In comparison Fig. 9. and Fig. 10, it is clear that the capacity of the BESS at RS2 about 0.03 MWh drops less than those of 0.032 MWh and 0.06 MWh at RS3 and RS5, respectively. Therefore, the TSS at RS2 is suitable for installing the BESS due to it obtains the small capacity. The BESS is fixed at the RS2 to find the optimal capacity as the results presented in Table 1. Table 1. Energy consumption, Energy losses and service voltage range with different BESS modules
In
BESS module
MWh consumed
MWh losses
Max RS2 voltage (V)
Min RS2 voltage (V)
1x500 kWp
4.4684
0.4489
881.17
668.98
5x500 kWp
4.3923
0.4489
881.17
668.98
10x500 kWp
4.2971
0.4489
881.17
668.98
20x500 kWp
4.1068
0.4489
881.17
668.98
BC1: NoRG
4.7240
0.4473
800.00
643.31
BC2: RG
4.4874
0.4489
881.17
668.98
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Table. 1, the BESS modules consist of 1, 5, 10 and 20 time of the peak power of 500 kW. The based case without BESS consists of the DC electrified railways system with no regenerative braking energy (BC1) and with regenerative braking energy (BC2). The energy losses, and the minimum and the maximum voltage of RS2 are almost the same with all BESS modules. However, the energy consumed by the TSS is reduced by all BESS modules comparison with the base case BC1 and BC2. Considering the BESS module of 1x500 kWp, it is the optimal capacity of the BESS to install at TSS RS2 because it can save energy 0.019 MWh comparison with BC1 and 0.2556 MWh comparison with BC2. Other BESS modules can also save more energy than the first module but their capacity is more than the first module with related to the capital cost. With the additional assumption, the daily service hour of the BTS Sukhumvit Line for one day is 16 hours from 6 am to 10 pm, and the electrical tariff is 3.0 THB/kWh. Therefore, the first BESS module of 500 kWp installed at RS2 can save energy 110.96 MWh/year or 332,880 THB/year comparing with BC1 and 1492.1 MWh/year or 4,478,112 THB/year comparing with BC2. 5. Conclusion This paper presents the application of the stationary BESS based on the Li-ion battery in the mass rapid transit of the BTS-Sky Train Sukhumvit Line, Bangkok, Thailand. The BTS system has 22 platforms, which is suitable to apply the regenerative braking energy with the stationary BESS because it is highly frequent of the train stop. This is confirmed by the results of the simulation that the stationary BESS is chosen to install at the TSS R2. The results present that the energy saving of the BTS system with the stationary BESS is achieved with the system with applied the regenerative braking energy by 0.2566 MWh which is 13 time of the BTS system without applied regenerative braking energy. References [ 1] Gonzalez-Gil A, Palacin R, Batty P. 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