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2020

Recuperation of Regenerative Braking Energy in Electric Rail Transit Systems

Mahdiyeh Khodaparastan CUNY City College

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Recuperation of Regenerative Braking Energy in Electric Rail Transit Systems

Mahdiyeh Khodaparastan Advisor: Professor Ahmed Mohamed

A dissertation submitted to the Graduate Faculty in Electrical Engineering in partial fulfillment of the requirements for the degree of Doctor of Philosophy

The City College of New York 2020

Table of Content 1 INTRODUCTION ...... 6 1.1. THE RESEARCH QUESTION ...... 7 1.2. METHODOLOGY ...... 7 2 LITERATURE REVIEW ...... 8 2.1 SYSTEM INTEGRATION ...... 8 2.2 TRAIN TIMETABLE OPTIMIZATION ...... 9 2.3 STORAGE BASED SOLUTIONS ...... 11 Energy Storage Technologies ...... 12 Onboard Energy Storage ...... 13 Wayside Energy Storage ...... 14 Reversible Substation ...... 15 Choosing The Right Application ...... 18 3 ELECTRIC RAIL TRANSIT SYSTEM MODELING ...... 20 3.1 POWER SUPPLY SUBSTATION MODELING ...... 20 3.2 TRAIN MODELING ...... 21 3.3 ELECTRIC VEHICLE MODELING ...... 23 3.4 ENERGY STORAGE MODELING ...... 24 Batteries ...... 24 Supercapacitors ...... 25 Flywheels ...... 26 3.5 REVERSIBLE SUBSTATION MODELING ...... 27 3.6 HYBRID REVERSIBLE SUBSTATION AND WAYSIDE ENERGY STORAGE MODELING ...... 30 3.7 DISTRIBUTION GRID MODELING ...... 33 Con Edison Service Territory Overview ...... 33 3.8 VALIDATION RESULTS ...... 37 3.9 ONE-CYCLE OPERATION ...... 37 3.10 24 HOURS OPERATION ...... 38 4 CASE STUDIES ...... 40 4.1 WAYSIDE ENERGY STORAGE ...... 40 Substation Peak Demand Reduction ...... 40 Maximum Recuperation of regenerative braking energy ...... 42 In this section, a similar case study, which was presented in the previous section for a battery, is performed here for flywheel and supercapacitor as well. The results for each technology are presented in Table 4-5 and 4-6 respectively for supercapacitor and flywheel...... 46 4.2 REVERSIBLE SUBSTATION ...... 46 4.3 HYBRID REVERSIBLE SUBSTATION AND WAYSIDE ENERGY STORAGE ...... 50 4.4 IMPACT ON DISTRIBUTION GRID ...... 54 5 ECONOMIC ANALYSIS ...... 58 5.1 WAYSIDE ENERGY STORAGE INSTALLATION COST ...... 58 Peak demand reduction ...... 58 Recuperation of regenerative braking energy ...... 61 5.2 REVERSIBLE SUBSTATION INSTALLATION COST ...... 61 5.3 ANNUAL MONETARY SAVING ...... 62 6 CONCLUSION ...... 66 APPENDIX A ...... 67 APPENDIX B ...... 68 REFERENCES ...... 69 Table of Figures

Fig. 2-1 A schematic diagram of a typical power supply substation ...... 8 Fig. 2-2 Onboard energy storage systems...... 13 Fig. 2-3 Wayside energy storage systems...... 14 Fig. 2-4 Block diagram of a reversible substation...... 15 Fig. 2-5 Block diagram for HESOP reversible substation...... 17 Fig. 2-6 Block diagram for diode rectifier/PWM converter reversible substation...... 17 Fig. 3-1 Substation schematic...... 20 Fig. 3-2 Schematic of the train running between two passenger stations...... 21 Fig. 3-3 Schematic of the variable resistance modeling ...... 21 Fig. 3-4 Vehicle modeling process...... 22 Fig. 3-5 Vehicle modeling process...... 23 Fig. 3-6 Block diagram of the braking ...... 24 Fig. 3-7 Battery Model Fig. 3-8. Bidirectional DC/DC converter ...... 25 Fig. 3-9 Flywheel model ...... 26 Fig. 3-10 Discharging current and of supercapacitor ...... 26 Fig. 3-11 Supercapacitor model ...... 26 Fig. 3-12. Schematic of a reversible substation and its controller ...... 29 Fig. 3-13. Schematic of a reversible substation and its controller ...... 31 Fig. 3-14 Flowchart of energy management unit ...... 32 Fig. 3-15 schematic of the ESS charge and discharge controller ...... 32 Fig. 3-16 Schematic of the ESS charge and discharge controller ...... 33 Fig. 3-17 Con Edison Network Territory...... 33 Fig. 3-18 schematic view of radial and network grid ...... 34 Fig. 3-19 Subway substations under study in this report...... 35 Fig. 3-20 Model conversion from PVL to OpenDSS...... 35 Fig. 3-21 Normalized load curve of the Borden network...... 35 Fig. 3-22 Subway substation power profile for a sample day on March...... 36 Fig. 3-23 Subway substation power profile for a sample day on November...... 36 Fig. 3-24. NYCT map of the system under study ...... 37 Fig. 3-25 Schematic of electric rail transit systems ...... 37 Fig. 3-26 Validation results for one-cycle operation...... 38 Fig. 3-27 24 hours power profile of the substation1 (a) and the substation 2 (b) in system under study ...... 39 Fig. 4-1 Impact of ESS on substation power ...... 40 Fig. 4-2 The 24 hours power profile of the substation2 with different size of energy ...... 40 Fig. 4-3 Schematic of NYCT line 7 ...... 42 Fig. 4-4 Schematic of NYCT line 7 from Hunter passenger station to 40 St...... 42 Fig. 4-5 The power profile of train and 3 substation in Line 7...... 43 Fig. 4-6 Train terminal voltage when ESS located at Hunter point Ave passenger station ...... 44 Fig. 4-7 Train terminal voltage when ESS located at Court Sq. passenger station ...... 44 Fig. 4-8 Train terminal voltage when ESS located at Queensboro passenger station ...... 44 Fig. 4-9. Case 1 train current profile ...... 45 Fig. 4-10. Case 1 train current profile ...... 47 Fig. 4-11 AC active and reactive 3ph power of the inverter...... 47 Fig. 4-12 Case 1 AC voltage and current...... 48 Fig. 4-13 third rail voltage at dc side of Inverter ...... 48 Fig. 4-14 phase current and voltage (showing unity power factor operation)...... 49 Fig. 4-15 direct and quadratic axis per-unit currents...... 49 Fig. 4-16 train versus inverter input power...... 49 Fig. 4-17 3ph active and reactive power...... 50 Fig. 4-18 3ph voltage and current...... 50 Fig. 4-19 Third rail voltage...... 51 Fig. 4-20 Per-unit d-axis and q-axis currents...... 51 Fig. 4-21 3ph active and reactive power...... 52 Fig. 4-22 3ph voltage and current...... 52 Fig. 4-23Third rail voltage...... 53 Fig. 4-24 Per-unit d-axis and q-axis currents...... 53 Fig. 4-25 ...... 54 Fig. 4-26Subway substations under study in this report...... 55 Fig. 4-27 Line loading of the primary feeders in the base scenario...... 56 Fig. 4-28 Primary buses ...... 56 Fig. 4-29 Secondary buses voltages...... 56 Fig. 4-30 Line loading of the primary feeders with WESS at 50 AVE and Jackson, and substations power is zero during 1pm-7pm...... 56 Fig. 4-31 Line loading of the primary feeders with zero substations power all day...... 57 Fig. 5-1 the Interval metering data for 20 days...... 62 Fig. 5-2 Interval metering data for a sample summer day ...... 62 Fig. 5-3 Probability of trains direct energy exchange ...... 63 Fig. 5-4 Jackson substation interval data with and without natural exchange of regenerative braking energy...... 63 Fig. 5-5 Interval data with and without wayside energy storage...... 64 Fig. 5-6 Energy savings with and without direct exchange and ESS at Jackson Substation ...... 64 Fig. 5-7 NYC Locational based Marginal Price for 2017 and 2018...... 64 Fig. 5-8 Energy saving at each subway substation ...... 64

Abstract

Electric rail transit systems are large consumers of energy. In trains with regenerative braking capability, a fraction of the energy used to power a train is regenerated during braking. This regenerated energy, if not properly captured, is typically dumped in the form of heat to avoid overvoltage. Finding a way to recuperate regenerative braking energy can result in substantial economic as well as technical benefits. Regenerative braking energy can be effectively recuperated using wayside energy storage, reversible substations, or hybrid storage/reversible substation systems. In this research study, we compare these recuperation techniques and investigate their application in New York City Transit (NYCT) systems, where most of the regenerative braking energy is currently being wasted.

We have developed a detailed transient model to determine the applicability, feasibility, and pros and cons of deploying wayside energy storage, such as batteries, super capacitors or flywheels. This model has been validated using real measurement data on the 7-Line (Flushing), including:1) speed, current, voltage, power and energy train profiles; and 2) 24-hour interval metering data at substations. The validated model has been used to analyze and compare various ESS technologies, including Li-ion Battery, Supercapacitor and Flywheel. In addition, we have developed detailed transient models for reversible substations. A reversible substation, also known as bidirectional or inverting substation, provides a path through an inverter for regenerative braking energy to feedback to the upstream AC grid. This energy can be consumed by AC equipment within passenger stations (e.g., escalators) or fed back to the main grid based on legislations of the electric distribution utility. This study will provide crucial technical as well as financial guidelines for various stakeholders while making investment decisions pertaining to regenerative braking energy.

1 INTRODUCTION Electric rail transit systems are large consumer of electricity. For instance, New York City Transit consumes 1700 GWh annually. Even though electric transportation systems already provide relatively low energy consumption per passenger, there is potential for significant energy efficiency enhancement, as well as peak power and carbon footprint reductions. In general, electric train operation can be divided into four modes: acceleration, cruising, coasting and braking [1]. During the acceleration mode, a train accelerates and draws energy from a catenary or a third rail (i.e. a power supply rail, located next to the traction rails). In the cruising mode, the power of the motor is almost constant. In the coasting mode, the speed of the train is nearly constant, and it draws a negligible amount of power. In the braking mode, the train decelerates until it stops. In light rail traction systems and in urban areas, since the distance between the passenger stations is short, the cruising mode can be omitted. There are several types of train braking systems, including regenerative braking, resistance braking and air braking. In regenerative braking, which is common in today’s electric rail systems, a train decelerates by reversing the operation of its motors. During braking, the motors of a train act as generators converting mechanical energy to electrical energy. In this paper, the produced electrical energy will be referred to as “regenerative braking energy” or “regenerative energy.” This energy is used to supply train’s onboard auxiliary loads, while the surplus energy is fed back to the third rail. In dense cities, the distance between passenger stations is typically short and train acceleration/braking cycles repeat frequently, which results in considerable amounts of regenerative energy [1]. Regenerative braking energy that is fed back to the third rail by a braking train can be utilized by neighboring trains that might be accelerating within the same power supply section as the braking one. However, this involves a high level of uncertainty since there is no guarantee that a train will be accelerating at the same time and location when/where regenerative energy is available. The amount of energy that can be reused by the neighboring trains depends on several factors, such as train headway and age of the system. If there are no nearby trains to use this regenerated energy, which is typically the case, the voltage of the third rail tends to increase. There is an over-voltage limit to protect equipment in the rail transit system. To adhere to this limit, a braking train may not be able to inject its regenerative energy to the third rail. The excess energy must be dissipated in the form of heat in onboard or wayside dumping resistors. This wasted heat warms up the tunnel and substation, and must be managed through a ventilation system [2]. Several solutions have been proposed in the literature to maximize the reuse of regenerative braking energy: (1) train timetable optimization, in which synchronization of multiple trains operation has been investigated. By synchronizing trains operation, when a train is braking and feeding regenerative energy back to the third rail, another train is simultaneously accelerating and absorbing this energy from the third rail; (2) energy storage systems (ESS), in which regenerative braking energy is stored in an electric storage medium, such as super capacitor, battery and flywheel, and released to the third rail when demanded. The storage medium can be placed on board the vehicle or beside the third rail, i.e. wayside; (3) reversible substation, in which a path is provided for regenerative energy to flow in reverse direction and feed power back to the main AC grid; (4) hybrid reversible substation and wayside energy storage system that combine the reversible substation and wayside energy storage technique. In this approach ESS is shared between transit system and utility company. 1.1. The Research Question The key research question of this work is, in a given location of a transit system, which of the following techniques is most suitable? • Wayside energy storage • Reversible substation • Hybrid reversible substation and wayside ESS

The study also addresses other questions, including: 1. How much energy savings and peak demand reduction result from existing regenerative energy configuration? What are the cost savings? 2. How much energy savings and peak demand reduction can be achieved with each technique? 3. What are the general design considerations for each recuperation technique including system size and optimal placement?

1.2. Methodology 1. To develop detailed models for the NYCT system, and related Con-Edison distribution networks. 2. To validate the developed models versus real measurements. 3. To use the validated models for analyzing wayside energy storage, reversible substation and hybrid reversible substation deployment.

2 LITERATURE REVIEW Several solutions have been proposed in the literature to maximize the reuse of regenerative braking energy: (1) train timetable optimization, in which synchronization of multiple trains operation has been investigated. By synchronizing trains operation, when a train is braking and feeding regenerative energy back to the third rail, another train is simultaneously accelerating and absorbing this energy from the third rail; (2) energy storage systems (ESS), in which regenerative braking energy is stored in an electric storage medium, such as super capacitor, battery and flywheel, and released to the third rail when demanded. The storage medium can be placed on board the vehicle or beside the third rail, i.e. wayside; (3) reversible substation, in which a path is provided for regenerative energy to flow in reverse direction and feed power back to the main AC grid [4]. The goal of this chapter is to provide a comprehensive review on the research efforts, studies and implementations that have been presented by both the academia and the industry on maximizing reuse of regenerative braking energy. Various solutions and technologies have been described and discussed. Advantages and disadvantages of each solution have been presented. 2.1 System Integration Electric rail transit systems consist of a network of rails, supplied by geographically distributed power supply substations. A typical DC transit substation consists of a voltage transformation stage that steps down medium voltage to a lower voltage level, followed by an AC/DC rectification stage that provides DC power to the third rail. There are also traction network protection devices (circuit breaker, insulator, etc.) both at the AC and DC sides to prevent personnel injuries and equipment damage. Transformers have overcurrent, Bochholtz and temperature protection and supply cables have differential feeder protection. On the DC side, rectifiers have overcurrent, reverse current trip protection and high-speed breaker. There are impedance relays along the track or on the vehicle to protect earth faults. Figure 2-1 shows an example of a substation in which two transformers and two rectifiers are connected in parallel, to increase the power supply reliability. Auxiliary loads, such as elevators, escalator, ventilation systems and lighting systems are supplied through a separate transformer (referred to as “AUX TRANS” in Figure 1). A typical sub- station rating is 3 MW at 750 V DC supplying 4 kA with overload capabilities of 150, 300 and 4500 of the rated current for 1 hour, 1 minute and 10 s, respectively [5]. There are three common voltage levels for the third rail in DC transit systems: 600V, 750V and 1500V [6]. The operating third rail voltage is maintained between safety under/over voltage limits, e.g. ∼500 and ∼900 for a 750V system [7]. AUX TRANS

To Auxiliary Load

∆/∆ AC +

DC

Three-phase main grid AC

DC - Y/∆ Fig. 2-1 A schematic diagram of a typical power supply substation Based on IEEE Standard 1159-2009, voltage events in electric rail system can be classified as: 1) normal voltage that is considered 10% above and below the nominal value; 2) transient overvoltage that is voltage above 10% of the nominal value but for a very short time i.e. 0.5 cycles to 30 cycles; 3) interruption, which is voltage below 10% of nominal value (momentary: 0.5 cycle to 3 seconds, temporary: 3 seconds to 1 minute and sustained: over 1 minute); 4) voltage swell which is a voltage deviation above 110% of nominal (momentary: 30 cycle to 3 seconds, temporary: 3 seconds to 1 minute); 5) voltage sag, which is voltage deviation between 10% and 90% of the nominal voltage (momentary: 30 cycle to 3 seconds, temporary: 3 seconds to 1 minute); and 6) over/under voltage, which is voltage deviation above/ below 10%-20% of the nominal voltage lasting more than 1 minute. In some dense stations, an ESS may be used for voltage regulation [8]. The railway line circuit consists of traction rails and a power rail; in order to have better operation, protection and maintenance, they are divided into sections. Each section can be supplied by only one substation at one side or two substations at both ends. The first case is suitable for systems with short distance and few vehicles while the second case is suitable for systems with longer distances and many vehicles [9]. Trains move on traction rails while receiving their power from either a third rail or an overhead line. In addition to providing the friction force needed by the wheels to propel train vehicles, traction rails can also provide a return path for power. When a train moves on traction rails, the resistances between the train and its departure and arrival passenger stations change based on the distance [10]. In urban areas, the average distance between passenger stations is short (e.g. 1-2 mile). Therefore, trains accelerate rapidly to their maximum speed (e.g. 80-100 km/h), and decelerate shortly afterwards to prepare for their next stop. The typical average acceleration and deceleration rates are 1.1 m/s2 and −1.3 m/s2, respectively. The electric vehicle is the main load of electric transit systems. The main electric part of a vehicle is its electric drive, which controls the torque and the speed of the vehicle. Electric drives mostly consist of converters and electric machines linked by appropriate control circuits. Specifically, there are DC-C and DC-AC converters, DC motor and three- phase . In DC traction system, DC motors are controlled by a bank of resistors and a DC-DC converter. Three phase induction motors are controlled through DC-AC converters. DC-AC converters can be either voltage source inverter (VSI) or current source inverter (CSI). VSI does not need a fixed voltage and can handle +20% and −50% variation of traction line voltage. CSI needs a chopper converter to maintain DC link current constant [11], [12]. Some of the important factors that need to be considered in the selection of drives are as follows: line voltage regulation, quality of the power absorbed by the trains, electromagnetic interference introduced by the drive to the power line, preventing resonance that may be caused by the interaction between the drive and line components [11]. 2.2 TRAIN TIMETABLE OPTIMIZATION Train timetable optimization has been proposed as one of the approaches to maximize the reuse of regenerative braking energy. In this method, the braking and acceleration actions of two neighboring trains are scheduled to occur simultaneously; therefore, some of the energy produced by the decelerating train is used by an accelerating one. Some studies show that up to 14% of energy saving can be achieved through timetable optimization [13]–[15]. Studies that have been performed on train timetable optimization can be classified, according to their objectives, into two main categories: minimizing peak power demand, and maximizing the utilization of regenerative braking energy [16]. In the early stages of research on timetable optimization (i.e. early 1960s), the emphasis was on peak power demand reduction. Most of this research proposed methods to shift the acceleration time of some trains to off-peak time (note that time synchronization between trains was not targeted) [17], [18]. For instance, in [17], to limit the number of trains accelerating at the same time, train scheduling tables have been optimized using genetic algorithm. In [19], a control algorithm for coordinating movement of multiple trains has been proposed to reduce peak power demand. In [14], the peak power has been reduced through controlling train running time using dynamic programing. More recently, research aimed at using train timetable optimization to maximize the utilization of regenerative braking energy, by synchronizing the acceleration/deceleration intervals of neighboring trains. Most of this research aimed at optimizing the dwell time (i.e. stop time at each station) of the trains to increase the chance of synchronizing accelerating and decelerating trains [13], [15], [20]–[22]. Some other research focused on determining the optimal time overlap between multiple trains [23]–[25]. The optimization problem may be formulated to maximize utilization of regenerative braking energy, by finding the optimal departure and arrival times of trains. As an example, if a set of arrival times is considered as a = {ani,1 ≤ i ≤ I,1 ≤ n ≤ N}, where an i denotes the time that train i arrives at station n, I and N are the number of trains and stations, respectively; and departure times are defined as d={dni,1≤i≤I,1≤n≤N}, where dni denotes the time that train i departs station n. The objective function of timetable optimization aimed to maximize utilization of regenerative braking energy can be formulated as follows: T Ns ì I I ü F(a,d) = ååminíåwi (a,d,t)l(i,t, s)´å fi (a,d,t)l(i,t,s)ý t=1 s=1 î i=1 i=1 þ where T is the total operation time, Ns is the number of electricity supply substations, ωi (a, d, t) is the energy produced by train i during the time unit [t, t + 1], fi (a, d, t), is the required energy for accelerating train i during time unit [t,t + 1], and λ(i,t,s) denotes whether the train i is located in the electricity supply interval s at time t or not [16], [23]. Currently, there is ongoing research on integrated optimization methods, which combine train timetable optimization and speed profile optimization. Speed profile optimization is one of the conventional approaches used to improve the energy efficiency of electric rail transit system. In this approach, the speed profile of a single train is optimized such that it consumes less energy during the trips between stations. Timetable and speed profile optimization problems are tied to each other. Timetable optimization provides the best running time that can be used as an input in speed profile optimization. Simultaneously, speed profile optimization determines the optimal acceleration/deceleration rates, which can be used as an input to timetable optimization. An example of the integrated optimization method is presented in [26]. In this study, the optimal dwell time at each station, and maximum train speed at each section is determined. The results show that 7.31% energy saving can be achieved using this approach. The integrated optimization method provides better energy saving as compared to using timetable optimization or speed profile optimization individually. In [27], an integrated optimization method has been proposed based on actual operation data from Beijing . The results show that the proposed method can reduce energy consumption of the overall system by 21.17% more than the timetable optimization method [28], and 6.35% more than the speed profile Table 2-1 Examples of Train Timetable Optimization Implementations Saving (% of Method Implemented in real system? Comment Ref. consumed energy) Dwell time optimization 14% No, but data are gathered from The impact of both headway and dwell time on [13] with GA algorithm Metro reusing regenerative energy has been studied. Running time reserve 4% No, but data are gathered from The headway is considered to be constant. At each [14] optimization with GA Berlin Metro stop, the amount of reserve time to be spent on the next section of the ride is decided. Dwell time optimization 5.1% No A mathematical model of metro timetable has been [15] by greedy heuristic method defined. Departure time through - No, but data are gathered from a Around 40% of peak energy has been reduced and [20] multi-criteria mixed Korean subway system utilization of regenerative braking energy is integer programing improved by 5%. Departure and dwell time 7% in simulation, Proposed models were used to 85% of braking and accelerating processes are [21] Optimization 3.52% in reality design a timetable for Madrid synchronized. underground system Fuzzy logic control Not presented. No Train operation is specified by a set of indices, and [22] Dwell time the aim of fuzzy control is to find the best performance among these indices. Running time 7% No, but data are gathered from a Two objective functions are considered: energy [133] Optimization by GA substation in the UK consumption and journey time. The best possible compromise between them is searched using GA. Direct climbing 14% No, but data are gathered from a The optimal set of speed profile and timetable [134] optimization substation in Italy variables has been found in order to minimize energy consumption.

Dwell time and run time 6.6% - From energy saving point of view, run-time [97] optimization/Genetic algorithm control is superior over dwell time control. More and dynamic programing model flexible train control can also be achieved with run time control. Substation energy 38.6% No, but the case study was based Substation energy consumption optimized by [135] consumption optimization on Beijing Yizhuang Metro modifying the speed profile and the dwell time

optimization method, for the same system and headways [16], [23]. In [29], other real world factors, such as the constant number of performing trains and cycle time are considered as part of the integrated optimization. For better utilization of regenerative braking energy, all trains supplied from the same electric section are considered in the time table. Another integration optimization method is presented in [30]. The aim of this paper is to optimize substations’ energy consumption through finding optimal train movement mode sequences, inter-station journey times, and service intervals. An overview on some of the studies that is carried out in this area has been presented in Table 2-1. 2.3 STORAGE BASED SOLUTIONS An energy storage system, if properly designed, can capture the energy produced by a braking train and discharge it when needed. Consequently, the amount of energy consumed from the main grid is reduced [20], [21], [31]. In addition, using ESS can reduce the peak power demand, which not only benefits the rail transit system but also the power utility. ESS may be used to provide services to the main grid, such as peak shaving [4]. Since the energy regenerated by a braking train is captured by an ESS, the need for onboard or wayside dumping resistors is minimized. Therefore, heat waste and ventilation system costs are reduced [22]. ESS can be implemented in two different ways: onboard and wayside. In onboard, ESS is mostly located on the roof of each train. On the other hand, wayside ESS is located outside the train, on the trackside. It can absorb the regenerative energy produced by all trains braking within the same section and deliver it later to other trains accelerating nearby. Both wayside and onboard ESS will be described in the following subsections, and examples of their application in transit systems all over the world will be presented. Before that, the common technologies available and used for ESS in the rail transit system will be briefly discussed. Energy Storage Technologies Selection of the most suitable storage technology is a key factor to achieve optimal ESS performance for a given application. Several important factors must be considered while designing an ESS, and choosing the most suitable storage technology. These factors include: the energy capacity and specific energy, rate of charge and discharge, durability and life cycle [7]. The common energy storage technologies that have been utilized in rail transit systems are batteries, supercapacitors and flywheels. 1) Batteries: Battery is the oldest electric energy storage technology, which is widely used in different applications. A battery consists of multiple electrochemical cells, connected in parallel and series to form a unit. Cells consist of two electrodes (i.e. anode and cathode) immersed in an electrolyte solution. Batteries work based on the following principle: due to reversible chemical reactions (i.e. oxidation and reduction) that occur at the electrodes, a potential difference appears between them (voltage between the anode and the cathode). Consequently, energy can reversibly change from the electrical form to the chemical form [32], [33]. There are various types of batteries depending on the material of their electrodes and electrolyte. Among those types, the most commonly used in rail transit systems are: Lead–acid (pbso4), Lithium-ion (Li-ion), Nickel-metal hydride (Ni-MH) and sodium sulfur (Na-s). Other types of batteries like flow battery may have the potential to be used in rail transit systems [34][35]. [34][35] A comparison of the advantages and disadvantages of each type has been summarized in Table 2- 2.

2) Flywheels: Flywheel is an electromechanical ESS that stores and delivers kinetic energy when it is needed. Flywheel is composed of an electrical machine driving a rotating mass, so called , spinning at a high speed. The amount of energy that can be stored or delivered depends on the inertia and speed of the rotating mass. During the charging process, the electrical machine acts as a motor and speeds up the rotor increasing the kinetic energy of the flywheel system. During the discharging process, the rotational speed of the rotor decreases releasing its stored energy through the electrical machine, which acts as a generator. The electrical machine is coupled to a variable frequency power converter. To reduce friction losses, flywheels use magnetic bearing, and to Table 2-2 A Comparison of Different Battery Technologies Type Advantages Disadvantages Comment Reference Pbso4 • Low cost per Wh • Low number of cycle -Recently, extensive research has been carried out [32], [36], • Long history • Low charging current on replacing lead with other materials, such as [80] • Wide deployment • Limited service life carbon, to increase its power and energy density • High reliability • Environmental concern • High power density • Poor performance in low temperature Ni-MH • Long service life • High cost per Wh -The main disadvantage is high self-discharge rate, [32], [80], • High energy • High maintenance might be overcome using novel separators [136], • High charge/discharge current • High self-discharge rate. [137] • High cycle durability • Low Environmental concern Li-ion • High energy density • High cost per Wh - Currently, researchers investigate a combination [32], [80], • Being small and light • Require cell balance and control to of electrochemical and nanostructures that can [138] • Low maintenance avoid overcharge improve the performance of Li-ion batteries • High number of cycle • Required special packing and protection circuit Na-s • High energy density • High cost -Researchers are investigating new ways to reduce [32], [36], • High power density • Environmental concern their high operating temperature. [136], • Highly Energy efficiency • Need cooling unit [137], [139]

reduce air friction losses, the rotor is contained in a vacuum chamber [32], [33], [36], [37], [38]. Some of the advantages of flywheel ESS are high energy efficiency (∼95%), high power density (5000 W/kg) and high energy density (>50 Wh/kg), less maintenance, high cycling capacity (more than 20000 cycles) and low environmental concerns [39]. Flywheel systems present some drawbacks, such as very high self-discharge current, risk of explosion in case of failure, high weight and cost. However, system safety is believed to be improvable through predictive designs, and smart protection schemes. According to some publications, if/when the cost of flywheel systems is lowered; they can be extensively used in all industries and play a significant role in the worldwide energy sustainability plans [33], [36], [40]. Based on the simulation results presented in [41], flywheel ESS is capable of achieving 31% energy saving in light rail transit systems. 3) Super Capacitors: Super capacitor is a type of electrochemical capacitors consisting of two porous electrodes immersed in an electrolyte solution. By applying voltage across the two electrodes, the electrolyte solution is polarized. Consequently, two thin layers of capacitive storage are created near each electrode. There is no chemical reaction, and the energy is stored electrostatically. Because of the porous electrode structure, the overall surface area of the electrode is considerably large. Therefore, the capacitance per unit volume of this type of capacitor is greater than the conventional capacitors [32], [36], [42]–[46]. The electrical characteristics of super capacitors highly depend on the selection of the electrolyte and electrode materials [43]. Super capacitors have several advantages, such as high energy efficiency (∼95%), large charge/discharge current capacity, long lifecycle (>50000), high power density (>4000) and low heating losses [36], [43], [45], [39], [47]. However the maximum operating voltage of ultra-capacitors is very low and they suffer from high leakage cur- rent. Because of these two drawbacks, they cannot hold energy for a long time [42]. Recently, Li-ion capacitors have been developed with less leakage current and higher energy and power densities than batteries and standard super capacitors [42], [48], [49]. Onboard Energy Storage In onboard ESS, the storage medium is placed on the vehicle. It can be placed on the roof or under the floor of the vehicle. Placing ESS under the floor is relatively costly, because space is not readily available. A schematic overview of onboard ESS is shown in Fig. 2-2. The efficiency of onboard ESS is highly dependent on the characteristic of the vehicle, which can directly affect the amount of energy produced and consumed during braking and acceleration, respectively [50]. Other advantages of onboard energy storage are peak power reduction, voltage stabilization, catenary free operation and loss reduction [51]. On the other hand, the cost of implementation, maintenance, and safety concerns, are high because unlike wayside storage, in onboard ESS, an ESS is needed for each train.

ESS ESS

Third rail Braking Train Charging ESS Accelerating Train discharging ESS Fig. 2-2 Onboard energy storage systems.

Onboard ESS is already in use by some rail transit agencies. In addition, several agencies all around the world are considering –or actually testing- it. Various technologies have been used for onboard ESS; among them, super capacitors have been more widely implemented in many transit systems. Due to safety and cost limitations, onboard flywheels did not acquire much attention, and still need more investigation. However, there are some ongoing efforts. For instance, construction of a prototype for hybrid electric vehicle by CCM has been reported in [52]. An agreement between Alstom Transport and Williams Group on installation of onboard flywheel on trams has been reported in [53]. On the other hand, batteries have not been able to compete with super capacitors due to their short lifetime, and low power density. Important examples of real world implementation of onboard ESS are Brussel metro and tram lines and Madrid Metro line in Europe that show 18.6%–35.8% and 24% energy saving, respectively [54], [55] [56]. Japan metro with 8% saving of regenerative braking energy, and Mannheim tramway with 19.4%–25.6% increase in the overall system energy efficiency are two other examples of real world implementation of onboard ESS [57], [58]. In academic research, studies mostly focus on optimal design, sizing and control of onboard ESS. For instance, in [59], an onboard super capacitor ESS control strategy integrated with control has been presented. A control method for maximum energy recovery has been presented in [60]. In this method, a line in Rome metro has been considered as a case study. Theoretical Results show 38% energy recovery. Table 2-3 provides an overview of various examples for onboard ESS worldwide. Wayside Energy Storage A schematic overview of wayside ESS is shown in Fig. 2-3. The main concept of wayside ESS is to temporarily absorb the energy regenerated during train braking and deliver it back to the third rail when needed. Generally, it consists of a storage medium connected to the third rail through a power control unit [61][62].

Third rail Braking Train AcceleratingTrain Charging ESS Discharging ESS

ESS ESS

Fig. 2-3 Wayside energy storage systems.

Table 2-3 Examples of Onboard Energy Storage Implementations Type Location Purpose Comment Reference

Ni-MH Sapporo Energy saving Giga-cell NiMH batteries provided by Kawasaki has [70] Catenary free operation been used. It can be fully charged in five minutes through the 600V DC overhead catenary. Li-ion Charlotte Energy saving -- [70], [140], Catenary free operation. [141] Ni-MH Lisbon Operation without overhead contact The SITRAS HES (hybrid energy storage) energy [6], [142] line storage system has been used. Ni-MH Nice Catenary free operation. - [55], [97] Super capacitor Mannheim Reduction of energy consumption and A 400V system with l kWh energy [64],[143]– peak power demand. 640 Ultra-caps, with a capacity of 1800F each. [145] Catenary free operation. Super capacitor Innsbruck Energy saving - [6] Super capacitor Seville, Energy saving, Catenary free operation. - [141] Saragossa Super capacitor Paris Energy saving, Catenary free operation Could also be recharged from the overhead contact [141], [146] system in about 20 seconds during station stops. Flywheel Rotterdam Energy saving Flywheel located at the roof. Flywheel system was [70], [147] (France) Catenary free operation developed and installed by ALSTOM. However, the project stopped due to technical issue. Battery Brookville Catenary free operation. - [141]

In addition to the general advantages that were previously mentioned for energy storage systems, wayside ESS can also help minimize problems related to voltage sag [4], [50], [63].Voltage sag, which is temporary voltage reduction below a certain limit for a short period of time, can damage electronic equipment in a rail car, and affect the performance of trains during acceleration. ESS can be designed to discharge very fast, and by injecting power to the third rail, they help regulate its voltage level [64]. In addition to the economic benefits provided by ESS through recapturing braking energy, ESS can be designed to participate in the local electricity markets as a distributed energy resource [65]. Some other applications that can be provided by wayside ESS include peak shaving, load shifting, emergency backup and frequency regulation [8]. In Madrid, an operating prototype is demonstrating the use of the rail system infrastructure including wayside ESS for charging electric vehicles [66]. Real world implementation of wayside ESS has reported energy savings of up to 30%. The amount of energy saving by ESS highly depends on the system characteristics and storage technology. As an example, the commercially available wayside ESS, Sitras SES (Static Energy Storage) system marketed by Siemens is presented as a solution that can save nearly 30% of energy. The proposed ESS use a supercapacitor technology that can provide 1MW peak power, and is capable of discharging 1400 A DC current into the third rail during 20–30 second. Sitras ESS is implemented in different cities in Germany (Dresden, Cologne, Koln and Bochum), Spain (Madrid) and China (Beijing). Bombardier has developed a system based on super capacitors, the EnerGstor, which is capable of offering 20% to 30% reduction in grid power consumption. An Energstor prototype, sized 1 kWh per unit, has been designed, assembled and tested at Kingston (Ontario) [6]. Another Supercapacitor-based system that is commercially available is Capapost, developed by Meiden and marketed by Envitech Energy, a member of the ABB Group, with scalability from 2.8 to 45 MJ of storable energy. This system has been reported to be installed in Hong Kong and Warsaw metro systems [67]. Table 4 provides an overview of various applications of wayside ESS all over the world. This information is mostly published by manufacturers of wayside ESS like Siemens [6], ABB [65], VYCON [68], [69], Pillar [70].

Reversible Substation Another approach to reuse regenerative braking energy is through the use of reversible substations, as shown in Fig. 2- 4. A reversible substation, also known as bidirectional or inverting substation, provides a path through an inverter for regenerative braking energy to feed back to the upstream AC grid, to be consumed by other electric AC equipment in the substation, such as escalators, lighting systems, etc. [79]. This energy can also feed back to the main grid based on the legislations and rules of the electricity distribution network. Reversible substations must maintain an acceptable power quality level for the power fed back to the grid by minimizing the harmonics level [79].

Rectifier Transformer AC Network HV DC Network

AC DC

Inverter Fig. 2-4 Block diagram of a reversible substation.

Table 2-4 Examples of Wayside Energy Storage Implementations Type Location Voltage Purpose Comment Reference Li-ion Philadelphia 660V - Energy saving ENVILINE™ ESS provided by ABB has been [65],[131] - Optimize SEPTA’s power and used. voltage quality - Frequency Regulation Market Revenues

NAS Long island 6kV AC - Peak shaving There were several challenges reported with [36],[136], this project, such as the sizing of ESS, safety [137], [139] issues, and unexpected costs. Li-ion West Japan 640V - Energy saving - [148] - Voltage stabilization

Li-ion Nagoya 640V - Voltage stabilization - [148]

Li-ion Kagoshima 640V - Voltage enhancement The ESS was far from the substation and [148] controlled remotely via internet. Ni-Mh Osaka 640V - Energy saving The battery was connected directly to the [148] electric line. Li-ion Kobe 640V - Voltage enhancement - [148]

Super Capacitor Seibu 640V - Energy saving - [148]

Ni-MH New York 670V - Voltage enhancement The battery was directly connected to the third [149] rail. Flywheel London 630V - Energy saving Flywheel system provided by URENCO. [36], [150], - Voltage enhancement [151]

Flywheel Los Angeles - - Energy saving Flywheel system provided by VYCON [68], [69]

Flywheel Hanover - - Energy saving Flywheel system provided by Pillar [70]

Flywheel New York 670V - Energy saving Flywheel system was provided by KINETIC [70] TRACTION, and successfully tested at Far Rockaway. However, the project was stopped due to budget constraints. Super Capacitor Madrid 750V - Voltage stabilization Sitras SES has been used. [6]

Super Capacitor Cologne 750V - Energy saving, voltage stabilization Sitras SES has been used [6]

Super Capacitor Beijing 750V - Energy saving Sitras SES has been used [6]

Super Capacitor Toronto 600V - Energy saving Sitras SES has been used [6]

Even though reversible substations are designed to have the ability to feed regenerative braking energy back to the upstream network, if maximum regenerative energy recuperation is targeted, priority should be given to the energy exchange between trains on the DC side of the power network. There are two common ways to provide a reverse path for the energy: 1) using a DC/AC converter in combination with a diode rectifier; and 2) using a reversible thyristor- controlled rectifier (RTCR). In the first approach, the DC/AC converter can be either a pulse width modulation (PWM) converter, or thyristor line commutated inverter (TCI) [80]. It is worth mentioning that in the first approach, the existing diode rectifier and transformer can be kept, and some additional equipment needs to be added for reversible energy conduction. However, in the second approach, the diode rectifiers need to be replaced with RTCRs and the rectifier transformers need to be changed, which makes this approach more expensive and complex [80]. However, RTCRs have advantages, such as voltage regulation and fault current limitation [81]. A TCI is an anti-parallel thyristor controlled rectifier (TCR) connected backward to provide a path for transferring energy from the DC side to the AC one. This technology has been used in an Alstom reversible substation setup called HESOP (Harmonic and Energy Saving Optimizer) [82], as shown in Fig. 2-5. The rated current of the TCI is half of that of the forward TCR, which reduces its cost. To use a TCI with an existing circuit, an auto transformer and a DC reactor should be used to increase the AC voltage, and limit circulating currents between the TCI and the diode rectifier. To minimize AC harmonics, a 12 pulse system has been proposed in [80]. As mentioned above, a diode rectifier can also be combined with a PWM converter to provide a reverse path for the energy. PWM converters have the advantage of working at unity power factor, and the disadvantage of high cost and high switching losses. In order to use PWM converters for reversible substation purposes, a step up DC/DC converter should be added between the PWM converter and the DC bus. In addition, to reduce the harmonics level and avoid current circulation, a DC filter needs to be added at the output of the converter. A similar technology has been developed by INGEBER, where, an Inverter and a DC chopper (DC/DC converter) are connected in series, and their combination is connected to the existing substation [83], [84]. Fig. 2-6 shows a typical RTCR. It consists of two TCRs, which are connected in parallel, pro- viding a path for the energy in forward and reverse directions. Only one of these TCRs can be fired at a time; therefore, no current will circulate between them, and there will be no need for a DC inductor. When RTCR is working in the forward direction (AC/DC), the inverter acts as an active filter. However, the rectifier only works in the traction mode [82]. In order to switch between the rectifier and inverter modes, a single controller provides pulses for both of them without any dead time [82]. A comparison between the aforementioned reversible substation technologies is presented in Table 2-5 [80].

Medium Voltage circuit Breaker Converter Transformer AC Circuit Breaker Auto- transformer AC AC Diode Rectifier DC DC Inverter Choking Coil

DC DC Incomming panel Disconnector

DC Section feeder

Fig. 2-5 Block diagram for HESOP reversible substation.

Grid

Substation

DC Side Chopper Inverter Connection L DC DC

DC AC DC Zero Link Current Inductor 1500 VDC Catenary

Fig. 2-6 Block diagram for diode rectifier/PWM converter reversible substation. Table 2-5 Comparison of Different Types of Reversible Substations

Parameters TCISitras TCIIngeteam RTCR Pregen peak (MW) 3 1.5 3

Prectifier peak (MW) 0 0 12 Efficiency (%) 96 92–94 97 Size (m3) 2.4 × 1 × 2.3 NA 3.5 × 0.8 × 2.5 Footprint (m2) 2.4 7.5 5.25 Weight (t) 2.65 NA NA life (years) 20+ 20+ 20+

Table 2-6 Examples of Reversible Substation Implementations

Company Location Voltage Technology Energy Saving Comment Ref. Level Alstom- Paris Tramway Thyristor 7% of traction - Recuperated more than 99% of recoverable braking [82], HESOP rectifier bridge consumed energy. [169], associated with energy - Reduced train heat dissipation, which led to reducing [170] 750 an IGBT energy consumption used for ventilation. Utrecht–Zwolle converter - No need for onboard braking resistors; therefore, train mass was reduced leading to less energy consumption London during acceleration.

Milan Metro 1500

Simense- Oslo, 750 Inverter, B6 - -Remote control is possible through a communication [70] Sitras TCI Singapore thyristor bridge, interface. autotransformer - Reduced the number of braking resistors on the train. Zugspitze, 1500 in parallel with a - In the 750V version, an autotransformer is integrated Germany diode rectifier with the inverter, but in the 1500V version or high power 750V, an autotransformer is installed separately.

Ingeber- Bilbao -Spain 1500 Inverter in 13% of the - The current injected to the AC grid is in high quality [70], Ingteam parallel with substation (THD < 3%). [83], Malaga -Spain 3000 existing rectifier annual energy - A DC/DC converter and an inverter are connected in [84], and transformer consumption series, and their combination is connected to an existing [171] Bielefeld- 750 grid. Germany - Reduced carbon emissions by 40%. Metro Brussels. 750

However, the rectifier only works in the traction mode [82]. In order to switch between the

rectifier and inverter modes, a single controller provides pulses for both of them without any dead time [82]. A comparison between the aforementioned reversible substation technologies is presented in Table 2-6 [80]. Beside these technologies, ABB also pro- posed two technologies called Enviline TCR and Enviline ERS. Enviline TCR is a Traction Control Rectifier that uses four quadrant converters to provide a reverse path for energy flow in the substation. This technology can be connected in parallel with an existing diode rectifier in a substation [85]. Enviline ERS is a wayside energy recuperation system consisting of an IGBT based inverter that can be connected in parallel with the existing substation’s rectifier to return surplus energy to the main grid, and can also be configured to work as a rectifier to boost rectification and provide reactive power support, if needed [86]. Some of the currently available reversible substation systems are summarized in Table 6. Choosing The Right Application Different technologies/techniques have been proposed to reuse regenerated braking energy. A comparison between the general pros and cons associated with these alternatives is presented in Table 2-7 [70], [80]. Choosing the right regenerative energy recuperation technique/technology requires careful consideration of various influential parameters, such as [39]: • Catenary-free operation • Electric network ownership • Electric network characteristic • Vehicles • Headways Catenary-free operation provides an opportunity for vehicles, especially tramway, to run without connection to the overhead line. It is a good solution for operating trams in, for instance, historic areas. In this case, only onboard energy storage can be used, and can be charged through regenerative braking and/or fast charging infrastructure in the stations [39].When considering different applications of energy recovery, electric network ownership plays an important role. In many cases, local energy providers own the power system infrastructure, and transportation companies have limited autonomy on the electric network. In this case, if there is a possibility to sell the recovered energy for a high price, reversible substations may be the best option. Otherwise, wayside energy storage should be selected [39]. The characteristics of the network represent another important parameter that should be considered when selecting the energy recovery technique. For example, in some stations with a high level of traffic, the energy exchange between braking and accelerating trains occurs naturally. Therefore, the energy recovery application should be designed in a way that gives priority to natural energy exchange between the trains. Moreover, some stations face serious voltage drop (due to aging, etc.) when several trains accelerate simultaneously. In this case, wayside energy storage may be used to help sustain the third rail voltage [39]. The type of vehicle used in a transportation system is also an important factor. For example, in some systems, old and new vehicles may be running together, while old vehicle may not have the ability to regenerate energy during braking. Therefore, investing in energy recovery may not yield the same value. In addition, the weight of the vehicles affects the regenerative braking energy, such that heavier vehicle produces more energy during braking. An average rate of train occupancy should be considered during designing and analyzing the ESS system [39].

Table 2-7 A Comparison between Different Recuperation Techniques Application Advantages Disadvantages Onboard ESS -Provides possibility for catenary-free operation. -High cost due to placement of ESS on the vehicle. -Reduces voltage drop. -High safety constraints due to onboard passengers. -Reduces third rail losses and increases efficiency. -Standstill vehicles for maintenance and repair. Wayside ESS -Mitigates voltage sag. -Increases overhead line losses due to the absorption and release of -Can be used by all vehicles running on the line (within the energy over the traction line. same section). -Analysis is needed to choose the right sizing and location. -Maintenance and repair do not impact train operation. Reversible -Provides possibility for selling electricity to the main grid. -No voltage stabilization. Substation -Can be used by all vehicles running on the line. -Analysis is needed for choosing the right location. -Maintenance and repair do not impact train operation. -Lower safety constraints.

3 ELECTRIC RAIL TRANSIT SYSTEM MODELING We developed a simulation tool to study regenerative braking energy recuperation in DC rail transit system, and to investigate the performance of different technique such as wayside energy storage, reversible substation and Hybrid reversible and wayside energy storage on utilizing regenerative braking energy. In the proposed simulation technique, multi-train operation and several types of ESS technologies are considered and simulated. In previous studies, the dynamic behavior of system components is neglected; trains and ESSs were modeled with current sources and substations were modeled as a voltage source behind a diode rectifier. An advantage of the proposed simulation tool over previous efforts is the detailed system modeling. In order to verify the reliability of the proposed simulation tool, the results are validated versus real measurement from NYCT subway system. 3.1 Power Supply Substation Modeling In DC electric rail transit systems, the power required by trains is provided by a power supply network including rail network and substations. Generally, substations consist of voltage transformers that step down the voltage and a unidirectional rectifier that converts electricity from AC to DC. In order to increase the reliability of the power supply, two sets, each consisting of a transformer and a rectifier, are connected in parallel. One of the transformers is connected as Y-Δ and the other one is connected as Δ-Δ in order to avoid phase shift. A capacitor bank is added at the output of transformers for fixing its output voltage. There are circuit breakers, insulation and other protection devices at both AC and DC sides to increase the safety. Substations feed DC voltage to the overhead line or third rail (a rail next to the running rail) to supply the train power. The magnitude of DC voltage depends on the power demand and length of the third rail. Typical values are 600-750V. However, there are also available systems with 1500V and 3000V [3]. More information about DC power supply networks can be found in [4], [5]. A detailed substation model that is used as a module in the proposed simulation tool is presented in Fig. 3-1. The description and values of the parameters related to each component are presented in Table 3-1. As mentioned above, vehicles get their required power from either overhead lines or third rails. Running rails provide a return path for the current and make the power circuit complete. The rail

Three-phase main grid

AC Circuit Breaker

AC Insulator

Y/∆ ∆/∆

C C

AC AC

DC DC + - + - T o

R A R L u o x DC Circuit Breaker a i d l i a r

DC Insulator y + Third Rail -

Running Rail Fig. 3-1 Substation schematic.

RPW RPE Train Position + R calculated + - Power supply Position Passenger Passenger + Memory Station 1 Station 2 Resistance Per Unit Length s i + - + - RTW R TE + Output Voltage - V=Ri Fig. 3-2 Schematic of the train running between two Fig. 3-3 Schematic of the variable resistance modeling passenger stations.

Table 3-1 Substation Parameters Symbo Description (unit) Value l Pn nominal power (kVA) 1663 fn nominal frequency (HZ) 60 V1 RMS voltage of primary winding (V) 13200 V2 RMS voltage of secondary winding 465 (V) R1, R2 resistance of primary and secondary 2.66, winding (Ω) 0.003 L1, L2 inductance of primary and secondary 6670, winding (µH) 9.19 Rm magnetization resistance (Ω) 3000 Lm magnetization inductance (Ω) 2000 C capacitor bank (F) 0.001 Req equivalent resistance 0.002 system network is divided into several sections to provide easy operation, protection and maintenance. Sections are connected to each other by means of traction circuit breakers. Depending on the status of circuit breakers, each section can be powered by one or two substations at both ends. When a train moves on the traction rails, the resistances between the train and its departure and arrival points are changing based on the distance between them at each time instant [6]. In order to simulate the movement of vehicles, rail sections are modeled by variable resistances. Variable resistances are modeled by a controlled voltage source, as presented in Fig. 3-2. A section of the rail with a vehicle running from west to east is presented in Fig. 3-3. Equations related to each variable resistance are presented in (1) to (4) [6].

RPW = xp Rpower_ rail (1)

RPE = (L - xp )Rpower_ rail (2)

RTW = xp Rtraction_ rail (3)

RTE = (L - xp )Rtraction_ rail (4)

Where RPW and RPE are the power rail resistances at west and east side of the train. Similarly, RTW and RTE are the traction rail (running rail) resistances. Rpower_rail and Rtraction_rail are the resistances of power and traction rail per unit of length. L is the distance between two passenger station and xp is the train position. 3.2 Train Modeling There are two main approaches to model a train: 1) Forward modeling, known as cause-effect modeling. 2) Backward modeling, known as effect-cause modeling. In forward modeling of the vehicle, the input (cause) will be current/power absorbed by the vehicle. By following the dynamics of every component of the vehicle, the speed of the wheels (effect) can be calculated. In backward modeling, the analysis is performed in the reverse direction, i.e. the speed of the wheels (effect) is considered as an input and, going backward through the various components, the current/power required by the vehicle (cause) is calculated. In this study, the backward methodology is used to model the vehicles. The modeling process is presented in Fig. 3-4. As illustrated, there are three main stages to calculate the required power of the train in the backward approach; including vehicle dynamic calculation stage, gearbox stages and motor’s drive stages. There are several forces applied to the wheels, including friction force (FR), the force due to the wind (FW) and gravity force (Fg). These forces should be overcome by the tractive effort (FT) created by the motors of the vehicle. In the first stage, speed of the wheel (v) and inclination angle of the path (Ɵ) are considered as inputs and using vehicle dynamic equations, (5) to (10), the tractive effort applied to the wheel is calculated and from there the required torque (Tw) and angular speed (ωw) of the wheels are determined and used as inputs for the next stage, which is a gearbox. The role of a gearbox is to reduce the speed of the motor drive connected to its shaft while increase output torque of the motor drive. In the backward approach, using the equations that described the gearbox performance, (11) to (14), the required torque (TG) and the speed of the motor drive (wG) are determined. dv F - F - F - F = M T R g W Metro dt (5) F = f M g cosq R R Metro (6) F =M gsinq g Metro (7) 1 F = C Arv2 (8) W 2 w F ´ r T = T (9) w 4n cars v w = (10) w r Where, Mmetro is the weight of the train, fR is the friction factor, g is the acceleration gravity, Cw, A and ρ are drag coefficient, front area of the train and air density, respectively. The number of cars and the radius of the wheels are presented by n and r, respectively. Gearbox equations in motoring condition are: T B T = w + G γ γ G G (11)

FN FW

v

Gear Fg Motor Motor Box Gear Drive Drive Box FT

FR Ө Mg

Speed Tw TG Rail Vehicle Dynamic Pw Gear box PG Motor Drive PT Transit Gradient Network ωw ωG

Fig. 3-4 Vehicle modeling process.

- +

ψs Sk Chopper Ψs* + - circuit

Switching S1

Te* + Table S2 - S3

n Te o i

t Vd c Flux

n ψs dq u

f & Vq Vabc

x Sk Torque abc u l

F id dq Iabc Te Calculation D iq I s P abc p m a r

d

- Low Pass e ω rpm to m/s e

p + Filter S Speed Sensor * ω

ω Speed Control Unit

Fig. 3-5 Vehicle modeling process.

wG = wwg G (12)

Where, gG is the gearbox ratio and B represents the vehicle losses and is calculated using (9).

B = Tw (1-hG ) (13) Where, ηG is the gearbox efficiency. For the braking process (negative torque), (11) can be modified as follows:

Tw B TG = - (14) g G g G In the last stage, the calculated torque and speed from the gearbox are given to the motor drive to calculate the current required by the vehicle. In this paper, two models are proposed for drive modeling: 1) Detailed model and 2) Approximate model. In detailed modeling, every component of the vehicle’s drive is represented and modeled, which makes the model more accurate but more complex and it takes the longer time to simulate. The Approximate model is less accurate but fast because it does not consider the dynamic behavior of every component. 3.3 Electric Vehicle Modeling Electric trains consist of several cars connected to each other. Each car has a set of motor drive and gearboxes connected to a shaft. Each shaft has two wheels connected to it. Typically, a motor drive consists of the induction motors, an inverter and its controller, and a chopper circuit. To model the drive, a (DTC) DTC drive available for AC machines in MATLAB/Simulink library has been modified and adopted. A schematic of the motor drive is presented in Fig. 3-5. Control methods available for induction motor can be classified into two main groups: 1) scalar- based controller (control magnitude and frequency of variables in steady states); 2) vector-based control (control magnitude, frequency and the instantaneous position of space vector of the variable). Vector-based control also classified into filed oriented, feedback linearization, direct torque control and passively based control [7]. DTC control is used in this study to control the induction motor. This controller works based on control of voltage (output voltage of inverter). In this control strategy, at each time step, a voltage vector is applied to the inverter in order to reduce the error of torque and flux. There is no intermediate current controller in this technique which makes the controller fast and robust [8]. Most of the equations and description related to DTC controller is presented in the Appendix A. In summary, as illustrated in Fig. 3-5, the torque and flux are calculated from the voltage and current of the motor. Then the estimated torque and flux are compared with their references produced by the speed controller section. In the speed controller part, the speed of the motor, which is converted to m/s from rpm, is compared with the reference speed and the error is applied to the PID controller, followed by a limiter block. The limits depend on the motor rating. The output of this part is a reference torque. Flux reference is also produced from motor speed and flux calculation block worked based on (15) [7].

Ls 2 2 Lr T 2 y s = ( y r ) + (sLs ) ( ) LM LM y r (15)

2 Where, σ =1-(M /Ls Lr). The error of the torque and the flux are given to the hysteresis comparator, where the flux comparator has two limits based on the following conditions:

Hy =1 for ey > +HBy

Hy = -1 for ey < -HBy

Where, eψ is the flux error and ± HBψ are the upper and lower hysteresis band of the flux. Torque hysteresis comparator has three limits based on the following conditions:

HT =1 for eT > +HBT

HT = -1 for eT < -HBT

HT = 0 for -HBT < eT < +HBT Where, eT is the flux error and ± HBT are the upper and lower hysteresis band of the torque. The flux hysteresis band has an impact on stator current distortion and torque hysteresis band affect the switching frequency [9]. The hysteresis controllers outputs along with sector index (Өe) are used as inputs to the switching lookup table, presented in Table VI of Appendix A [10]. The last component in the motor drive is the breaking chopper. It consists of a resistor bank and an IGBT switch, which is controlled by a hysteresis controller. A schematic view of the braking chopper is presented in Fig. 3-6. The chopper circuit monitors the DC bus voltage, if the voltage goes above a pre-specified value (upper limit activation voltage), the IGBT switch turns on. Then,

g

+ -

Fig. 3-6 Block diagram of the braking chopper. the excess power on the line will be dissipated in the resistor bank. The switch is turned off when

the voltage drops to the lower voltage limit (lower limit shut down voltage). 3.4 Energy Storage Modeling Batteries, supercapacitors and flywheels are three types of technologies commonly used in DC electric rail transit systems. In the MATLAB/Simulink environment, there are available models for battery and supercapacitor. These two options are modified and adopted based on the desired design and parameters. To connect the battery and supercapacitor to the electric rail system, a bidirectional DC/DC converter is designed and modeled. The Flywheel energy storage system is modeled using a permanent machine connected to a rotating mass. Batteries The battery is modeled with a controlled voltage source in series with a resistance. This model is a generic dynamic model and can represent the different types of rechargeable battery, such as Lead-Acid, Lithium-Ion, Nickel- Cadmium and Nickel-Metal-Hydride. Each technology can be modeled by adjusting its parameters and equations. Fig. 3-7 presents a schematic view of the battery model. For the sake of brevity, the equations related to battery model is presented in Appendix B. The battery is connected to the system by means of the bi-directional DC/DC converter, presented in Fig. 3-8. During charging, only S1 is turned on and during discharging mode only S2 is turned on. More information about this type of bidirectional DC/DC converter can be found in [11]. The current (I_command) is produced by battery energy management unit that is working based on some general rules as follows: 1) If VPCC >Vset_ch, charging command up to a level of SOC=90%

2) If VPCC

3) If Vset_dis t4 î1+ sRSC CT g R1 L1 I_battery 2 Low pass filter Charge (0) Discharge (1) + + v i g1 S2 vout n S1 - - t I_command ò + PID 0 - I Exp(s) A <= Bat = mod e(s) 1/(B.i(t)).s +1 PWM g1 + Rin I_command 0 + Vbat Ein Eq.(33, 34) - g2 + PID - <= - I_command PWM Fig. 3-7 Battery Model Fig. 3-8. Bidirectional DC/DC converter

Table 3-2 DC/DC Converter Parameter Symbol Description (unit) Value

Vin Battery output voltage (V) 645 Vout Substation voltage (V) 500 D Duty cycle 0.44 f Switching frequency (kHz) 5 L1 Input inductance (mH) ≥ 0.1 R1 Inductance resistance (Ω) 3.2468

Iself-disch

=0 i = I sc (1- u(t)) + iself -disch .u(t) u(t)

Isc t ò + Rin 0

E + V in Eq.(35) sc -

-

Fig. 3-11 Supercapacitor model

Vsc(V)

t(s) t1 t2 toc t3 t4 t5 Isc(A)

t(s)

Fig. 3-10 Discharging current and voltage of supercapacitor

Tref I d abc Current w Current Speed Calculator Controller w Regulator dq ref Iq y ref I abc Switching Control g

I abc Rotating Mass + w IM -

w Speed Sensor

Fig. 3-9 Flywheel model

Where, CT is the total capacitance, RSC is the internal resistance and α1, α2 and α3 are constants and are equal to the rate of change of supercapacitor voltage at the corresponding time interval.

Flywheels

A flywheel ESS consists of a rotating mass, an , which can act as a generator or motor, and a power electronic interface. Schematic of flywheel modeling is presented in Fig. 3- 11.

The rotating mass is modeled based on the flywheel’s energy and speed equations and limitations. Since the rotating mass is coupled with the electric machine, its speed is equal to the speed of the machine. This speed is considered as an input to the rotating mass model. The speed of flywheel is limited between wmin and, wmax which are the minimum and maximum speed allowed for flywheel operation, respectively. If the input speed is beyond the speed limit of flywheel, this speed will change to the boundary value. Then the energy of the flywheel is calculated based on (17). 1 E = Jw 2 (17) 2 Where, E is the energy, J is the flywheel Inertia and w is the flywheel speed. The flywheel power is presented by (18): dE P = (18) dt Having the power and speed of a flywheel, the mechanical torque input for the electric machine is calculated based on (19).

Table 3-3 Flywheel Parameters Symbol Description (unit) Value

kWhd Delivered Energy (kWh) 0.52 Ppeak Peak (continuous) Power (kW) 375-750 Ms System Mass (kg) 1000 ωmax Flywheel maximum speed (rpm) 20000 ωmin Flywheel minimum speed (rpm) 10000 V Voltage (V) 420-800 Imax Maximum current of each module (A) 167 Kp, Ki Proportional and integral gain of speed controller 5, 100 Tmax, Tmin Speed controller output torque saturation (N.m) 256

P T = (19) w The electric machine used in this study is a permanent magnet synchronous machine, which is controlled via a 3-level AC/DC converter. During the charging process, the converter acts as an inverter and the electric machine acts as a motor and speeds up the flywheel. During the discharging process, the flywheel slows down and the motor acts as a generator, while the power electronic converter acts as a rectifier that injects the released energy of the flywheel to the third rail. The parameters and their values used for flywheel modeling are presented in Table 3-3. 3.5 Reversible Substation Modeling As mentioned earlier, one of the techniques for recuperation of regenerative braking energy is reversible substation, which is also known as a bidirectional or inverting substation. In this technique, a reverse path is created in the structure of the substation to feedback the power to the upstream AC grid. However, the power can feedback to the main grid based on the legislation and rules of the electricity distribution network [7]. Reversible Substations are classified into two main groups: 1) substations that have a DC/AC converter in combination with a diode rectifier; and 2) substations that have a reversible thyristor- controlled rectifier (RTCR). In the first type, the existing diode rectifier and transformer can be kept, and some additional equipment needs to be added for reversible energy conduction. while, in the second type, the diode rectifiers need to be replaced with RTCRs and the rectifier transformers need to be changed, which makes this approach more expensive and complex [8]. Some examples of reversible substation implementation/testing are presented in Table 3-4 [1]. In this study, the first type of reversible substations is molded and simulated. Schematic of the Table 3-4 Reversible Substation Parameters. Parameter Value Input Capacitors 12000 µF Filter Resistance 2 mΩ Filter Inductance 250 µH Transformer Power 1663 KVA Transformer Voltage 250V/13.2 KV Transformer 2.6623/0.003 Resistance pu Transformer 0.006/9e-6 pu Inductance

reversible substation model is presented in Fig. 3-12. To create a reverse path a set of inverter, filter and a transformer in series are placed in parallel with the existing substation structure. The parameters related to each component are presented in Table 3-5. The reversible substation sends power to the main grid by regulating the DC voltage of the third rail. During deceleration, regenerative braking energy is injected to the third rail and if there is no other load to absorb it, the voltage of the third will increase. The deviation of the voltage from its nominal value can activate the reversible substation inverter and based on its control circuit, it will send the third rail excess power to the main grid.

Table 3-5 Examples of Reversible Substation Implementations Company Location Voltage Technology Energy Saving Comment Ref. Level Alstom- Paris Tramway Thyristor 7% of traction - Recuperated more than 99% of recoverable braking [9], HESOP rectifier bridge consumed energy. [10], associated with energy - Reduced train heat dissipation, which led to reducing [11] 750 an IGBT energy consumption used for ventilation. Utrecht–Zwolle converter - No need for onboard braking resistors; therefore, train mass was reduced leading to less energy consumption London during acceleration.

Milan Metro 1500 Simense- Oslo, 750 Inverter, B6 - -Remote control is possible through a communication [12] Sitras TCI Singapore thyristor bridge, interface. autotransformer - Reduced the number of braking resistors on the train. Zugspitze, 1500 in parallel with a - In the 750V version, an autotransformer is integrated Germany diode rectifier with the inverter, but in the 1500V version or high power 750V, an autotransformer is installed separately. Ingeber- Bilbao -Spain 1500 Inverter in 13% of the - The current injected to the AC grid is in high quality [12], Ingteam parallel with substation (THD < 3%). [13], Malaga -Spain 3000 existing rectifier annual energy - A DC/DC converter and an inverter are connected in [14] and transformer consumption series, and their combination is connected to an existing Bielefeld- 750 grid. Germany - Reduced carbon emissions by 40%. Metro Brussels. 750

Main Distribution Grid A B C Iabc Vabc ω PLL Ɵ ω

Vabc Unidirectional abc Vd, Vq Substation Inverter Transformer dq Uabc_ref PWM g RPW Current RPE - Generation Generator + + Regulator Iabc abc Id, Iq

VDC V N dq Filter

- VDC_m Id_ref Iq_ref RTE Voltage RTW Regulator g VDC_ref Fig. 3-12. Schematic of a reversible substation and its controller

Since the reversible substation will be used to provide grid services as a smart inverter, independent control of active and reactive power is needed. Therefore, the reversible substation will be controlled using vector-decoupling pulse-width-modulation (PWM) technique [7]. Vector- decoupling control requires coordinate transformation to the d-q frame of references. Feedback and feedforward control techniques of such converters are possible. However, they are complicated and require accurate mathematical modeling of the inverter. Hence, we will use three Proportional-Integral (PI) controllers to build the control model in real-time, although the mathematical model will be established in order to have a successful decoupling of the vectors. The voltage equation of a three-phase PWM converter is as follows, di (20) e = Ri + L s + v s s dt r di L de - wLi + Ri = e - v (21) dt qe de de de di L qe - wLi + Ri = e - v (22) dt de qe qe qe

Where, es and is are respectively source voltage and current, vr is converter input voltage, R, L are Resistance and inductance of the boosting inductor, respectively and w is the angular frequency of the voltage source. For fast voltage control, the input power should supply instantaneously the sum of load power and charging rate of the capacitor energy. Neglecting the resistance loss and the switching device loss, the power balance between the ac input and the DC output is as follows, 3 P = (edeide + eqeiqe ) = vdcidc (23) 2 Where vdc and idc are the DC output voltage and current, respectively. On the dc output side, dv i = -C dc - i (24) dc dt L

Where iL is the load current. From (24) and (25),

3 dvdc (edeide + eqeiqe ) = -Cvdc - vdciL (25) 2 dt

In order to enhance the performance of the current control loops, the decoupling term (wLide) and cont cont vrq v (wLiqe) were included while calculating and rd , respectively. These voltages are the modulation signals for the PWM technique. The equations used in building the controller are given by (26),

cont ref ref vrq = wLide + eqe - Riqe - K p .[ide - ide ]- Ki .ò[ide - ide ]dt (26) cont ref ref vrd = -wLiqe - Riqe - K p .[ide - ide ]- Ki .ò[ide - ide ]dt The control schematic of the inverter is presented in Fig.18.The control parameters are presented in Table 3-6. In summary, the train accelerates producing regenerative braking energy. If this energy is not captured, the voltage will rise leading the train to be electrically disconnected. However, in this case, the reversible substation will attempt to collect this energy by pushing the power back to the grid. The inverter is commanded to regulate the third rail voltage to 650V. Therefore, when the voltage starts to rise as a result of the regenerative braking energy, a mismatch between the measured voltage (VDC_m) and the reference voltage (VDC_Ref) starts to appear. As a result, some direct-axis (related to P) Id_ref starts to appear leading the inverter to send power to the main grid. In this test, since the set point for the quadratic-axis current Iq_ref (i.e., the component of the current controlling Q) is forced to zero, the inverter can operate at unity power factor. Table 3-6 Inverter Control Parameters Parameter Value VDC_ref 650 VDC Voltage regulator gain (Kp,KI) 7, 800 Voltage regulator saturation limits -3, 3 Current regulator gain Kp,KI) 0.3, 20 Current regulator saturation limits -2, 2 Iq_ref 0 Ts_Control 100 µs

3.6 Hybrid Reversible Substation and Wayside Energy Storage Modeling A hybrid reversible substation/WESS as illustrated in Fig. 3-13, is a combination of a reversible substation and a wayside energy storage system. Regenerative braking energy can be absorbed by both the ESS and the reversible substation based on a control signal received from the energy management unit . A key aspect of this technique is the energy management unit that provides setpoints/settings for both the energy storage system and the reversible substation. Setpoints are determined based on predefined modes of operation that can be classified into Grid Applications and Rail Transit Applications.

In the Rail Transit Application Modes, priority is given to the rail system. The reversible substation and ESS provide the following applications: • Maximum recuperation of regen braking energy (Mode=1) • Peak demand reduction of the rail transit system (Mode=2) In the Grid Application Modes, priority is given to the grid. The reversible substation and ESS collaborate to provide the desired output for each of below applications: • Feeder peak demand reduction (Mode=3) • Voltage regulation and reactive power support (smart inverter) (Mode=4)

Besides the above application, a hybrid reversible substation can provide other services such as demand response, grid black start, and emergency backup for the rail transit system. For these services, special modes and settings need to be designed. ESS’s and inverter’s settings and reference points are determined based on offline simulation to make sure the operation of a hybrid reversible substation with these settings does not create any conflict with the normal operation of a transit system. Reversible substation setpoints are sent directly to inverters’ controllers and ESS setpoints feed into a state machine controller that controls charge and discharge of the energy storage. A flowchart of the proposed energy management is presented in Fig. 3-14. ESS state machine and its flowchart are presented in Figs. 3-15 and 3-16, respectively. ESS state machine determines the

Fig. 3-13. Schematic of a reversible substation and its controller ESS charge and discharge control parameter based on the voltage of the line, state of charge of

ESS, and setpoints received from the energy management unit.

Fig. 3-14 Flowchart of energy management unit

Fig. 3-15 schematic of the ESS charge and discharge controller

Fig. 3-16 Schematic of the ESS charge and discharge controller 3.7 Distribution Grid Modeling Con Edison Service Territory Overview Con Edison provides electric services to 3.2 million customers in New York City and portions of Westchester County. Electricity is delivered through approximately 94,000 miles of underground cable, and almost 37,000 miles of overhead cable. Fig. 3-17 illustrates Con Edison service territory map.

Fig. 3-17 Con Edison Network Territory. There are two types of electric distribution grid systems: radial grids, and network grids. Figure 3- 18 shows the schematic of a radial and a network grid. Radial Grids traditionally have a single high voltage cable, often referred to as a feeder, sending energy from the substation to numerous distribution transformers tapped at various points along its length. The distribution transformers step the voltage down to low-voltage electricity and typically serve between 1-16 customers. These systems are called radial grids because the substation and feeders resemble a hub with spokes. Cables and transformers on radial grids are often above ground, seen predominantly in areas like Staten Island or Westchester as illustrated in Fig. 3-17. Network grids have multiple primary feeders supplying several network transformers tied together in parallel on the secondary side to provide energy into a low voltage grid (area network type) or a local building bus (spot or isolated network) where the consumer is connected. Thousands of low voltage customers are served off the low voltage grid of an area network. Cables and transformers on network grids are typically below ground and are used in densely populated areas. Network grids are used extensively throughout Manhattan, Brooklyn, Queens, and the Bronx. Con Edison’s meshed distribution network has the following characteristics. • 69 kV, 138 kV, and 345 kV transmission • 27 kV for Brooklyn and Queens, 33 kV and 13 kV for Manhattan and Bronx • 50 area substations serving all networks • N-2 contingency design In order to examine the impact of sending regenerative braking energy from a reversible path to the distribution grid, a portion of the Con Edison distribution network, Borden network, is selected. The Borden network is located in Queens area and feeds two rectifier substations, the Jackson & West (Jackson) substation and the 50th AVE & 11th ST (50 AVE) substation as shown in Fig. 3-19. Con Edison network is originally modeled in PVL (Poly Voltage Load Flow), An in house software developed for load flow at one instant. In order to perform load flow study over 24 hours, Borden network PVL model is converted to OpnenDSS software using Matlab script, as illustrated in Figure 3-20.

Fig. 3-18 schematic view of radial and network grid

Fig. 3-19 Subway substations under study in this report.

Fig. 3-20 Model conversion from PVL to OpenDSS. In our study, the load flow ran for a whole day with 15-minute intervals, i.e., a total of 96 runs. Since Con Edison’s model looks at a snapshot of the grid at the peak, a load profile for each load has been created. These load profiles were assumed to follow the load profile of the area substation feeding the region under study. Therefore, the load curve of the substation was normalized, as depicted in Figure 3-21, and multiplied by the load value of each bus to create the load curves. The load profiles at the buses of the two rectifier substations are based on real interval metering data as shown in Figures 3-22 and 3-23 for two sample days.

1

0.8

0.6

0.4 Normalized Load Curve 0.2

0 0 5 10 15 20 Hours Fig. 3-21 Normalized load curve of the Borden network. 03/29/2017 4500 50 AVE 4000 Jackson

3500

3000

2500

2000 Power (kW) 1500

1000

500

0 0 5 10 15 20 Hours Fig. 3-22 Subway substation power profile for a sample day on March.

11/03/2017 4500 50 AVE 4000 Jackson

3500

3000

2500

2000 Power (kW) 1500

1000

500

0 0 5 10 15 20 Hours Fig. 3-23 Subway substation power profile for a sample day on November.

3.8 Validation Results In order to validate our proposed simulation tool, a portion of line 7 of NYCT consisting of 3 substation and 4 passenger stations is considered as a case study. NYCT map and a portion under study are presented in Fig. 3-24. A schematic of this system is presented in Fig. 3-25. This system is simulated for several cases and the results are compared with real measurements. Firstly, the results are compared for one cycle operation and then they are compared for 24 hours operation.

Fig. 3-24. NYCT map of the system under study

Substation3 Substation 1 Substation2 A A A B B B C C C

AC AC AC DC DC DC RPW RPE RPW RPE RPW RPE RPW RPE

Passenger passenger Passenger passenger Passenger Station 1 Station 2 Station 3 Station 2 Station 3

RTW RTE RTW RTE RTW RTE RTW RTE Fig. 3-25 Schematic of electric rail transit systems

3.9 One-cycle operation In this section, several speed profiles, from the real measurement, are given to the train model and the output results, i.e. third rail voltage and current of the trains, are compared with real measurements (5000 sample/second). Speed profiles which are given to the train as input and related current and voltage are presented in Fig. 3-26. As illustrated, in the first 15-20s, the speed increases with the maximum acceleration and consequently the current rises to its maximum. During the same time interval, the voltage slightly decreases to a lower value. After this, the speed increases with a smaller acceleration rate until it reaches the maximum speed and the current gradually decreases to an almost constant value. During deceleration, motors act as generators and produce (the current is in the reverse direction and here it is shown with negative values). The current will have different amplitudes and shapes, Based on the deceleration rate. In the last 20 seconds of deceleration, several fluctuations happen in the speed profiles which are reflected with larger fluctuations in the current. The results from simulation versus real measurements show that, with each of the speed profiles, the current and the voltage from simulation closely follow the real measurements for current and voltage.

3.10 24 hours operation The single-cycle operation of the rail transit model has been extended to a 24 hours operation for a more conclusive validation of the results. Besides, a 24 hours operation is imperative for the study of peak demand reduction of substations. This prototype has been obtained on the basis of train scheduling by NYCT [12]. The schedule provides information, such as headway between trains during different times of the day and the probability of two trains exchanging regenerative energy during peak hours of the day. This data is used to obtain factors for every fifteen minutes

Fig. 3-26 Validation results for one-cycle operation. 2500 Real Data 2000 Simulation Data

1500

Power (kW) Power 1000

500

0 0:00 4:48 9:36 14:24 19:12 0:00 Time (HH:MM) (a)

2500 Real Data for Power (kW) 2000 Simulation Data for Power (kW)

1500

Power (kW) Power 1000

500

0 0:00 4:48 9:36 14:24 19:12 0:00

Time (HH:MM) (b) Fig. 3-27 24 hours power profile of the substation1 (a) and the substation 2 (b) in system under study interval of the day, which when multiplied with the power and energy profiles of a single train can provide the energy consumption during every 15 minutes of 24 hours (as real data sampled). Two examples of 24 hours power profile of substation 1 and 2 in the system under study are illustrated in Fig. 3-27. As illustrated, the power demand reduces gradually at night and then starts to increase in the early morning. There is a local maximum around 8:30 AM when the express, and local trains run together and the time interval between trains is reduced to provide a fast and reliable service for a large number of passengers who are using the transit system for commutation. After this time, as it is expected the headway between running trains increases and express train service stops. Therefore, power demand decreases and remains at an almost constant value until 3 PM in the afternoon, when the express service starts again. Also, the headway between running train decreases again and power demand increases until it reaches its maximum around 6:30 PM. In this time, the power demand of the substations goes beyond 2 MW. Based on the approach explained earlier in this section, the 24 hours power profile of two substations are created and compared with real data. Those follow the same trend as real data and most of the time those are matched with each other. However, there are some points where they deviate from each other. This is due to the fact that the number of passengers on the trains may differ day by day, which affects the power drawn by the trains. Additionally, there may be a delay in the running time of some of the trains, so it affects the amount of power drawn from the substation in some 15 minutes interval. For example, if some delays happen and as a result of two trains, running in the reverse direction, accelerate at the same time, twice the power of a single train is requested from the substation, which increases the demand during that interval.

4 CASE STUDIES 4.1 Wayside Energy Storage In this section, several case studies are presented to investigate the performance of Wayside Energy Storage for applications such as substation peak demand reduction and maximum recuperation of regenerative braking energy. Substation Peak Demand Reduction In this section, the proposed model is used as a tool to test the impact of the installation of three different technologies, including a battery, a supercapacitor, and a flywheel, on peak demand reduction. A portion of the NYCT as presented in Fig. 3-25, is selected as a case study. ESSs will be installed at substation 2. Fig. 4-1illusterte the power of substation 2, with and without energy storage, when a train leaving a passenger station close to that substation. The purple curve is the train current profile supplied by substations 2 and 3. Since the train starts its journey next to substation 2, most of its current is supplied by substation 2 (solid ). The yellow curve represents the ESS current. As a result of ESS current injection during train acceleration (0 s-32 s), the power of substation two is reduced considerably as presented by the dashed light-green curve. The sizing requirement for achieving 10%, 18%, and 24% peak demand reduction in substation 2, as presented in Fig. 4-2, is presented in Table 4-1. The capital cost analysis for installing each size of ESS is also presented in Table 4-2.

Fig. 4-1 Impact of ESS on substation power

2500 Power without ESS (kW) Power with ESS 10%

2000 Power with ESS 18% Power with ESS 24%

1500

1000 Power (kW) 500

0 0:00 2:24 4:48 7:12 9:36 12:00 14:24 16:48 19:12 21:36 0:00 Time (HH:MM)

Fig. 4-2 The 24 hours power profile of the substation2 with different size of energy Table 4-1 Sizing requirement for peak demand reduction Sizing for 10% Sizing for 18% demand Sizing for 24% Charging/ demand reduction reduction demand reduction

Discharging Rate Energy Power Energy Power Energy Power (kWh) (kW) (kWh) (kW) (kWh) (kW)

1C/1C 1111.6 570 1990 995 2072 1036 Battery

Supercapacitor 1.5 570 2.6 3.3 995 1036 (Capacitance) (62 F) (106 F) (133 F)

Flywheel 3.8 570 6.6 995 7 1036

Table 4-2 Capital cost for different size of ESS Capital Cost ($) Peak Demand Reduction

10 % 18% 24% Type of ESS Battery 1C/1C 1333,914 – 5002,180 2387,872 – 8954,521 2486,680 – 9325,053 Supercapacitor 57,750 – 250,500 100,800 – 437,000 105,250 – 463,900 Flywheel 93,100 – 247,000 162,450 – 431,000 169,400 – 449,400

Maximum Recuperation of regenerative braking energy In this section, the proposed model is used as a tool to test the impact of the installation of three different technologies, including a battery, a supercapacitor, and a flywheel, on peak demand reduction. A portion of the NYCT as presented in Fig. 3-25, is selected as a case study. ESSs will be installed at substation 2. In this case study, a portion of NYCT line 7 in the Borden area is considered. This portion includes three substations namely 50 Ave, Jackson and Queensboro Substations, and five-passenger stations, from Hunters point Ave to 40 St, as presented in Fig. 4- 3. In the first step, we investigated the contribution of substations for supplying a train when starting a journey from Hunter passenger station to Court Sq. the passenger station and then from Court Sq. to Queensboro Plaza. A schematic of the electric rail transit system is presented in Fig. 4-4. The power profiles of the train and the above-mentioned substation during these two cycles are presented in Fig. 4-5. The power at each substation and the percentage of their contributions are presented in table 4-3. Based on Fig.4-5 and Table 4-3, it can be easily concluded that the third substation (Queensboro here) has a very small contribution compared to the other two substations. Therefore, a case study between 50Ave and Jackson Ave substation can neglect the Queensboro substation.

Fig. 4-3 Schematic of NYCT line 7

Substation3 Substation 1 Substation2 A A A B B B C C C

AC AC AC DC DC DC RPW RPE RPW RPE RPW RPE RPW RPE

Passenger passenger Passenger passenger Passenger Station 1 Station 2 Station 3 Station 2 Station 3

RTW RTE RTW RTE RTW RTE RTW RTE Fig. 4-4 Schematic of NYCT line 7 from Hunter passenger station to 40 St.

Fig. 4-5 The power profile of train and 3 substation in Line 7

Table 4-3 Substation Power Contribution Name Peak Power % Contribution Train 3.3*106 w - 50 Ave 1st cycle 2.8*106 w 83% Jackson 1st cycle 4.67*105 w 14% Queensboro1st cycle 1.2 *105 w 3% 50 Ave 2nd cycle 1.56*106 52% Jackson 2nd cycle 1.56*106 52% Queensboro 2nd cycle 2.87 *105 3%

4.1.1.1 Wayside energy storage location In this case study, a suitable location for deploying WESS is investigated. we Assume a train running from Hunter point Ave passenger station to Queensboro passenger station (2 cycles). We Assume that we have an ideal ESS that can capture all the regenerative braking energy produced by train. We placed this ESS in each passenger station to find a suitable point. As mentioned in Chapter 1, when a train injects regenerative braking energy into the third rail, the voltage starts to rise if there is not enough load to capture this energy and the chopper will function to keep the voltage at the terminal of the train below 720. Therefore, the best location is the location that creates a small voltage rise at the terminal voltage of the train. The train’s terminal voltage when the ESS is located at each passenger station is presented in Figs.4-6 to 4-8. As illustrated, when ESS is located in the middle passenger station (at Court Sq.) the rise in the voltage at the terminal of the train is smaller than the rise of the train voltage in the other two locations. Another important point that can be concluded is that the distance between ESS and the decelerating train is one of the limitations in the recuperation of regenerative braking energy. 750 X: 51.38 Y: 732.5

700

650 Train Voltage (V)

600

550 10 20 30 40 50 60 Time (s)

Fig. 4-6 Train terminal voltage when ESS located at Hunter point Ave passenger station

700

X: 35.45 Y: 673.4

650 Train Voltage

600

550 10 20 30 40 50 60 Time (s)

Fig. 4-7 Train terminal voltage when ESS located at Court Sq. passenger station

800

750

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Train Voltage (V) 650

600

550 10 20 30 40 50 60 Time (s)

Fig. 4-8 Train terminal voltage when ESS located at Queensboro passenger station

4.1.1.2 Wayside energy storage size In this case study, different sizes of ESS were installed in the middle passenger station (Court Sq. passenger station in Fig. 4-3 ) and the performance of ESS on capturing regenerative braking energy is investigated. Our main goal is to determine what are the requirements and limitations for ESS to capture maximum regenerative braking energy. A train with the power profile presented in Fig. 4-10 is running from Hunter point Ave passenger station to Court Sq. passenger station. Different size of Li-ion battery is installed in Court Sq. passenger station. The requirement for this study are as follows: • battery current is limited to a maximum of 1C • voltage at the train terminal is limited to a maximum of 720 V An important point in this study is the current contribution of substations during the charging process. Generally, when there is no ESS in the system, the power of substation during train deceleration is almost zero as presented in Fig. 4-5. However, when ESS is added to the system, substations consider ESS as a new load and if ESS requests more current than what is available from the train, the substations will contribute to providing it. Information regarding energy saving for each size is presented in Table 4-4.

Table 4-4 Different size of battery for recuperation of regen braking energy

Size RTrain Chopper Ebattery E50 Ave EJackson ENet 1000 Ah 0.08 35.34 4.9 3.67 26.77 1500 Ah 0.1 44.01 2.11 2.39 39.51 2000 Ah 0.1 44.4 2.16 2.45 39.79 2500 Ah 0.1 44.1 2.13 2.4 39.57 3000 Ah 0.1 58.78 3.93 4.22 50.63

8000

6000

4000

2000 Train Current (A)

0

-2000

-4000 0 10 20 30 40 50 60 Time (s)

Fig. 4-9. Case 1 train current profile 4.1.1.3 Wayside energy storage technology In this section, a similar case study, which was presented in the previous section for a battery, is performed here for flywheel and supercapacitor as well. The results for each technology are presented in Table 4-5 and 4-6 respectively for supercapacitor and flywheel.

Table 4-6 Different size of flywheel for recuperation of regen braking energy

Size RTrain Chopper EFlywheel E50 Ave EJackson ENet 10 unit 0.07 30.03 7.98% 5.67% 16.38 15 unit 0.08 44.37 5.5% 4.85% 34.02 20 unit 0.08 57.95 7.74% 7.59% 42.62 25 unit 0.08 71.22 7.99% 9.45% 53.78

Table 4-5 Different size of supercapacitor for recuperation of regen braking energy

Size RTrain Chopper ESC E50 Ave EJackson ENet 10 module 0.1 16.9 1.3 2.19 13.41 15 module 0.1 23.16 2.13 3 18.03 20 module 0.1 28.25 3.26 4.15 20.84 25 module 0.1 38.10 5.63 6.56 25.91 30 module 0.1 40.86 7.39 7.46 26.10

4.2 Reversible Substation In this section, the proposed reversible substation model is tested for the recuperation of regenerative braking energy. As mentioned in the Modeling chapter, for efficient recuperation of regenerative braking energy, whenever the voltage attempts to rise due to the energy produced by an approaching decelerating train, the inverter has to rapidly inject as much power as needed to the AC grid train. In ideal conditions, it would inject almost all the power that is produced by the decelerating train to the main grid, unless some of the energy is utilized on the third rail (e.g., by a nearby accelerating train). The controller has to monitor the voltage and autonomously yield an appropriate set point for the Id (responsible for active power) to regulate the third rail voltage. In order to test the developed reversible substation model, a portion of the NYCT system (as presented in Fig.4-3) is considered and two cases were simulated. In the first case, A train with the current profile shown in Fig. 4-11, is running from Court sq. passenger station to Queensboro passenger station. Jackson substation, close to Queensboro passenger station, is Assumed to have a reverts path (4 unit of 0.5 MW inverter connected in parallel). In other words, Regenerative braking energy produced by a train approaching the reversible substation, where the inverter is installed. Starting around 33s, the train accelerates producing regenerative braking energy. If this energy is not captured, the voltage will rise leading the train to be electrically disconnected. However, in this case, the reversible substation will attempt to collect this energy by pushing the power back to the grid. The inverter is commanded to regulate the third rail voltage to 650V. Therefore, when the voltage starts to rise as a result of the regenerative braking energy, a mismatch between the measured voltage (VDC_m) and the reference voltage (VDC_Ref) starts to appear. As a result, some direct-axis (related to P) Id_ref starts to appear leading the inverter to send power to the main grid. In this test, since the set point for the quadratic-axis current Iq_ref (i.e., the component of the current controlling Q) is forced to zero, the inverter is operating at unity power factor. Fig. 4-3 shows the active and reactive power values injected into the main grid. It can be observed that the active power varies corresponding to the train current during deceleration. It can also be observed that the reactive power component is zero. Fig. 4-4 shows the AC voltage and current. Fig. 4-5 shows the third rail voltage. It can be seen that the voltage is regulated to its reference value of 650V once the inverter kicks in during the deceleration interval, at around 33 seconds.

8000

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-4000 0 10 20 30 40 50 60 Time (s)

Fig. 4-10. Case 1 train current profile

4

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-0.5 3ph Reactive Power (MVAR) -1 0 10 20 30 40 50 60 Time (s) Fig. 4-11 AC active and reactive 3ph power of the inverter.

Fig. 4-12 Case 1 AC voltage and current.

850

V 800 dc ref V dc mesurment 750

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550

500

450 10 20 30 40 50 60 Time (s) Fig. 4-13 third rail voltage at dc side of Inverter . Fig. 4-7 shows the phase current and voltage. It can be seen that the inverter is capable of maintaining unity power factor operation (i.e., the current and voltage are in phase), by proper decoupling between the d-axis and q-axis currents. This is also evident by looking at Fig. 48, which shows the per-unit values of Id and Iq. Fig. 4-6 shows both the train and inverter power. It can be seen that the inverter is capable of injecting almost all the power produced by the train to the main AC grid. Note that this case study assumes that the AC grid is hospitable to this amount of power and that the inverter is large enough to handle all train power. Also, it is Assume that the train is decelerating next to the passenger station. To see the impact of train location on the recuperation of regenerative braking energy a case study is performed. In this case, the same portion NYCT line 7 mentioned above is considered. Jackson substation is considered to have a reverse path (2 MW inverter) and the train starts running from Hunter point Ave passenger station to 40th St passenger station (4 cycles). The information regarding percentages energy-saving and substation energy contribution during train deceleration in each cycle is presented in Table 4-7. Based on Table 4-7, it can be concluded the distance between the decelerating train and reversible substation can limit the percentage of energy saving. On average, a reversible substation can provide 72.26 % energy saving from 4 cycles of train operation.

50 V (kV) a 40 I (A)*0.25 a 30

20

10

0

-10

-20

-30

-40

-50 44.5 44.51 44.52 44.53 44.54 44.55 44.56 44.57 44.58 44.59 44.6 Time (s) Fig. 4-14 phase current and voltage (showing unity power factor operation).

Fig. 4-15 direct and quadratic axis per-unit currents.

Fig. 4-16 train versus inverter input power. Table 4-7 Different size of flywheel for recuperation of regen braking energy

Size RTrain Chopper Einv E50 Ave EJackson ENet 1st cycle 0.15 85.38% 1.6% 10.19% 73.59% 2nd cycle - 98.01% 1.37% 10.89% 85.74% 3rd cycle 0.07 62.28% 1.98% 10.38% 49.92% 4th cycle - 97.1% 6% 11.28% 79.82%

4.3 Hybrid Reversible Substation and Wayside Energy storage The results of this section represent the case when an inverter provides a reverse path for the train power to flow back to the main AC grid as in the previous case, but with a wayside, ESS is connected to the third rail. The wayside ESS stores the energy from several running trains. An energy management algorithm (presented in chapter 2) determines when and how much energy should be injected into the main AC grid at a given time. The exact type of ESS is not the focus of this task but the goal is to examine the applicability of the model and robustness of the controller. Figs. 4-9 to 4-10 show a case study when a hybrid high-power/high-energy ESS stores the energy accumulated from multiple decelerating trains and then discharges a constant value of 2MW for about 30s. The third rail voltage is kept constant during this process as shown in Fig. 4-11.

8

6

4

2

3ph Active Power 0

-2 5 10 15 20 25 30 Time (s)

1

0.5

0

-0.5 3ph Reactive Power

-1 0 5 10 15 20 25 30 Time (s)

Fig. 4-17 3ph active and reactive power.

Fig. 4-18 3ph voltage and current. 800

750

700

650

600 dc Voltage (V)

550

500

450 5 10 15 20 25 30 Time (s)

Fig. 4-19 Third rail voltage.

Fig. 4-20 Per-unit d-axis and q-axis currents. Several simulation runs were performed to examine the inverter’s ability to provide services (e.g., reactive power support) to the distribution grid. The results of a selected case study are presented in Figs. 4-13 to 4-15. In this case, the inverter is commanded to receive reactive power starting at about 33s (by setting the reference value the quadratic-axis current Iq to a negative value). This emulates smart inverter functions, e.g., as they draw reactive power to reduce the voltage during times with excessive solar energy production. It can be seen that the reactive power Q as well as the q-axis component of the current Iq started to appear, while the active power still follows the train current. This service does not affect the inverter’s ability to regulate the third rail voltage, as seen in Fig. 4-16. Fig. 4-17 shows the phase voltage and current. It can be observed that the phase current, in this case, lags the voltage to enable reactive power to flow from the main grid to the transit system while the active power is being sent back to the main grid in the opposite direction.

Fig. 4-21 3ph active and reactive power.

Fig. 4-22 3ph voltage and current. 800

V dc ref V 750 dc measurment

700

650

600 dc Volatge (V)

550

500

450 10 20 30 40 50 60 Time (s)

Fig. 4-23Third rail voltage.

Fig. 4-24 Per-unit d-axis and q-axis currents.

60 V (kV) a I *0.25 a

40

20

0 Current and Voltage -20

-40

-60 50 50.01 50.02 50.03 50.04 50.05 50.06 50.07 50.08 50.09 50.1 Time (s)

Fig. 4-25 phase current and voltage (showing legging current due to simultaneous active and reactive power exchange with the main grid). A portion of NYCT Line 7 as presented in Fig. 4-3 is considered. The train is running from Hunter point Ave passenger station to Queensboro passenger station (2cycle). Jackson substation (close to Queensboro passenger station) has a reverse path including two units of inverters (0.5MW each). A 1500 Ah battery is located at the middle passenger station (Court Sq.). The goal of this case study is to compare the results of a hybrid technique to the cases where wayside ESS and Reversible substation techniques solely. This comparison is performed for different applications, such as Maximum recuperation of regenerative braking energy, substation peak demand reduction, feeder relief at the distribution grid. The results are presented in Table. In this case study, we also compare the capability to reactive power support, voltage regulation, and participating in demand response. Table 4-8 Different size of flywheel for recuperation of regen braking energy

Application ESS Reversible Hybrid Regen Recuperation 44.1 63.23% 88.3 % Substation Peak Reduction 18% - 18% Feeder relief yes yes yes Reactive power support - - yes Demand response - - yes

4.4 Impact on Distribution Grid In this section, one of Con Edison’s networks, namely the “Borden” network, has been analyzed under several scenarios. The Borden network feeds two rectifier substations, the Jackson & West (Jackson) substation and the 50th AVE & 11th ST (50 AVE) substation as shown in Figure 4-27. More information on Con Edison’s Grid is previously presented in the Modeling chapter. Con Edison’s load flow model for the Borden network was run under several load profiles, representing cases with and without wayside energy storage. The effect on voltage magnitudes and line loading was observed. It was found that capturing regenerative braking energy within the Borden network can result in primary feeder relief to 4, out of 16, primary feeders. The maximum cable loading relief is 2.5%. It was also found that having rectifier substations with wayside energy storage had a minimal impact on the voltage magnitude of both primary and secondary buses.

Fig. 4-26Subway substations under study in this report.

To cases were studied: 1. Base Case. In this case, the status quo of the distribution network is analyzed without any modifications. 2. Hybrid Reversible Substation/WESS In this case, a hybrid Reversible Substation/WESS system is analyzed. A high power/high energy WESS is assumed. The high-power WESS enables capturing regenerative braking energy. This energy can be sent back to the main grid, or accumulated in the high-energy WESS for later use. Two scenarios were analyzed: (a) Scenario I: WESS provides energy saving throughout the day, and completely offsets the substation power (the high-energy storage is discharged) between 1 pm-7 pm and (b) Scenario II: WESS provides energy saving and offsets the substation power throughout the day.

Based on previous work, it is assumed that regenerative braking energy can result in 38-48% energy saving (an average of 43% has been used in this study).

4.4.1.1 Base Case The base scenario represents the case when the load profiles of the two substations are not changed. In this case, the feeder loading, primary voltage, and secondary voltage are shown in Figures 4-28 to 4-30, respectively.

Base Case Feeder Loading

100

80

60

40 Percent Loading

20

0

80 16 60 14 12 40 10 8 20 6 4 0 2 Feeder Number Interval Number (quarter minutes) Fig. 4-27 Line loading of the primary feeders in the base scenario.

Fig. 4-28 Primary buses voltages. Fig. 4-29 Secondary buses voltages.

4.4.1.2 Hybrid Reversible Substation/WESS This scenario represents the case when two WESS are deployed at both 50 AVE and Jackson substations leading to an estimated 43% energy savings. In addition, the energy demand of the subway substations is completely offset (power falls to zero) between 1 pm-7 pm. In this case, the feeder loading is shown in FiguresFeeder Loading 4 with-31 WESS. at 50 AVE and Jackson and zero consumption from 1-7 pm

100

80

60

40 Percent Loading

20

0

80 16 60 14 12 40 10 8 20 6 4 0 2 Feeder Number Interval Number (quarter minutes) Fig. 4-30 Line loading of the primary feeders with WESS at 50 AVE and Jackson, and substations power is zero during 1pm-7pm.

This scenario represents the case when two WESS are deployed at both 50 AVE and Jackson substations leading to an estimated 43% energy savings. In addition, the energy demand of the subway substations is completely offset all day. In this case, the feeder loading is shown in Figures 4-32.

Feeder Loading with WESS at 50 AVE and Jackson and zero consumption all day

100

80

60

40 Percent Loading

20

0

80 16 60 14 12 40 10 8 20 6 4 0 2 Feeder Number Interval Number (quarter minutes) Fig. 4-31 Line loading of the primary feeders with zero substations power all day.

5 ECONOMIC ANALYSIS

In this chapter, the estimated energy and monetary savings associated with installing wayside energy storage at NYCT’s substations are summarized. In the first section, the cost of system installation for each technique, wayside energy storage, and reversible substation is presented. The cost of and hybrid reversible substation and wayside energy storage technique can be calculated based on the installation cost of wayside energy storage and reverse-path techniques. In the next section, the annual monetary saving related to energy and peak demand reduction is presented. The system under study is a portion of NYCT line 7 in Borden area of Queens is considered. The schematic of the system under study is presented in Fig.4-3. It is Assumed that Jackson substation is equipped with the reverse path and the train is running from Hunter point Ave passenger station to 40 St passenger station. 5.1 Wayside energy storage installation cost In this section, the cost of wayside energy storage for two case study is calculated. In the first case, ESS is supposed to reduce the peak of the Jackson substation by 10% and in the second case ESS is designed to provide 20% energy saving at each train cycle. Li-ion Battery, Supercapacitor, and flywheel are considered as ESS technology and they are sized for each application. Peak demand reduction For the peak power demand reduction application, an ESS is required to be installed at the substation location. This ESS should release a specific amount of energy during peak hours, which is typically 30-60 minutes, to achieve the desired amount of peak demand reduction. In the first step, the required power of a train from Jackson substation during one cycle operation is calculated using the dynamic equations of motion and the train parameters as presented in chapter 2. In the second step, using the train timetable schedule, the number of train acceleration near a substation in each 15-minute interval was determined. Then, the 24-hours power profile of a train, in 15-minute intervals, including its value during peak hours were multiplied by 0.9 to achieve a 10% reduction. Then, dividing the power demand of Jackson substation in each 15-minute interval by the number of train acceleration cycles, the power supplied by the substation in each train acceleration was determined. The difference between this power and the power that is calculated in the first step should be provided by the ESS. The required power, energy, discharge current and its duration are presented in Table 5-1. Table 5-1 Peak Demand Reduction Requirements Cases Power Energy Current Duration Case 2 353 kW 1.20 kWh 705 A 12.3 s

For peak demand reduction, an ESS needs to be charged and discharged in each train acceleration and deceleration cycle. During peak time (about 5:25 PM to 5:45 PM), the headway between running trains is very short, about 2-3 minutes. Consequently, the ESS should be charged and discharged around 15-20 times each day for trains running in both directions. Therefore, an ESS cycles about 5475-7300 times a year or around 55000-73000 in ten years. Efficiency is another important factor in the selection of an ESS; It is defined as the total energy released by the ESS over the total energy captured by ESS. The roundtrip efficiency should be above 85 % [25]. Based on Table 5-1, they are sized such that they provide 705A current for the duration of 12.3 seconds (353 kW, 1.2 kWh). Maxwell supercapacitor (K2 series) [31] and VYCON flywheel [32] are used as an ESS. Their characteristics and sizing information are presented in Table5-2. It is assumed that the supercapacitor is connected to the rail system through DC/DC bidirectional converter with 95% efficiency that converts 500 VDC to 650 VDC [33]. It is also assumed that ESS is working between 40-90% of its state of charge. One critical factor in the selection of ESS is the cost. The cost per kW and kWh of the supercapacitor ESS ranges from 100-300 $/kW and 300-2000 $kWh, respectively. Similarly, the cost per kW and kWh of the flywheel ESS ranges from 250-350 $/kW and 1000-5000 $/kW, respectively [23]. The initial cost of ESS is calculated using (27) [34]. CC** PC E (27) =+$/kW $/ kWh The ESS is supposed to provide 353 kW, 1.2 kWh. Using (27) the initial cost of the supercapacitor is about $36000-108000. A similar calculation for the flywheel shows that its initial cost is around $90000-130000. It can be concluded that the supercapacitor cost is smaller than the flywheel. It is important to note that the power and energy used in these calculations are the required output of the ESS for power and energy. ESS may be sized more largely in order to provide such power and energy as an output. In the case of the supercapacitor, since the voltage of a cell is very small (2.5 - 3V), a considerable number of cells should be connected in series to reach some specific voltage level. For instance, in this application, the input of a DC/DC converter, where the ESS installed, is 500 VDC and Maxwell supercapacitor cell has a maximum voltage of 3V. It is also recommended not to use a supercapacitor in their maximum voltage. Here we consider 2.8 VDC for each cell as nominal voltage. Therefore, almost 180 cells are required to create 500 VDC. In addition, the maximum continuous current of cells in 40 0C is limited. Based on the information presented by Maxwell, the maximum continuous current of supercapacitor cells (for a maximum duration of 17 seconds) is 500 A [31]. Therefore, to provide 705 A current, 2 parallel strings are required. In summary, 360 total number of cells are required and the power and energy of each cell are 6kW and 3.04 Wh, respectively. In conclusion, to provide 353 kW and 1.2 kWh as an output, the size of SESS will be 2160 kW and 1.094 kWh. Similarly, for the flywheel ESS, VYCON Company provides 125 kW and 0.52 kWh module. To have an output of 353kW and 1.2 kWh, 3 modules (375 kW and 1.56 kWh) is required to be installed in parallel. Based on this information the initial costs of the ESSs are calculated and presented in Table 5-2. It is also important to mention that there are other factors that affect the cost of ESS such as power conversion system (including auxiliary circuit and equipment like converter and energy management unit.), BPC i.e. the balance of plant cost (the owner’s cost for project engineering and project management, land, grid connection equipment) operation and maintenance (O&M), and replacement cost [35]. The cost of the energy conversion system for supercapacitor is 350 $/kW and for the flywheel, this cost is included in its capital cost. The balance of plant cost is 100 $/kW. Operation and maintenance costs can be classified into fixed and variable O&M costs. Fixed cost includes the cost of annual tax and insurance which is considered 1 $/kW-year for supercapacitor and 5.6 $/kW- year for the flywheel. The variable cost of flywheel includes the service cost for changing oil, air tank filter, and bearing replacement which is considered 0.03 $/kWh. The variable cost of supercapacitor includes the service cost for periodical visual inspection of the cells, interconnections, cables, and fixing the problem if there is any; confirming the DC voltage and current and the other sensors. For the supercapacitor, this cost is considered 0.03 $/kWh [36]. The replacement cost is the cost associated with the life of the ESS. The life of a supercapacitor ends when its capacity goes down to 80% of its initial capacity or when the internal resistance gets doubled. The Supercapacitor is assumed to have a lifespan of 10 years. A recent study shows the test results of different laboratories on supercapacitor life [37]. Based on this study average supercapacitor life is considered as 5 years in this paper. It is also assumed that the energy conversion system is needed to be replaced every 5 years. The lifespan of the flywheel is between 15-20 years, and in this study, it is considered to be 15 years. The cost comparison of supercapacitor ESS vs. flywheel for 10 years of operation is presented in Table 5-3. For the power and energy cost of ESS, the average value presented in the literature has been selected in our calculation. For the supercapacitor, these costs are 200 $/kW and 1150 $/kWh. Similarly, for the flywheel, 300 $/kW and 3000 $/kWh is used. Since the installed supercapacitor has a higher power; therefore its initial cost and the cost and the cost of the energy conversion system are higher (almost 4 times). On the other hand, the supercapacitor life span in small in practice and it needed to be replaced after 5 years while flywheel only has the O&M cost for 10 years. Based on the above, the total cost of the supercapacitor in 10 years is significantly higher than the flywheel. Table 5-2 ESS characteristics for peak demand reduction Supercapacitor Cell C=3000F, Vmax=3, ESRDC=0.27mΩ Configuration 2 string*180 cell in series Max Voltage 500 Stored Energy 3.04 Wh Specific Power 5.9 kW/kg Flywheel Module 125 kW, 750 Vdc Configuration 3 module in parallel Energy Storage 1875 kW-sec Speed 10,000 to 20,000 rpm DC Current 167 Adc Recharge Time 15 sec

Table 5-3 ESS Cost Comparison for peak demand reduction Cost options Supercapacitor ($) Flywheel ($)

Initial 433258.10 117180.00 Energy Conversion System 756000 - Balance of Plant 216000.00 37500.00 Annual O & M 2160.03 2100.04

Replacement (every 5 year) 763738.10 -

Replacement (in 10 year) 1527476.20 - O & M (in 10 years) 21600.3 21000.4 Total cost (in 10 year) 2945334.6 175680.4

Recuperation of regenerative braking energy In this section, ESSs are sized to provide 20% regenerative braking energy recuperation of one cycle of train operation. To provide this service, ESSs are sized in a way to be able to charge with 900A with the duration of the 30s (0.6 MW, 4.8 kWh). Maxwell supercapacitor (K2 series) and VYCON flywheel are used as the ESS technologies. Their sizing information is presented in Table 5-4. The cost comparison of supercapacitor ESS vs. flywheel ESS for this application is presented in Table 5-5. Table 5-4 ESS characteristics for energy recuperation Supercapacitor Cell C=3000F, Vmax=3, ESRDC=0.27mΩ Configuration 4 string*180 cell in series Max Voltage 500 Stored Energy 3.04 Wh Specific Power 5.9 kW/kg Flywheel Module 125 kW, 750 Vdc Configuration 5 module in parallel Energy Storage 1875 kW-sec Speed 10,000 to 20,000 rpm DC Current 167 Adc Recharge Time 15 sec

Table 5-5 ESS cost comparison for energy recuperation Cost options Supercapacitor ($) Flywheel ($) Initial 866518.50 195300 Converter System 1512000.00 - Balance of Plant 432000.00 62500.00 Annual O & M 4320.06 3500.078 Replacement (5 years) 1527576.00 - Replacement (10 year) 3055152.00 - Maintenance (10 years) 462763.20 35000.78 Total cost (in 10 year) 6328433.5 292800.78

5.2 Reversible substation installation cost In this section, the cost of installation for 1 MW reversible substation is presented. As described in Chapter 2 (Modeling Reversible Substation), A reverse path consist of the following components : • Inverter unit • Transformer • Filter

To find the total cost of the reversible substation, the cost of the above-mentioned components are calculated and added. The cost of each component and the total cost of a reversible substation is presented in Table 5-6. The 1MW reverse-path includes two 0.5 MW inverters, two 0.5 MW filters, and two sets of the transformer.

Table 5-6 Peak Demand Reduction Requirements component Power rating Cost Inverter 1MW $258,039 Filter 0.5 MW $15,000 Transformer 0.5 MW $ 96,000 Total 1MW $480,039

5.3 Annual monetary saving In this section, the estimated energy and monetary savings associated with installing wayside energy storage at the NYC transit system are investigated. A portion of line 7 in the Borden area is considered for this study. The high-resolution substation power profiles of the Jackson substation were created using train timetables and, after being averaged over 15-minute intervals, verified against real interval metering data. Figs.5-1 and 5-2, show a sample of the interval metering data for Jackson substation for 20 random summer days.

2500

2000

1500

1000 Power (W)

500

0 0 5 10 15 20 25 Time (Hours) Fig. 5-1 the Interval metering data for 20 days. 2500

2000

1500

1000 Power (W)

500 July 10, 2018 0 0 5 10 15 20 25 Time (Hours) Fig. 5-2 Interval metering data for a sample summer day

In order to consider a natural exchange power between trains, a probability curve based on real on and off studies done by Con Edison is developed. This curve, represented in Fig.5-3, shows the probability that trains meet at passenger stations. Fig.5-4 shows the impact of train natural exchange on the Jackson substation power profile.

1

0.8

0.6

0.4 Probability

0.2

0 0 5 10 15 20 25 Time (Hours) Fig. 5-3 Probability of trains direct energy exchange

106 2.5

2

1.5

1 Power (W)

0.5 Regen ON Regen OFF 0 0 5 10 15 20 25 Time (Hours) Fig. 5-4 Jackson substation interval data with and without natural exchange of regenerative braking energy. To perform a cost analysis, a case study that ESS create 40 % energy saving in each train acceleration cycle is considered. The power profile of Jackson substation with and without this ESS is presented in Fig.5-5. Fig.5-6 compare the energy savings for Jackson substations in the cases of: (1) with natural power exchange among trains and without ESS; (2) with both ESS and natural power exchange among train; (3) without ESS and natural exchange. Each data point represents the total energy saving achieved by the end of day 1, day 2,..., day 365. The weekly dips in the figure correspond to weekends. The horizontal lines representing constant values repeating for consecutive days (e.g., between day ~60 to day ~80 in the Jackson & West curve) are due to missing interval metering data, which were replaced by the average daily energy within the season not to affect the energy totals. The curves also show seasonal variations as they tend to peak during March and October. Energy charges were based on actual New York Independent System Operator (NYISO) real- time Locational Based Marginal Prices (LBMP) for New York City (NYC). Figure 5-7 shows the monthly averaged NYC real-time LBMP. Demand delivery charges were based on Power Authority of the State of New York (PASNY) 12 - Rate I - High Tension Service of $19.14/kW per month of the maximum demand. The coincident peak is assumed to occur between 08:00am and 08:30am from November through May, and between 06:00pm and 06:30pm for the rest of the year. Summery energy saving calculation for Jackson substation is presented in Fig. 5-8 and Table 5-7.

106 2.5 Original 2 Energy Saving

1.5

1 Power (W)

0.5

0 0 5 10 15 20 25 Time (Hours) Fig. 5-5 Interval data with and without wayside energy storage.

104 2018 - Jackson & West 8 With Direct Exchange and With ESS 7 With Direct Exchange and Without ESS Without Direct Exchange and Without ESS 6

5

4

3 Energy (kWh)

2

1

0 50 100 150 200 250 300 350 Day Fig. 5-6 Energy savings with and without direct exchange and ESS at Jackson Substation

120 2018 100 2017

80

60

40 LBMP ($/MWh)

20

0 1 2 3 4 5 6 7 8 9 10 11 12 Month Fig. 5-7 NYC Locational based Marginal Price for 2017 and 2018.

104 Jackson & West (2018) 15

10 Saving ($) 5

0 1 2 3 4 5 6 7 8 9 10 11 12 Month Fig. 5-8 Energy saving at each subway substation Table 5-7 Summary of the savings at the Jackson & West substation Savings due to Peak Savings due to Energy Total Savings ($) $ Demand Reduction ($) Reduction ($) Lower Limit Upper Limit Lower Limit Upper Limit Lower Limit Upper Limit Jan. 35148.76 44398.43 63682.99 80441.68 98831.7 124840.11 Feb. 27838.32 35164.19 15152.97 19140.59 42991.3 54304.78 March 21392.37 27021.94 19379.86 24479.82 40772.2 51501.761 April 30561.4 38603.88 20461.61 25846.24 51023 64450.12 May 30393.83 38392.21 17669.04 22318.79 48062.9 60710.997 June 31378.33 39635.79 17205.74 21733.57 48584.1 61369.353 July 31755.37 40112.05 20195.49 25510.09 51950.9 65622.143 Aug. 32907.45 41567.3 25461.26 32161.6 58368.7 73728.898 Sept. 30833.71 38947.85 21414.11 27049.4 52247.8 65997.247 Oct. 32530.41 41091.04 24331.55 30734.58 56862 71825.623 Nov. 25932.16 32756.41 20059.94 25338.88 45992.1 58095.287 Dec. 28592.4 36116.72 18538.22 23416.7 47130.6 59533.418 Per Year 359264.5 453807.8 283552.8 358171.9 642817 811979.73

6 CONCLUSION

Some of the major findings of this study include: § A single NYCT train running on the 7-Line draws about 15-20 kWh during acceleration. The average train peak demand is about 4 MW. § Under ideal conditions, occurring during short time intervals in the day, NYCT trains can on average reproduce ~50% of acceleration energy during deceleration. “Ideal conditions” refer to the existence of a coincident load near the decelerating train (i.e. a high auxiliary load or an accelerating train), which can receive the back-injected regenerative energy before overvoltage takes place. Chances increase during peak periods. § Because “ideal conditions” are infrequent, existing regenerative braking configurations result in only ~8% reduction in the energy consumption and peak demand of the substations supplying the NYCT 7-Line over a 24-hour timeframe, since it is not actively managed. § Demand/energy savings can be increased to ~43% with proper design and deployment of wayside ESS, since ideal conditions would be guaranteed for longer durations of the day. § Since regenerative energy needs to be captured within only ~20 seconds, a high-power fast- response storage technology is required. Simulations indicate flywheels and super-capacitors (SC) are viable candidates considering capital costs for this application (excluding installation and maintenance costs).

APPENDIX A The torque and the flux of induction motor are related to each other based on (26):

3 LM T = p 2 y ry s sindy (26) 2 LsLr - LM

Where, LM, Lr and Ls are the magnetizing, rotor and stator inductances, respectively. ψr and ψs are rotor and stator flux, and δψ is the torque angle. Stator and rotor flux rotate with a linear speed in an approximately a circular path. A vector diagram of stator and rotor flux movement is presented in Fig. 59. In constant magnitude flux, if the speed of stator flux increases, the angle δψ is increased and the torque value will reduce and if the speed of stator flux decreases or goes to zero, the angle δψ is decreased and the torque will increase. On the other hand, the stator flux is a state variable that can be controlled by the stator voltage based on (27). dy V =V = 2pf s (27) s inv(n) dt Inverter output voltage space vector Vinv (n) can be described with (28) and (29).

ì 2 j(n-1)p ï( )v e 3 n =1,2,3,4,5,6 V = dc inv(n) í 3 (28) îï 0 0,7

Vdc (29) 2 vdc = Vsrated Where, Vsrated is the rms value of phase angle. For n=1-6, voltage vector called active and the rest are called zero. Active vectors can move in forward and backward direction. Applying the active voltage vector to the inverter switches, the speed of the flux increased based on (27) and consequently δψ increased so that torque reduced. By applying zero vectors, flux movement will be zero and since the rotor flux continues its movement, δψ will reduce and therefore torque will increase. As illustrated in Fig. 6, the torque and stator flux are calculated from dq components of voltage and current presented in (30) to (34). Dq components of voltage and current are calculated based on park transformation presented in (35) [10]. 3P T = (y s is -y s is ) (30) e 4 ds qs qs ds

s 2 s 2 yˆs = y ds +y qs (31)

s -1 y qs qe = sin (32) yˆs y s = (v - R i )dt (33) ds ò ds ss d y s = (v - R i )dt (34) qs ò q ss q é 2p 2p ùéF ù éF ù Cosq Cos(q - ) Cos(q + ) a d 2 ê úê ú ê ú = ê 3 3 úêF ú (35) êF ú 3 2p 2p b ë q û ê- Sinq - Sin(q - ) - Sin(q + )úêF ú ëê 3 3 ûúëê c ûú The switching table for of inverter is presented in Table 16. APPENDIX B Nickel- Cadmium and Nickel-Metal-Hydride batteries equations are presented in (36) and (37). During charging mode: Q Q E = E - (K c i) - (K) c Q(t) batt(int) 0 Q - Q(t) Q - Q(t) (36) c c Exp(s) + Laplace-1 ( .0) mode(s) During discharging mode: Q Q E = E - (K c i) - (K) c Q(t) ba tt (int) 0 Q(t) + 0.1Q Q - Q(t) (37) c c Exp(s) 1 + Laplace-1( . ) mode(s) s

Where E0 is the constant voltage, K is the Polarization constant, Qc is the maximum capacity of battery, i is the low frequency current dynamic, Exp(s) exponential zone dynamic of voltage, mode(s) is the mode of charging (mode(s)=1) and discharging (mode(s)=0) of the battery. Internal voltage of supercapacitor is also described by (38). N Q(t)d E = s + SC(int) N N ee A (38) p e 0 i 2N N RT Q(t) e s sinh -1 ( ) F N N 2 A 8RTee c p e i 0

Where, Ns, Np are number of series and parallel capacitors, Ne is the number of electrodes layers, ε and ε0 are permittivity of material and air, respectively. R and T are ideal gas constant and operating temperature, respectively and Ai is the interfacial area between electrodes and electrolyte.

ωaf TABLE 16 q SWITCHING TABLE ωab ψ T S1 S2 S3 S4 S5 S6 ψs 1 1 V2 V3 V4 V5 V6 V1 0 V V V V V V ωr 0 7 0 7 0 7 δψ -1 V6 V1 V2 V3 V4 V5 -1 1 V3 V4 V5 V6 V1 V2 ψr d 0 V V V V V V 7 0 7 0 7 0 Fig. 59. Stator and rotor flux rotation -1 V5 V6 V1 V2 V3 V4

TABLE 16 SWITCHING TABLE

Fig. 59. Stator and rotor flux rotation

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