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Energy Storage Technologies in MVDC Microgrids
8 ENERGY STORAGE TECHNOLOGIES IN MVDC MICROGRIDS Diaa-Eldin A. Mansour Faculty of Engineering, Tanta University, Tanta, Egypt
1
Classification of Energy Storage Technologies
Energy storage technologies (ESTs) have diverse classifications either based on their form of storage or based on their projected functions. According to form of storage, there are many existing forms that have been described in detail in the literature; however, this chapter will focus on ESTs applied for microgrids. ESTs can be classified into electrochemical storage as in batteries, electrical storage as in supercapacitors (SCs), magnetic storage as in superconducting magnetic energy storage (SMES), kinetic storage as in flywheels, and chemical storage as in hydrogen. According to the projected functions of ESTs, they can be classified based on their energy density, their power density, or based on their response time. A major distinction in the application of ESTs with microgrids depends on these features.
2 2.1
Battery Energy Storage Systems Comparison of Different Battery Types
Battery energy storage systems (BESSs) are widely used in the energy market. A BESS is an electrochemical device that can convert electrical energy to chemical energy or vice versa depending on its operational mode—either charging or discharging. The basic principle of a BESS is depicted in Fig. 1. A BESS is composed Medium-Voltage Direct Current Grids. https://doi.org/10.1016/B978-0-12-814560-9.00010-0 # 2019 Elsevier Inc. All rights reserved.
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Fig. 1 The basic principle of a battery energy storage system.
of a battery bank, power-conditioning system, and control scheme. The battery bank comprises a number of batteries, with each battery having multiple cells connected in parallel and/or series to supply the desired output voltage and capacity. The cell itself consists of two electrodes in an electrolyte, where electrons are transferred between electrodes and through the external circuit. The first electrode is negative and acts as an anode, while the second one is positive and acts as a cathode. There are different battery types with different applications depending on electrode form and electrolyte material. The most important battery types used for electrical grids are lead–acid (LA) batteries, nickel-cadmium (Ni-Cd) batteries, lithium-ion (Li-ion) batteries, and flow batteries. LA batteries were the first rechargeable batteries used for commercial applications. However, they had the disadvantages of having low specific energy and power, the need for periodic maintenance, and limited charge/discharge cycles. Ni-Cd batteries offer a competitive substitution to LA batteries due to their higher energy density, large number of charge/discharge cycles, and lower maintenance requirements. In Ni-Cd batteries, nickel hydroxide is used as the positive electrode and cadmium hydroxide is used as the negative one. In addition to the toxicity of nickel and cadmium metals, Ni-Cd batteries have a memory effect that necessitates complete charging and discharging before starting a new cycle. This makes them unsuitable for microgrids that require moderate charging and discharging cycles depending on the condition of energy mismatch. Li-ion batteries were widely used for mobile phones and electronic devices before being adopted as potential energy storage systems for large applications. The motivation behind using Li-ion batteries in energy applications is attributed to several factors: they have high energy and power densities compared to other battery types; their open-circuit voltage is high, reaching
Chapter 8 ENERGY STORAGE TECHNOLOGIES IN MVDC MICROGRIDS
Anolyte reservoir
Flow cell
External circuit
Catholyte reservoir
Ion selective membrane
Fig. 2 The basic operational principle of flow batteries for energy storage.
up to 4 V per cell; and they offer rapid charging/discharging, a low self-discharging rate, and a long lifetime of up to 3000 cycles. Recently, flow batteries were developed as a new technology for energy storage. Their operation is based on a reversible chemical reaction that occurs between two aqueous electrolytes supplied from two separated tanks as shown in Fig. 2. The energy capacity of flow batteries can be easily managed through changing the volume of stored electrolytes. The use of flow batteries with microgrids and renewable energy sources is still limited due to their high cost.
2.2
Battery Modeling and Characteristics
Because of the nonlinear characteristics of batteries, it is not appropriate to model them as a constant voltage source. Therefore, there are several battery models that have been developed in the literature. These models include the Thevenin battery model, the impedance-based battery model, the runtime-based battery model, and the combined model. The combined model is the most widely adopted model for investigating battery characteristics. According to the combined model, the cell dynamic equivalent circuit is structured according to Fig. 3 [1]. The equivalent circuit consists of two main parts. The first part represents the voltage-current characteristics, containing a series resistor Rser and two RC parallel circuits indicated by RTS, CTS, RTL, and CTL. The series resistor Rser represents the instantaneous voltage drop, while the RC parallel network elements RTS and CTS
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Rser
Vsoc
RTS
RTL
Rsd + –
Ccap
Voc
CTS
CTL
Ibat
Fig. 3 The equivalent circuit to a battery cell model.
represent the step response in the short time range. Elements RTL and CTL represent the step response in the long time range. The second part of the equivalent circuit represents battery lifetime. This part contains the cell’s self-discharge resistance Rsd in addition to a capacitor Ccap. The self-discharge resistance, which is affected by cell temperature, represents the internal energy loss of the cell when the battery is stored for a long time and also affects the flow rate. On the other hand, the capacitor represents the capacity of the cell in ampere hours (Ah). The two parts of the equivalent circuit are linked through the battery charge/discharge current Ibat which flows through the first part and is considered a current source for the second part of the equivalent circuit. This equivalent circuit represents the nonlinear relationship between the open-circuit voltage (Voc) and the state of charge (SOC). The following equations are used to define the elements comprising the cell equivalent circuit, as well as the value of the open-circuit voltage (Voc) in terms of the battery’s SOC: VOC ðSOCÞ ¼ 1:031 e 35SOC + 3:685 + 0:2156 SOC 0:1178 SOC2 + 0:3201 SOC3 (1) Rser ðSOCÞ ¼ 0:1562 e 24:37SOC + 0:07446
(2)
RTS ðSOCÞ ¼ 0:3208 e 29:14SOC + 0:04669
(3)
CTS ðSOCÞ ¼ 752:9 e
13:51SOC
+ 703:6
(4)
RTL ðSOCÞ ¼ 6:603 e 155:2SOC + 0:04984
(5)
CTL ðSOCÞ ¼ 6056 e 27:12SOC + 4475
(6)
In addition, the cell capacity Ccap is given as follows: Ccap ¼ 3600 Capacity f1 ðCycleÞ f2 ðTempÞ
(7)
Chapter 8 ENERGY STORAGE TECHNOLOGIES IN MVDC MICROGRIDS
5.0 Cell current Cell voltage
Current (A)
2.5
4.5
2.0
4.0
1.5
3.5
1.0
3.0
0.5
2.5
0.0
0
20
40
60
80
Voltage (V)
3.0
2.0 100
State of charge (%)
Fig. 4 The voltage and current characteristics of a Li-ion battery cell.
The factors f1 and f2 represent the cycle number and temperature, respectively, which affect battery lifetime. On the other hand, Rsd is a function of SOC, temperature, and cycle number. Because of the low self-discharge feature of Li-ion batteries, self-discharge can be ignored or represented as a large resistor, which represents the typical case used for modeling. The voltage characteristic of a Li-ion battery cell with a 4.1-V rated voltage is shown against the SOC in Fig. 4. This characteristic is typical. The initial voltage of the cell is 3.0 V when the battery is dead with a zero SOC. When the charging process starts, the voltage increases quickly to 3.7 V during the initial 15% SOC. With an increasing SOC, the voltage continues to increase, but at slower rate until the SOC reaches 100%, corresponding to 4.1 V. With respect to charging current, it increases from 0 A to a maximum value of 2.6 A at 15% SOC, before decreasing gradually to 0 A at 100% SOC.
2.3
Battery Applications With DC Microgrids
Fig. 5 shows a battery that has been interfaced with a DC microgrid via a bidirectional converter. A BESS has two main functions within a DC microgrid. The first function is the energy management of the available generation and the load demand; the second function is the stabilization of DC bus voltage, especially for DC microgrids in island mode. There are several modes that determine the operation of a BESS in DC microgrids. These modes are determined by grid connection status, SOC, available generation, and load requirements [2–4]. They are described in the following text.
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L S1 Battery model
194
C
S2
g2
g1
Voltage control
Vref
Vdc Coupling point
Fig. 5 A battery interfaced with a DC microgrid.
Mode 1: operation under AC grid connection. In this case, any excess or lack of power experienced by the DC microgrid is compensated by the grid, through the proper control of a grid-voltage source converter. Renewable energy sources are then operated at their maximum power point tracking and a BESS can be charged or discharged flexibly depending on operator requirements. Mode 2: operation under AC grid disturbance. In this case, the grid converter becomes incapable of maintaining a constant DC bus voltage. So, a BESS control operates in voltage-stabilization mode by balancing the power within the DC microgrid, provided the available generation lies within the maximum power range. Otherwise, the DC bus voltage will fall, necessitating load shedding. Mode 3: islanding operation. This mode is similar to Mode 2, where a BESS stabilizes the DC bus voltage and compensates for the power mismatch. Here, the SOC of the BESS plays an important role in determining the appropriate operation. If the required power exceeds the rating of the BESS, or the required energy exceeds the remaining SOC of the battery, then load shedding becomes necessary to maintain a constant DC voltage. To the contrary, if the battery is fully charged or the generating power exceeds the rating of the BESS, then an overvoltage can occur. However, this can be mitigated for a photovoltaic (PV) system by changing from maximum power point tracking (MPPT) control to droop control, and for the case of wind energy, by changing from MPPT control to pitch angle control.
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3 3.1
Supercapacitor Energy Storage Systems Basic Principles
SCs store energy in the form of electrostatic charges between two conductive electrodes, separated by a dielectric material. The electrodes in SCs are porous. The energy stored in an SC (Esc) is given by the following equation: 1 Esc ¼ CV 2 2
(8)
where C is the capacitance and V is the voltage between terminals. The capacitance in turn is proportional to the electrode area. So, using porous electrodes provides a large specific area with a subsequent high energy density. This is the main difference between SCs and conventional capacitors. In spite of the very high charge density stored on the electrodes of SCs, they have low cell voltages, in the order of 3 V. Therefore, to reach the desired capacity, multiple series and parallel cells are connected. SCs can be classified either depending on the design of the electrodes or the electrode material. For the design of the electrodes, SCs can be symmetrical, if negative and positive electrodes have the same material, or unsymmetrical, if different materials are used for the electrodes. Regarding electrode material, it can be activated carbon, a metal oxide, or an electronically conducting polymer. Activated carbon is the most common material used commercially for SC electrodes, as it possesses high capacity and low cost.
3.2
Supercapacitor Modeling and Characteristics
As practically observed, an SC has nonlinear characteristics due to its internal construction. Accordingly, its modeling is different to that of conventional capacitors. The stored charges in SCs form what is called an electrical double layer between the solid electrodes and electrolyte. So, the extraction of charge in SCs passes through different processes, each having different time constants. To model this behavior accurately, a three-branch SC model, depicted in Fig. 6, is proposed [5]. The first branch includes a voltage-dependent capacitor to simulate nonlinear behavior, while the other branches model the long-term charging behavior that depends on the distribution of charge along the electrodes.
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DC
i1
+ –
C1
i2
C2
i3
Vo (t)
C3
Fig. 6 A three-branch supercapacitor model.
3.3
Supercapacitor Applications With DC Microgrids
SCs are usually used with a DC microgrid for smoothing output power and mitigating fluctuations [6, 7], due to their large power densities. However, SCs cannot contribute to energy management due to their small energy densities. To achieve their required functions, SCs are operated either using a current-mode controller or voltage-mode controller [8]. The current-mode controller is based on measuring the total power in the system either supplied from generation or delivered to the load, and then, filtering this power using a high-pass filter to extract the high-frequency component that acts as the reference output power for the current-mode controller of the SC. This scheme necessitates the accurate measurement of the different powers that are naturally distributed. For the voltage-mode controller, the voltage of the DC bus itself is used as an indication of power fluctuation. So, the high-frequency component of this voltage is used as a reference signal for the voltage-mode controller of the SC. Since the size and cost of SCs increases when used to supply low-frequency or large magnitude variations, they are usually used in combination with batteries, forming what is called a hybrid energy storage system, achieving both functions of mitigating fluctuations and energy management. In [9], the SC operation was managed with battery based on the magnitude of fluctuations. For small-scale fluctuations, the SC operates through fast charging and discharging to balance the power on the DC bus. The changes in SC voltage in this case will be small. For large-scale fluctuations, the changes in SC voltage will be high, either as a voltage rise or as a voltage drop. So, the battery operates to compensate the energy required by the SC. In additional research [10], the operation between the SC and battery was managed,
Chapter 8 ENERGY STORAGE TECHNOLOGIES IN MVDC MICROGRIDS
giving consideration to the frequency component of generation/ load variations. In this case, high-frequency components and low-frequency components can exist individually or in combination. The energy management strategy was built based on the frequency component so that high-frequency components were allocated to the SC and low-frequency components were allocated to the battery. Hybrid energy storage was also considered with a PV/load DC microgrid [11], in order to benefit from the fast charging/discharging of the SC to alleviate the impact of sudden changes in the grid—either originating from the load side or the PV side.
4 4.1
Superconducting Magnetic Energy Storage Basic Principles
A SMES unit consists of two main parts, in addition to a power conditioning system. The first part of a SMES unit is the superconducting coil, which is the heart of the system. It stores energy in the form of a magnetic field generated by a circulating DC current. The maximum stored energy is determined by two factors. The first factor is the size and geometry of the coil, which determines the inductance of the coil—the larger the coil inductance, the greater the stored energy. The second factor is linked to the characteristics of the conductor, which determine the maximum carrying current. Superconductors carry substantial currents exhibiting high magnetic fields. The second part of a SMES unit is the refrigeration system. A SMES coil must be maintained at a temperature sufficiently low to maintain a superconducting state in the coil. Reaching and keeping the superconducting temperature is accomplished by a special cryogenic refrigerator. There are several types of superconducting materials used for a SMES unit, permitting their classification as high-temperature superconductors and low-temperature superconductors. High-temperature superconductors are cooled at 77 K using liquid nitrogen, while low-temperature superconductors are generally cooled at 4.2 K using liquid helium. Since a SMES unit stores energy in the form of a magnetic field, large quantities of power can be stored over short time periods with high efficiency. The inductive stored energy ESMES in a SMES coil is expressed as [12, 13]: 1 2 ESMES ¼ L ISMES 2
(9)
where L is the superconducting coil inductance and ISMES is the SMES maximum current.
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4.2
Superconducting Magnetic Energy Storage Modeling and Characteristics
A model of a SMES unit was developed using a coil with a DC chopper with a smoothing capacitor on its output (Fig. 7). The SMES coil itself was modeled using several segments, as shown in Fig. 8 [14], where each segment represented a single coil. SMES coils can be wound as a solenoid structure, toroidal structure, or pancake structure. For small-scale units, the pancake SMES structure is preferred [15]. However, for large-scale units, solenoid and toroidal structures are usually used [16]. The toroidal structure has a reduced wire cost compared to the other structures. Each segment of a SMES coil is composed of a series inductance and resistance, as well as a shunt capacitance to ground. The inductance is measured in Henry, the resistance in ohms, and the capacitance in microfarad. The resistance Rt accounts for the eddy current losses in the coil. The required inductance is divided
Idc D1
S1
Vdc SMES coil S2
D2
Fig. 7 Model of a superconducting magnetic energy storage unit.
Lt
Rt
Lt
Ctt
1/2Ctg
Rt
Lt
Ctt
Ctg
Rt Ctt
Ctg
Ctg
1/2Ctg
Fig. 8 Model of a superconducting magnetic energy storage coil.
Chapter 8 ENERGY STORAGE TECHNOLOGIES IN MVDC MICROGRIDS
equally among the different segments of a SMES coil and is represented by Lt. The interwinding capacitances between coils are represented by Ctt and the coil turns to ground capacitance is represented by Ctg. A SMES coil is enclosed in a closed container and is grounded by the material that encloses it.
4.3
Superconducting Magnetic Energy Storage Applications With DC Microgrids
By controlling the main switches S1 and S2 of a two-quadrant DC-DC chopper, a SMES unit can be operated in three different modes. The first mode is the charging mode, where SMES stores energy from the grid to the coil. In the case when both switches are “on” and the charging current flows through them, as shown in Fig. 9A. When one of the switches is “on” and the other “off” SMES is said to be in freewheeling mode, as shown in Fig. 9B. This mode causes SMES coil terminals to be shorted and this keeps the current circulating in the coil without any significant loss due to the use of superconducting material for the coil with a very low ohmic resistance for the switch and diode. This mode can be used when SMES is charged, and there is a need to keep its SOC for a certain period before discharging. The third mode is the discharging mode, in which the coil will inject stored energy back to the system. To operate in this mode, both switches need to be “off” to force a route for SMES current to flow back into the system through diodes, as shown Fig. 9C. SMES is used with microgrids in the same way that an SC is used, where it has fast charging/discharging and a large power density. However, SMES has a higher energy density than an SC. Therefore, it is expected that SMES will play a part in the energy storage applications of the future, especially with the continuous downscaling of superconducting material costs. Several applications of SMES with microgrids are highlighted here. First, in the case of islanding operations, either due to tripping of tie-line connections with the grid or an occurring fault on the grid, SMES compensates quickly for the sudden power loss preventing a large deviation in frequency and enhancing the dynamic performance of the system [17]. A second application is linked to its ability to smooth power fluctuations [18], especially from wind turbine generators that are inherently operated under variable wind speeds. SMES can also be used with batteries in a hybrid platform to alleviate the impact of sudden power changes over battery lifetime [19].
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D1
S1
SMES coil S2
D2
(A)
D1
S1
SMES coil S2
D2
D1
S1
(B)
SMES coil S2
D2
(C) Fig. 9 Model of a superconducting magnetic energy storage unit. (A) Charging mode. (B) Freewheeling mode. (C) Discharging mode.
Also, SMES effectively compensates for sudden changes that originate from pulsed loads in a DC microgrid, as shown in Fig. 10, that presents the characteristics of a DC microgrid composed of a diesel generator, a pulsed load, and a SMES/battery hybrid energy storage system. Here, the load changes from 7 to 11MW, pulsing every 3.0 s. All the voltage levels and power ratings were adjusted to match the values given in [20]. Without using any storage system, the system undergoes sudden voltage dips and swells directly after each pulsed increase and decrease in load, respectively. In addition, the DC bus voltage remains below the nominal voltage during pulsed load operation. All these voltage variations cannot be compensated by the diesel generator due to its large ramp rate. Using only the battery, the voltage dips and swells
Chapter 8 ENERGY STORAGE TECHNOLOGIES IN MVDC MICROGRIDS
Load (MW)
12 10 8 6
DC voltage (p.u.)
4 2.5 Without energy storage With battery only With SMES/battery
2.0 1.5 1.0 0.5
SMES current (A)
Battery current (A)
0.0 800 600 400 200 0 400 300 200 100 0
0
2
4
6
8
10
12
Time (s) Fig. 10 Superconducting magnetic energy storage/battery hybrid energy storage system operating under a pulsed load.
decrease in magnitude, but still show slight values due to the battery’s slow response. Using SMES, the DC bus voltage remains constant during the pulsed load operation. The SMES current was 300 A at the instant of the pulsed load operation, the current then decreased gradually enabling the battery to respond and discharge to compensate the pulsed load change. During transition times, both SMES and battery shared the load requirements. After SMES was discharged, the battery completely supplied the load requirements.
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5 Other Energy Storage Technologies There are a few other energy storage technologies that have been used with DC microgrids. Particularly, flywheel energy storage and hydrogen storage have been used in a limited range. This section summarizes the applications of these two technologies with DC microgrids. For hydrogen storage, surplus energy is used to operate an electrolyzer, to produce hydrogen. The produced hydrogen is then stored as a pressurized gas in cylinders, or as a liquid in cryogenic tanks. When this energy is needed, the stored hydrogen is used to produce energy through either a combustion engine or a fuel cell [21]. The latter is more efficient. The scheme used for hydrogen storage with a DC microgrid is shown in Fig. 11 [22]. The operation of a hydrogen storage system follows three different operating modes, similar to other energy storage technologies. The first mode is charging mode during which the electrolyzer is switched on when there is an excess energy and the existing battery has attained its maximum SOC. The second mode is discharging mode, where the electrolyzer is switched off and the fuel cell is turned on. This mode is operated when there is a lack of energy supplied from renewable energy sources and the battery. The last mode is dead-band mode, in which neither the electrolyzer nor fuel cell is operated—where battery usage is preferred to avoid frequent electrolyzer and fuel cell on-off cycles. These frequent on-off cycles can degrade the performance and lifetime of a hydrogen storage system [23]. Hydrogen storage has high energy density, but low power density. Therefore, it can be used as an energy balancer in microgrids, in a similar manner to batteries. With a DC microgrid composed of a PV array, a battery, and a load [22], a hydrogen storage system can
Fig. 11 A hydrogen storage scheme with a DC microgrid.
Chapter 8 ENERGY STORAGE TECHNOLOGIES IN MVDC MICROGRIDS
successfully absorb excess energy during sunny periods and keep a stable power supply to the load during cloudy periods. Regarding a flywheel energy storage system (FESS), the energy is stored in kinetic form using a spinning rotating disk. In addition to the rotating disk, the other components of a FESS include bearings, electrical machinery, and a power converter interface [24]. The rotating disk is usually made of composite material in order to achieve high-speed operation while maintaining low weight. This reflects on the energy stored in the flywheel Ef, and can be expressed as follows: 1 Ef ¼ j ω2 2
(10)
where j is the moment of inertia and ω is the angular velocity. Bearing systems can be mechanical, magnetic, or superconducting. The latter two types have low friction, small losses, and high operating speeds. The electrical machinery can be an induction machine, a permanent magnet synchronous machine, or a switched reluctance machine. They can be operated into two modes, generating mode and motoring mode, depending on the energy management needs from the FESS. A schematic diagram of a FESS interfaced with a DC microgrid is shown in Fig. 12. The power converter interface is a three-phase voltage source converter operating in inverting mode or rectifying mode in order to enable an energy exchange between the FESS and the microgrid. The control scheme utilizes the DC bus voltage as a control signal. In addition, the rotating disk speed and electrical machine currents are used as inputs to the control scheme DC bus
S1
S3
S5
S2
S4
S6
Machine
w
Vdc
Iabc
Control scheme
Fig. 12 Schematic diagram of a flywheel energy storage system interfaced with a DC microgrid.
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in order to keep stored energy within its maximum and minimum thresholds and to set priority for all energy storage units connected to the DC bus. A FESS has multiple applications with DC microgrids, either as a primary energy storage unit or as a backup. It operates in three modes: charging, discharging, and standby. During charging mode, the machine operates in motoring mode resulting in an acceleration of the rotating disk to higher speeds, absorbing energy from the grid. Once the rotating disk speed attains its maximum threshold, the FESS is isolated from the system and operates in standby mode, by keeping the rotating disk speed constant. During discharging mode the machine operates in generating mode by decelerating the rotating disk and injecting power into the grid.
6 Comparison of Energy Storage Technologies The differences between the ESTs mentioned in this chapter mean they have different applications in terms of DC microgrids. These differences can be summarized in terms of power and energy densities, response times, efficiencies, lifetimes, and costs. Fig. 13 summarizes the energy and power density profiles for common ESTs [25–27]. SCs, SMES, and FESSs have higher power densities, while batteries and hydrogen storage have higher energy densities. So, batteries and hydrogen storage can be used for energy management and the smoothing of low-frequency variations. On the other hand, SCs, SMES, and FESSs can be used for
Specific power (W/kg)
10
10
10
10
10
5
Supercapacitor SMES FESS Li-ion battery Hydrogen Flow batteries
4
3
2
1
1
10
100
Specific energy(Wh/kg) Fig. 13 Energy and power density profiles for common energy storage technologies.
1000
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205
suppressing fluctuations and providing frequency regulation. These different applications are supported by the response time range for each device—small for SCs and SMES, moderate for FESSs, and large for batteries and hydrogen storage systems, as depicted in Table 1. Efficiency and lifetime details are also presented in Table 1. SMES has the highest efficiency of up to 98% and provides a longer lifetime along with SCs. Finally, the cost of different ESTs is summarized in Fig. 14. Li-ion batteries and hydrogen storage have the lowest cost per kilowatt-hour compared to others. On the other hand, SCs, SMES, and FESS have the lowest cost per kilowatt. Moreover, the continuous downscaling of superconducting material costs is expected to make SMES reach market maturity by 2030 [28].
Table 1 Response Time, Efficiency, and Lifetime for Common Energy Storage Technologies Energy Storage
Li-Ion Battery
Supercapacitor
SMES
Hydrogen
FESS
Response time Efficiency (%) Lifetime (years)
Large 90 15
Small 95 >20
Small 98 >20
Large 42 15
Moderate 95 20
FESS, flywheel energy storage system; SMES, superconducting magnetic energy storage.
105 $/kWh $/kW
Cost ($)
104 103 102 101 100
Li-ion
Super capacitor
SMES
Hydrogen
FESS
Fig. 14 Cost of different energy storage technologies per kilowatt-hour and per kilowatt.
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References [1] M. Chen, G.A. Rincon-Mora, Accurate electrical battery model capable of predicting runtime and I-V performance, IEEE Trans. Energy Convers. 21 (2006) 504–511. [2] L. Xu, D. Chen, Control and operation of a DC microgrid with variable generation and energy storage, IEEE Trans. Power Del. 26 (2011) 2513–2522. [3] A.M. Dizqah, A. Maheri, K. Busawon, A. Kamjoo, A multivariable optimal energy management strategy for standalone DC microgrids, IEEE Trans. Power Syst. 30 (2015) 2278–2287. [4] A. Varghese, L.R. Chandran, A. Rajendran, Power flow control of solar PV based islanded low voltage DC microgrid with battery management system, in: IEEE 1st International Conference on Power Electronics, Intelligent Control and Energy Systems (ICPEICES), Delhi, 2016, pp. 1–6. [5] A.S. Weddell, G.V. Merrett, T.J. Kazmierski, B.M. Al-Hashimi, Accurate Supercapacitor modeling for energy harvesting wireless sensor nodes, IEEE Trans. Circuits Syst. II 58 (2011) 911–915. [6] A. Ghazanfari, M. Hamzeh, H. Mokhtari, H. Karimi, Active power Management of multihybrid fuel cell/supercapacitor power conversion system in a medium voltage microgrid, IEEE Trans. Smart Grid 3 (2012) 1903–1910. [7] M. Hamzeh, M. Ghafouri, H. Karimi, K. Sheshyekani, J.M. Guerrero, Power oscillations damping in DC microgrids, IEEE Trans. Energy Convers. 31 (2016) 970–980. [8] Y. Zhang, Y.W. Li, Energy management strategy for Supercapacitor in droopcontrolled DC microgrid using virtual impedance, IEEE Trans. Power Electron. 32 (2017) 2704–2716. [9] S. Zhang, W. Qin, P. Wang, X. Han, J. Wang, D. Lei, Hierarchical control strategy of hybrid energy storage system in bipolar-type DC micro-grid, in: IEEE 3rd International Future Energy Electronics Conference and ECCE Asia, Kaohsiung, 2017, pp. 2223–2227. [10] A. Tani, M.B. Camara, B. Dakyo, Energy management in the decentralized generation systems based on renewable energy—Ultracapacitors and battery to compensate the wind/load power fluctuations, IEEE Trans. Ind. Appl. 51 (2015) 1817–1827. [11] R. Ramadan, D.M. Yehia, E.M. Rashad, Impact of hybrid energy storage system on solar power generation integrated in microgrids, in: 4th International Conference on Electric Power and Energy Conversion Systems (EPECS), Sharjah, 2015, pp. 1–5. [12] E. Salih, S. Lachowicz, O. Bass, D. Habibi, Superconducting magnetic energy storage unit for damping enhancement of a wind farm generation system, J. Clean Energy Technol. 3 (2015) 398–405. [13] Y. Liu, Y. Tang, J. Shi, X. Shi, J. Deng, K. Gong, Application of small-sized SMES in an EV charging station with DC bus and PV system, IEEE Trans. Appl. Supercond. 25 (2015) 5700406. [14] A.B. Arsoy, Z. Wang, Y. Liu, P.F. Ribeiro, Transient modeling and simulation of a SMES coil and the power electronics interface, IEEE Trans. Appl. Supercond. 9 (1999) 4715–4724. [15] A. Hekmati, R. Hekmati, Double pancake superconducting coil design for maximum magnetic energy storage in small scale SMES systems, Cryogenics 80 (2016) 74–81. [16] Y. Xu, et al., A study on the design and comparison of 1–100-MJ-class SMES magnet with different coil configurations, IEEE Trans. Appl. Supercond. 27 (2017).
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[17] M.G. Molina, P.E. Mercado, Power flow stabilization and control of microgrid with wind generation by superconducting magnetic energy storage, IEEE Trans. Power Electron. 26 (2011) 910–922. [18] I. Ngamroo, T. Karaipoom, Improving low-voltage ride-through performance and alleviating power fluctuation of DFIG wind turbine in DC microgrid by optimal SMES with fault current limiting function, IEEE Trans. Appl. Supercond. 24 (2014) 5700805. [19] J. Li, A.M. Gee, M. Zhang, W. Yuan, Analysis of battery lifetime extension in a SMES-battery hybrid energy storage system using a novel battery lifetime model, Energy 86 (2015) 175–185. [20] H. Alafnan, et al., Stability improvement of DC power systems in an all-electric ship using hybrid SMES/battery, IEEE Trans. Appl. Superconductivity 28 (2018). [21] R. Amirante, E. Cassone, E. Distaso, P. Tamburrano, Overview on recent developments in energy storage: mechanical, electrochemical and hydrogen technologies, Energy Convers. Manag. 132 (2017) 372–387. [22] L. Valverde, F. Rosa, C. Bordons, Design, planning and management of a hydrogen-based microgrid, IEEE Trans. Ind. Informat. 9 (2013) 1398–1404. [23] S.G. Tesfahunegn, Ø. Ulleberg, P.J.S. Vie, T.M. Undeland, Optimal shifting of photovoltaic and load fluctuations from fuel cell and electrolyzer to lead acid battery in a photovoltaic/hydrogen standalone power system for improved performance and life time, J. Power Sources 196 (2011) 10401–10414. [24] A.A.K. Arani, H. Karami, G.B. Gharehpetian, M.S.A. Hejazi, Review of flywheel energy storage systems structures and applications in power systems and microgrids, Renew. Sust. Energ. Rev. 69 (2017) 9–18. [25] F. Dı´az-Gonza´lez, A. Sumper, O. Gomis-Bellmunt, R. Villafa´filaRobles, A review of energy storage technologies for wind power applications, Renew. Sust. Energ. Rev. 16 (2012) 2154–2171. [26] T. Kousksou, P. Bruel, A. Jamil, T. El Rhafiki, Y. Zeraouli, Energy storage: applications and challenges, Sol. Energy Mater. Sol. Cells 120 (2014) 59–80. [27] M. Farhadi, O. Mohammed, Energy storage technologies for high-power applications, IEEE Trans. Ind. Appl. 52 (2016) 1953–1961. [28] B.G. Marchionini, Y. Yamada, L. Martini, H. Ohsaki, High-temperature superconductivity: a roadmap for electric power sector applications, 2015–2030, IEEE Trans. Appl. Supercond. 27 (2017).
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1
Classification of Energy Storage Technologies
Energy storage technologies (ESTs) have diverse classifications either based on their form of storage or based on their projected functions. According to form of storage, there are many existing forms that have been described in detail in the literature; however, this chapter will focus on ESTs applied for microgrids. ESTs can be classified into electrochemical storage as in batteries, electrical storage as in supercapacitors (SCs), magnetic storage as in superconducting magnetic energy storage (SMES), kinetic storage as in flywheels, and chemical storage as in hydrogen. According to the projected functions of ESTs, they can be classified based on their energy density, their power density, or based on their response time. A major distinction in the application of ESTs with microgrids depends on these features.
2 2.1
Battery Energy Storage Systems Comparison of Different Battery Types
Battery energy storage systems (BESSs) are widely used in the energy market. A BESS is an electrochemical device that can convert electrical energy to chemical energy or vice versa depending on its operational mode—either charging or discharging. The basic principle of a BESS is depicted in Fig. 1. A BESS is composed Medium-Voltage Direct Current Grids. https://doi.org/10.1016/B978-0-12-814560-9.00010-0 # 2019 Elsevier Inc. All rights reserved.
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Fig. 1 The basic principle of a battery energy storage system.
of a battery bank, power-conditioning system, and control scheme. The battery bank comprises a number of batteries, with each battery having multiple cells connected in parallel and/or series to supply the desired output voltage and capacity. The cell itself consists of two electrodes in an electrolyte, where electrons are transferred between electrodes and through the external circuit. The first electrode is negative and acts as an anode, while the second one is positive and acts as a cathode. There are different battery types with different applications depending on electrode form and electrolyte material. The most important battery types used for electrical grids are lead–acid (LA) batteries, nickel-cadmium (Ni-Cd) batteries, lithium-ion (Li-ion) batteries, and flow batteries. LA batteries were the first rechargeable batteries used for commercial applications. However, they had the disadvantages of having low specific energy and power, the need for periodic maintenance, and limited charge/discharge cycles. Ni-Cd batteries offer a competitive substitution to LA batteries due to their higher energy density, large number of charge/discharge cycles, and lower maintenance requirements. In Ni-Cd batteries, nickel hydroxide is used as the positive electrode and cadmium hydroxide is used as the negative one. In addition to the toxicity of nickel and cadmium metals, Ni-Cd batteries have a memory effect that necessitates complete charging and discharging before starting a new cycle. This makes them unsuitable for microgrids that require moderate charging and discharging cycles depending on the condition of energy mismatch. Li-ion batteries were widely used for mobile phones and electronic devices before being adopted as potential energy storage systems for large applications. The motivation behind using Li-ion batteries in energy applications is attributed to several factors: they have high energy and power densities compared to other battery types; their open-circuit voltage is high, reaching
Chapter 8 ENERGY STORAGE TECHNOLOGIES IN MVDC MICROGRIDS
Anolyte reservoir
Flow cell
External circuit
Catholyte reservoir
Ion selective membrane
Fig. 2 The basic operational principle of flow batteries for energy storage.
up to 4 V per cell; and they offer rapid charging/discharging, a low self-discharging rate, and a long lifetime of up to 3000 cycles. Recently, flow batteries were developed as a new technology for energy storage. Their operation is based on a reversible chemical reaction that occurs between two aqueous electrolytes supplied from two separated tanks as shown in Fig. 2. The energy capacity of flow batteries can be easily managed through changing the volume of stored electrolytes. The use of flow batteries with microgrids and renewable energy sources is still limited due to their high cost.
2.2
Battery Modeling and Characteristics
Because of the nonlinear characteristics of batteries, it is not appropriate to model them as a constant voltage source. Therefore, there are several battery models that have been developed in the literature. These models include the Thevenin battery model, the impedance-based battery model, the runtime-based battery model, and the combined model. The combined model is the most widely adopted model for investigating battery characteristics. According to the combined model, the cell dynamic equivalent circuit is structured according to Fig. 3 [1]. The equivalent circuit consists of two main parts. The first part represents the voltage-current characteristics, containing a series resistor Rser and two RC parallel circuits indicated by RTS, CTS, RTL, and CTL. The series resistor Rser represents the instantaneous voltage drop, while the RC parallel network elements RTS and CTS
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Rser
Vsoc
RTS
RTL
Rsd + –
Ccap
Voc
CTS
CTL
Ibat
Fig. 3 The equivalent circuit to a battery cell model.
represent the step response in the short time range. Elements RTL and CTL represent the step response in the long time range. The second part of the equivalent circuit represents battery lifetime. This part contains the cell’s self-discharge resistance Rsd in addition to a capacitor Ccap. The self-discharge resistance, which is affected by cell temperature, represents the internal energy loss of the cell when the battery is stored for a long time and also affects the flow rate. On the other hand, the capacitor represents the capacity of the cell in ampere hours (Ah). The two parts of the equivalent circuit are linked through the battery charge/discharge current Ibat which flows through the first part and is considered a current source for the second part of the equivalent circuit. This equivalent circuit represents the nonlinear relationship between the open-circuit voltage (Voc) and the state of charge (SOC). The following equations are used to define the elements comprising the cell equivalent circuit, as well as the value of the open-circuit voltage (Voc) in terms of the battery’s SOC: VOC ðSOCÞ ¼ 1:031 e 35SOC + 3:685 + 0:2156 SOC 0:1178 SOC2 + 0:3201 SOC3 (1) Rser ðSOCÞ ¼ 0:1562 e 24:37SOC + 0:07446
(2)
RTS ðSOCÞ ¼ 0:3208 e 29:14SOC + 0:04669
(3)
CTS ðSOCÞ ¼ 752:9 e
13:51SOC
+ 703:6
(4)
RTL ðSOCÞ ¼ 6:603 e 155:2SOC + 0:04984
(5)
CTL ðSOCÞ ¼ 6056 e 27:12SOC + 4475
(6)
In addition, the cell capacity Ccap is given as follows: Ccap ¼ 3600 Capacity f1 ðCycleÞ f2 ðTempÞ
(7)
Chapter 8 ENERGY STORAGE TECHNOLOGIES IN MVDC MICROGRIDS
5.0 Cell current Cell voltage
Current (A)
2.5
4.5
2.0
4.0
1.5
3.5
1.0
3.0
0.5
2.5
0.0
0
20
40
60
80
Voltage (V)
3.0
2.0 100
State of charge (%)
Fig. 4 The voltage and current characteristics of a Li-ion battery cell.
The factors f1 and f2 represent the cycle number and temperature, respectively, which affect battery lifetime. On the other hand, Rsd is a function of SOC, temperature, and cycle number. Because of the low self-discharge feature of Li-ion batteries, self-discharge can be ignored or represented as a large resistor, which represents the typical case used for modeling. The voltage characteristic of a Li-ion battery cell with a 4.1-V rated voltage is shown against the SOC in Fig. 4. This characteristic is typical. The initial voltage of the cell is 3.0 V when the battery is dead with a zero SOC. When the charging process starts, the voltage increases quickly to 3.7 V during the initial 15% SOC. With an increasing SOC, the voltage continues to increase, but at slower rate until the SOC reaches 100%, corresponding to 4.1 V. With respect to charging current, it increases from 0 A to a maximum value of 2.6 A at 15% SOC, before decreasing gradually to 0 A at 100% SOC.
2.3
Battery Applications With DC Microgrids
Fig. 5 shows a battery that has been interfaced with a DC microgrid via a bidirectional converter. A BESS has two main functions within a DC microgrid. The first function is the energy management of the available generation and the load demand; the second function is the stabilization of DC bus voltage, especially for DC microgrids in island mode. There are several modes that determine the operation of a BESS in DC microgrids. These modes are determined by grid connection status, SOC, available generation, and load requirements [2–4]. They are described in the following text.
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L S1 Battery model
194
C
S2
g2
g1
Voltage control
Vref
Vdc Coupling point
Fig. 5 A battery interfaced with a DC microgrid.
Mode 1: operation under AC grid connection. In this case, any excess or lack of power experienced by the DC microgrid is compensated by the grid, through the proper control of a grid-voltage source converter. Renewable energy sources are then operated at their maximum power point tracking and a BESS can be charged or discharged flexibly depending on operator requirements. Mode 2: operation under AC grid disturbance. In this case, the grid converter becomes incapable of maintaining a constant DC bus voltage. So, a BESS control operates in voltage-stabilization mode by balancing the power within the DC microgrid, provided the available generation lies within the maximum power range. Otherwise, the DC bus voltage will fall, necessitating load shedding. Mode 3: islanding operation. This mode is similar to Mode 2, where a BESS stabilizes the DC bus voltage and compensates for the power mismatch. Here, the SOC of the BESS plays an important role in determining the appropriate operation. If the required power exceeds the rating of the BESS, or the required energy exceeds the remaining SOC of the battery, then load shedding becomes necessary to maintain a constant DC voltage. To the contrary, if the battery is fully charged or the generating power exceeds the rating of the BESS, then an overvoltage can occur. However, this can be mitigated for a photovoltaic (PV) system by changing from maximum power point tracking (MPPT) control to droop control, and for the case of wind energy, by changing from MPPT control to pitch angle control.
Chapter 8 ENERGY STORAGE TECHNOLOGIES IN MVDC MICROGRIDS
3 3.1
Supercapacitor Energy Storage Systems Basic Principles
SCs store energy in the form of electrostatic charges between two conductive electrodes, separated by a dielectric material. The electrodes in SCs are porous. The energy stored in an SC (Esc) is given by the following equation: 1 Esc ¼ CV 2 2
(8)
where C is the capacitance and V is the voltage between terminals. The capacitance in turn is proportional to the electrode area. So, using porous electrodes provides a large specific area with a subsequent high energy density. This is the main difference between SCs and conventional capacitors. In spite of the very high charge density stored on the electrodes of SCs, they have low cell voltages, in the order of 3 V. Therefore, to reach the desired capacity, multiple series and parallel cells are connected. SCs can be classified either depending on the design of the electrodes or the electrode material. For the design of the electrodes, SCs can be symmetrical, if negative and positive electrodes have the same material, or unsymmetrical, if different materials are used for the electrodes. Regarding electrode material, it can be activated carbon, a metal oxide, or an electronically conducting polymer. Activated carbon is the most common material used commercially for SC electrodes, as it possesses high capacity and low cost.
3.2
Supercapacitor Modeling and Characteristics
As practically observed, an SC has nonlinear characteristics due to its internal construction. Accordingly, its modeling is different to that of conventional capacitors. The stored charges in SCs form what is called an electrical double layer between the solid electrodes and electrolyte. So, the extraction of charge in SCs passes through different processes, each having different time constants. To model this behavior accurately, a three-branch SC model, depicted in Fig. 6, is proposed [5]. The first branch includes a voltage-dependent capacitor to simulate nonlinear behavior, while the other branches model the long-term charging behavior that depends on the distribution of charge along the electrodes.
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DC
i1
+ –
C1
i2
C2
i3
Vo (t)
C3
Fig. 6 A three-branch supercapacitor model.
3.3
Supercapacitor Applications With DC Microgrids
SCs are usually used with a DC microgrid for smoothing output power and mitigating fluctuations [6, 7], due to their large power densities. However, SCs cannot contribute to energy management due to their small energy densities. To achieve their required functions, SCs are operated either using a current-mode controller or voltage-mode controller [8]. The current-mode controller is based on measuring the total power in the system either supplied from generation or delivered to the load, and then, filtering this power using a high-pass filter to extract the high-frequency component that acts as the reference output power for the current-mode controller of the SC. This scheme necessitates the accurate measurement of the different powers that are naturally distributed. For the voltage-mode controller, the voltage of the DC bus itself is used as an indication of power fluctuation. So, the high-frequency component of this voltage is used as a reference signal for the voltage-mode controller of the SC. Since the size and cost of SCs increases when used to supply low-frequency or large magnitude variations, they are usually used in combination with batteries, forming what is called a hybrid energy storage system, achieving both functions of mitigating fluctuations and energy management. In [9], the SC operation was managed with battery based on the magnitude of fluctuations. For small-scale fluctuations, the SC operates through fast charging and discharging to balance the power on the DC bus. The changes in SC voltage in this case will be small. For large-scale fluctuations, the changes in SC voltage will be high, either as a voltage rise or as a voltage drop. So, the battery operates to compensate the energy required by the SC. In additional research [10], the operation between the SC and battery was managed,
Chapter 8 ENERGY STORAGE TECHNOLOGIES IN MVDC MICROGRIDS
giving consideration to the frequency component of generation/ load variations. In this case, high-frequency components and low-frequency components can exist individually or in combination. The energy management strategy was built based on the frequency component so that high-frequency components were allocated to the SC and low-frequency components were allocated to the battery. Hybrid energy storage was also considered with a PV/load DC microgrid [11], in order to benefit from the fast charging/discharging of the SC to alleviate the impact of sudden changes in the grid—either originating from the load side or the PV side.
4 4.1
Superconducting Magnetic Energy Storage Basic Principles
A SMES unit consists of two main parts, in addition to a power conditioning system. The first part of a SMES unit is the superconducting coil, which is the heart of the system. It stores energy in the form of a magnetic field generated by a circulating DC current. The maximum stored energy is determined by two factors. The first factor is the size and geometry of the coil, which determines the inductance of the coil—the larger the coil inductance, the greater the stored energy. The second factor is linked to the characteristics of the conductor, which determine the maximum carrying current. Superconductors carry substantial currents exhibiting high magnetic fields. The second part of a SMES unit is the refrigeration system. A SMES coil must be maintained at a temperature sufficiently low to maintain a superconducting state in the coil. Reaching and keeping the superconducting temperature is accomplished by a special cryogenic refrigerator. There are several types of superconducting materials used for a SMES unit, permitting their classification as high-temperature superconductors and low-temperature superconductors. High-temperature superconductors are cooled at 77 K using liquid nitrogen, while low-temperature superconductors are generally cooled at 4.2 K using liquid helium. Since a SMES unit stores energy in the form of a magnetic field, large quantities of power can be stored over short time periods with high efficiency. The inductive stored energy ESMES in a SMES coil is expressed as [12, 13]: 1 2 ESMES ¼ L ISMES 2
(9)
where L is the superconducting coil inductance and ISMES is the SMES maximum current.
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4.2
Superconducting Magnetic Energy Storage Modeling and Characteristics
A model of a SMES unit was developed using a coil with a DC chopper with a smoothing capacitor on its output (Fig. 7). The SMES coil itself was modeled using several segments, as shown in Fig. 8 [14], where each segment represented a single coil. SMES coils can be wound as a solenoid structure, toroidal structure, or pancake structure. For small-scale units, the pancake SMES structure is preferred [15]. However, for large-scale units, solenoid and toroidal structures are usually used [16]. The toroidal structure has a reduced wire cost compared to the other structures. Each segment of a SMES coil is composed of a series inductance and resistance, as well as a shunt capacitance to ground. The inductance is measured in Henry, the resistance in ohms, and the capacitance in microfarad. The resistance Rt accounts for the eddy current losses in the coil. The required inductance is divided
Idc D1
S1
Vdc SMES coil S2
D2
Fig. 7 Model of a superconducting magnetic energy storage unit.
Lt
Rt
Lt
Ctt
1/2Ctg
Rt
Lt
Ctt
Ctg
Rt Ctt
Ctg
Ctg
1/2Ctg
Fig. 8 Model of a superconducting magnetic energy storage coil.
Chapter 8 ENERGY STORAGE TECHNOLOGIES IN MVDC MICROGRIDS
equally among the different segments of a SMES coil and is represented by Lt. The interwinding capacitances between coils are represented by Ctt and the coil turns to ground capacitance is represented by Ctg. A SMES coil is enclosed in a closed container and is grounded by the material that encloses it.
4.3
Superconducting Magnetic Energy Storage Applications With DC Microgrids
By controlling the main switches S1 and S2 of a two-quadrant DC-DC chopper, a SMES unit can be operated in three different modes. The first mode is the charging mode, where SMES stores energy from the grid to the coil. In the case when both switches are “on” and the charging current flows through them, as shown in Fig. 9A. When one of the switches is “on” and the other “off” SMES is said to be in freewheeling mode, as shown in Fig. 9B. This mode causes SMES coil terminals to be shorted and this keeps the current circulating in the coil without any significant loss due to the use of superconducting material for the coil with a very low ohmic resistance for the switch and diode. This mode can be used when SMES is charged, and there is a need to keep its SOC for a certain period before discharging. The third mode is the discharging mode, in which the coil will inject stored energy back to the system. To operate in this mode, both switches need to be “off” to force a route for SMES current to flow back into the system through diodes, as shown Fig. 9C. SMES is used with microgrids in the same way that an SC is used, where it has fast charging/discharging and a large power density. However, SMES has a higher energy density than an SC. Therefore, it is expected that SMES will play a part in the energy storage applications of the future, especially with the continuous downscaling of superconducting material costs. Several applications of SMES with microgrids are highlighted here. First, in the case of islanding operations, either due to tripping of tie-line connections with the grid or an occurring fault on the grid, SMES compensates quickly for the sudden power loss preventing a large deviation in frequency and enhancing the dynamic performance of the system [17]. A second application is linked to its ability to smooth power fluctuations [18], especially from wind turbine generators that are inherently operated under variable wind speeds. SMES can also be used with batteries in a hybrid platform to alleviate the impact of sudden power changes over battery lifetime [19].
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D1
S1
SMES coil S2
D2
(A)
D1
S1
SMES coil S2
D2
D1
S1
(B)
SMES coil S2
D2
(C) Fig. 9 Model of a superconducting magnetic energy storage unit. (A) Charging mode. (B) Freewheeling mode. (C) Discharging mode.
Also, SMES effectively compensates for sudden changes that originate from pulsed loads in a DC microgrid, as shown in Fig. 10, that presents the characteristics of a DC microgrid composed of a diesel generator, a pulsed load, and a SMES/battery hybrid energy storage system. Here, the load changes from 7 to 11MW, pulsing every 3.0 s. All the voltage levels and power ratings were adjusted to match the values given in [20]. Without using any storage system, the system undergoes sudden voltage dips and swells directly after each pulsed increase and decrease in load, respectively. In addition, the DC bus voltage remains below the nominal voltage during pulsed load operation. All these voltage variations cannot be compensated by the diesel generator due to its large ramp rate. Using only the battery, the voltage dips and swells
Chapter 8 ENERGY STORAGE TECHNOLOGIES IN MVDC MICROGRIDS
Load (MW)
12 10 8 6
DC voltage (p.u.)
4 2.5 Without energy storage With battery only With SMES/battery
2.0 1.5 1.0 0.5
SMES current (A)
Battery current (A)
0.0 800 600 400 200 0 400 300 200 100 0
0
2
4
6
8
10
12
Time (s) Fig. 10 Superconducting magnetic energy storage/battery hybrid energy storage system operating under a pulsed load.
decrease in magnitude, but still show slight values due to the battery’s slow response. Using SMES, the DC bus voltage remains constant during the pulsed load operation. The SMES current was 300 A at the instant of the pulsed load operation, the current then decreased gradually enabling the battery to respond and discharge to compensate the pulsed load change. During transition times, both SMES and battery shared the load requirements. After SMES was discharged, the battery completely supplied the load requirements.
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5 Other Energy Storage Technologies There are a few other energy storage technologies that have been used with DC microgrids. Particularly, flywheel energy storage and hydrogen storage have been used in a limited range. This section summarizes the applications of these two technologies with DC microgrids. For hydrogen storage, surplus energy is used to operate an electrolyzer, to produce hydrogen. The produced hydrogen is then stored as a pressurized gas in cylinders, or as a liquid in cryogenic tanks. When this energy is needed, the stored hydrogen is used to produce energy through either a combustion engine or a fuel cell [21]. The latter is more efficient. The scheme used for hydrogen storage with a DC microgrid is shown in Fig. 11 [22]. The operation of a hydrogen storage system follows three different operating modes, similar to other energy storage technologies. The first mode is charging mode during which the electrolyzer is switched on when there is an excess energy and the existing battery has attained its maximum SOC. The second mode is discharging mode, where the electrolyzer is switched off and the fuel cell is turned on. This mode is operated when there is a lack of energy supplied from renewable energy sources and the battery. The last mode is dead-band mode, in which neither the electrolyzer nor fuel cell is operated—where battery usage is preferred to avoid frequent electrolyzer and fuel cell on-off cycles. These frequent on-off cycles can degrade the performance and lifetime of a hydrogen storage system [23]. Hydrogen storage has high energy density, but low power density. Therefore, it can be used as an energy balancer in microgrids, in a similar manner to batteries. With a DC microgrid composed of a PV array, a battery, and a load [22], a hydrogen storage system can
Fig. 11 A hydrogen storage scheme with a DC microgrid.
Chapter 8 ENERGY STORAGE TECHNOLOGIES IN MVDC MICROGRIDS
successfully absorb excess energy during sunny periods and keep a stable power supply to the load during cloudy periods. Regarding a flywheel energy storage system (FESS), the energy is stored in kinetic form using a spinning rotating disk. In addition to the rotating disk, the other components of a FESS include bearings, electrical machinery, and a power converter interface [24]. The rotating disk is usually made of composite material in order to achieve high-speed operation while maintaining low weight. This reflects on the energy stored in the flywheel Ef, and can be expressed as follows: 1 Ef ¼ j ω2 2
(10)
where j is the moment of inertia and ω is the angular velocity. Bearing systems can be mechanical, magnetic, or superconducting. The latter two types have low friction, small losses, and high operating speeds. The electrical machinery can be an induction machine, a permanent magnet synchronous machine, or a switched reluctance machine. They can be operated into two modes, generating mode and motoring mode, depending on the energy management needs from the FESS. A schematic diagram of a FESS interfaced with a DC microgrid is shown in Fig. 12. The power converter interface is a three-phase voltage source converter operating in inverting mode or rectifying mode in order to enable an energy exchange between the FESS and the microgrid. The control scheme utilizes the DC bus voltage as a control signal. In addition, the rotating disk speed and electrical machine currents are used as inputs to the control scheme DC bus
S1
S3
S5
S2
S4
S6
Machine
w
Vdc
Iabc
Control scheme
Fig. 12 Schematic diagram of a flywheel energy storage system interfaced with a DC microgrid.
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in order to keep stored energy within its maximum and minimum thresholds and to set priority for all energy storage units connected to the DC bus. A FESS has multiple applications with DC microgrids, either as a primary energy storage unit or as a backup. It operates in three modes: charging, discharging, and standby. During charging mode, the machine operates in motoring mode resulting in an acceleration of the rotating disk to higher speeds, absorbing energy from the grid. Once the rotating disk speed attains its maximum threshold, the FESS is isolated from the system and operates in standby mode, by keeping the rotating disk speed constant. During discharging mode the machine operates in generating mode by decelerating the rotating disk and injecting power into the grid.
6 Comparison of Energy Storage Technologies The differences between the ESTs mentioned in this chapter mean they have different applications in terms of DC microgrids. These differences can be summarized in terms of power and energy densities, response times, efficiencies, lifetimes, and costs. Fig. 13 summarizes the energy and power density profiles for common ESTs [25–27]. SCs, SMES, and FESSs have higher power densities, while batteries and hydrogen storage have higher energy densities. So, batteries and hydrogen storage can be used for energy management and the smoothing of low-frequency variations. On the other hand, SCs, SMES, and FESSs can be used for
Specific power (W/kg)
10
10
10
10
10
5
Supercapacitor SMES FESS Li-ion battery Hydrogen Flow batteries
4
3
2
1
1
10
100
Specific energy(Wh/kg) Fig. 13 Energy and power density profiles for common energy storage technologies.
1000
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suppressing fluctuations and providing frequency regulation. These different applications are supported by the response time range for each device—small for SCs and SMES, moderate for FESSs, and large for batteries and hydrogen storage systems, as depicted in Table 1. Efficiency and lifetime details are also presented in Table 1. SMES has the highest efficiency of up to 98% and provides a longer lifetime along with SCs. Finally, the cost of different ESTs is summarized in Fig. 14. Li-ion batteries and hydrogen storage have the lowest cost per kilowatt-hour compared to others. On the other hand, SCs, SMES, and FESS have the lowest cost per kilowatt. Moreover, the continuous downscaling of superconducting material costs is expected to make SMES reach market maturity by 2030 [28].
Table 1 Response Time, Efficiency, and Lifetime for Common Energy Storage Technologies Energy Storage
Li-Ion Battery
Supercapacitor
SMES
Hydrogen
FESS
Response time Efficiency (%) Lifetime (years)
Large 90 15
Small 95 >20
Small 98 >20
Large 42 15
Moderate 95 20
FESS, flywheel energy storage system; SMES, superconducting magnetic energy storage.
105 $/kWh $/kW
Cost ($)
104 103 102 101 100
Li-ion
Super capacitor
SMES
Hydrogen
FESS
Fig. 14 Cost of different energy storage technologies per kilowatt-hour and per kilowatt.
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