Integrated photovoltaic-grid dc fast charging system for electric vehicle: A review of the architecture and control

Renewable and Sustainable Energy Reviews 69 (2017) 1243–1257

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Integrated photovoltaic-grid dc fast charging system for electric vehicle: A review of the architecture and control

MARK

⁎

Ratil H. Ashiquea,b, Zainal Salama,b,c, , Mohd Junaidi Bin Abdul Azizb,d, Abdul Rauf Bhattia,b,e a

Centre of Electrical Energy Systems (CEES), Universiti Teknologi Malaysia (UTM), 81300 Johor Bahru, Johor, Malaysia Faculty of Electrical Engineering, Universiti Teknologi Malaysia (UTM), 81300 Johor Bahru, Johor, Malaysia Institute of Future Energy, Universiti Teknologi Malaysia (UTM), 81300 Johor Bahru, Johor, Malaysia d Power Electronics and Drives Research Group, Universiti Teknologi Malaysia (UTM), 81300 Johor Bahru, Johor, Malaysia e Department of Electrical Engineering, Government College University Faisalabad (GCUF), 38000 Faisalabad, Pakistan b c

A R T I C L E I N F O

A BS T RAC T

Keywords: EV charging PV-grid charging DC fast charging BMS CMS

The fast charger for electric vehicle (EV) is a complex system that incorporates numerous interconnected subsystems. The interactions among these subsystems require a holistic understanding of the system architecture, control, power electronics, and their overall interaction with the electrical grid system. This review paper presents important aspects of a PV-grid integrated dc fast charger—with a special focus on the charging system components, architecture, operational modes, and control. These include the interaction between the PV power source, grid electricity, energy storage unit (ESU) and power electronics for the chargers. A considerable amount of discussion is also dedicated to battery management systems (BMS) and their mutual interactions in the control processes. For the power electronics, the paper evaluates soft switching non-isolated dc-to-dc power converter topologies that can be possibly used as future EV chargers. In addition to these, a brief discussion on the impact of the PV-grid charging on the ac grid and distribution system and their remedial measures are presented. Furthermore, the challenges in regard to the vehicle to grid (V2G) concept are also described. It is envisaged that the information provided in this paper would be useful as a one-stop document for engineers, researchers and others who require information related to the dc fast charging of EV that incorporates a renewable energy source.

1. Introduction The expected growth of electric vehicle market (EV) mandates a corresponding development in the charging facilities [1,2]. Next to the battery [3,4], the availability and reliability of chargers are of utmost concern. Efforts are being made to enhance the charger efficiency, to make it more versatile and to reduce the charging cost. Despite the encouraging indicators, implementing high power, fast charging facilities is not trivial. In [5–8], the authors describe the technological challenges to integrating the electrical grid into the EV chargers. The uncontrolled and random charging pattern may lead to voltage deviation, distribution losses, and degradation in power quality. Furthermore, the issue of reduced transformer lifetime due to overload and instability need to be addressed.

Recently, there are growing interests in utilizing Renewable Energy (RE) as a secondary energy source for the charger. Most possible RE sources include the wind, biomass and solar [9]. However, solar photovoltaic is a more feasible solution, especially for day-time charging. With the continuous downward trend in the price of the PV modules, this proposal is becoming attractive—as evident from numerous recent publications [2,10–13]. A PV system is easy to set-up, and is almost maintenance free [14]. This prospect is further enhanced by the improvement in power conversion technologies and installation practices [15–17]. Furthermore, since the charging is carried out during the peak demand period (daytime)—where the tariff is normally at its highest [18], the economic returns can be substantial [19]. M. Brenna et. al.[20] evaluate the benefits of integrating PV into the charging system, while in [11,13,21–24] its effectiveness in the smart grid

Abbreviations: BMS, Battery management system; CAN, Controller area network; CB, Circuit breaker; CC, Constant current; CCS, Central control system; CMS, Charger management system; CV, Constant voltage; DSP, Digital signal processor; ESU, Energy storage unit; EV, Electric vehicle; EVMS, Electric vehicle management system; EVSE, Electric vehicle supply equipment; GA, Genetic algorithm; MPP, Maximum power point; MPPT, Maximum power point tracking; PLC, Power line carrier; P & O, Perturb and observe; PQ, Power quality; RE, Renewable energy; SAE, Society of automotive engineers; SG, Smart grid; SOC, State of charge; SOH, State of health; OCV, Open circuit voltage; V2G, Vehicle to grid; ZVS, Zero voltage switching; ZCS, Zero current switching; ZVT, Zero voltage transition ⁎ Corresponding author at: Centre of Electrical Energy Systems (CEES), Universiti Teknology Malaysia (UTM), 81300 Johor Bahru, Johor, Malaysia. E-mail addresses: [email protected] (R.H. Ashique), [email protected] (Z. Salam), [email protected] (M.J. Bin Abdul Aziz), [email protected] (A.R. Bhatti). http://dx.doi.org/10.1016/j.rser.2016.11.245 Received 2 May 2016; Received in revised form 4 October 2016; Accepted 21 November 2016 Available online 01 December 2016 1364-0321/ © 2016 Elsevier Ltd. All rights reserved.

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Nomenclature

imax S, M C L R TS VS

Symbol unit description vPV iPV vmax

Volt (V) PV voltage Ampere (A) PV current Volt (V) Max. charging voltage

Ampere (A) Max. charging current - Power switch Farad (F) Capacitance Henry (H) Inductance Ohm (Ω) Resistance Degree celsius Safe operating temperature Volt (V) Safe operating voltage

of the battery pack, power rating of the charger, and the number of EV that are connected to the charger at that instant. The ac Level 1 is an on-board charging facility, derived from conventional 120 V ac outlets. It requires no extra setup and thus the charging can be done conveniently (normally overnight) at home. However, due to the size, weight, and thermal constraints, the Level 1 charging current is very much limited, hence the long charging time. The majority of public charging stations in the US and elsewhere are the ac Level 2—powered by a 240 V ac outlet. It requires a dedicated setup at charging sites due to its voltage rating and higher power handling capability. The ac Level 3 has even higher power ratings to ensure fast, secure and convenient charging as mostly preferred by EV owners. However, ac Level 3 charging is yet to be implemented. As the battery pack size and the number of EV on the road is increasing day by day, the only feasible way to reduce the charging time is to increase the power rating of the chargers. The dc fast charger is the most promising candidate to fulfil this requirement; hence the widespread installation, particularly at commercial charging stations. The dc fast charging is offered by the IEC CHAdeMO, SAE J1772 Combo and Tesla-S supercharger. The CHAdeMO is a conductive dc fast charger that allows up to 200 A charging at 50 kW. To establish secure communication between electric vehicle management system (EVMS) and charger control units, controller area network (CAN) protocol is applied. From the smart grid (SG) context, the CHAdeMO supports bidirectional power flow for the future vehicle to grid (V2G) or vehicle to home (V2H) applications. The SAE J1772 Combo 1 and 2 is a combined charging standard developed by the Society of Automotive Engineers (SAE). It specifies the physical, electrical and functional requirements to support the ac Level 1, 2, 3 and dc fast charging. The Combo 1 (or alternatively known as IEC Type 1) is commonly used in

environment is discussed. In [25], the authors investigate various architectures for the PV-Grid system, incorporating of either ac or dc buses. On the converters, the N. Naghizadeh and Y. Du et.al.[26,27] present a review on the topologies suitable for integrated PV-grid charger. The main focuses are the bi-directional dc-dc or dc-ac converters, coupled with the maximum power point tracking algorithms. The charger operational modes and its optimization are discussed in [28–30]. In addition, the merits of employing energy storage units (ESU) to reduce the negative effect on the grid are discussed in [29,31,32]. The work is further enhanced and supported with detailed system modeling, simulation and experimental evidence presented in [30]. The brief overview above provides a flavor on the issues related to the integration of PV into the conventional grid for the EV charging. Evidently, it consists of several sub-systems that interact with each other in a complex way. The literature that addresses these issues can be grouped into several categories, namely 1) charger topologies, 2) energy management and 3) system optimization. Although there exist several excellent review papers [2,11,12,33] that summarize the recent trends, they tend to focus on specific aspects of the system. For example, in [2], the emphasis is on the isolated and non-isolated dc chargers for PV-grid charging schemes. F. Mwasilu et. al.[12] review the EV charging infrastructures in the smart grid context, while [33] presents the optimization of the vehicle-to-grid (V2G) integration. On the other hand, the work in [11] details the cost minimization, efficiency maximization and emission reduction of the PV-grid system. Despite these works, there appears to be an absence of comprehensive review papers that combine the stated issues relating to the PVgrid integrated charging. Besides, so far there is no paper that covers the issues relating to the PV-grid integrated dc fast charging system for EV. Thus, this paper presents a review of the architecture of such a system that incorporates the battery management system (BMS) and charger management system (CMS) as part of the control. The functions of BMS for the state of charge (SOC) estimation, battery equalization, cell balancing and its inter-relation with the charging management system (CMS) are covered. Besides, a short discussion on renewable energy integration with the EV charging is presented. In addition, the paper evaluates the dc charger module, focusing on the soft switching bidirectional non-isolated topologies. For completeness, the impact of charging on the distribution grid, system assets, and power quality are discussed. An insight into the future of the vehicle-togrid (V2G) is also presented.

Table 1 EV charging standards. Level

Max power rating (kW)

Max ampere rating (A)

IEC Standard AC Charging ac Level 1 ac Level 2 ac Level 3

4 −7.5 8 −15 60 −120

16 32 250

DC Charging dc Fast Charging

100 −200

400

AC Charging ac Level 1 ac Level 2 ac Level 3

2 20 Above 20

16 80 –

DC Charging dc Level 1 dc Level 2 dc Level 3

40 90 240)

80 200 400

CHAdeMO dc Fast Charging

62.5

125

2. System of common use and the charging standards SAE Standard

Large scale penetration of the EV into car market is highly dependent on the widespread and successful implementation of the charging infrastructures [16]. Often, the selection of charging power level is an optimization between the cost of infrastructure and the charging time. There are two main categories of the EV charger: the ac and dc types, as shown in Table 1 [1]. Furthermore, there are three main worldwide bodies that are competing to become the de-facto standard for the EV battery charging: they are the IEC, CHAdeMO, and SAE. In addition, Tesla Motor also proposes its own charging standard for its EV. The charging time for the EV depends on three factors, namely size 1244

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the US, while Combo 2 (IEC Type 2) is more popular in Europe. The power line communication (PLC) standard IEEE P1901 is utilized to establish communication between EV, EVSE and other smart grid equipment. The Tesla 135 kW Supercharger is a dedicated dc fast charging utility for Tesla-S series, all-wheel drive (AWD) and Tesla-X vehicles. It is standardized and installed only by Tesla itself. A summary of power and current level comparison for electric vehicle supply equipment (EVSE) charging schemes are listed in Table 1. 3. Grid-connected RE based charging systems With the projected rapid increase in the number of EV, it is inevitable that the electrical grid will be burdened. The integration of RE sources into the grid is one way to alleviate the problem [9]. The wind, solar and biomass energy are possible sources that can be considered for this purpose. A number of studies are carried out to examine the large-scale, long-term impact of wind energy to meet the excess energy demand introduced by the EV charging [34–36]. However, it has to be noted that wind energy based systems require suitable locations and wide premises for the installation of windmills. In urban areas where large buildings are the major hurdles in the wind pathways, the challenge is immense. Moreover, highly fluctuating nature of wind speed makes it less attractive for the EV charging, compared to other RE sources. Biomass energy (i.e. bioelectricity from biomass) differs from the wind energy in the sense that it can be stored conveniently and can be utilized whenever necessary [9]. Although liquid biofuels are thought to be a promising alternative vehicle fuel, bioelectricity has a number of advantages for EV charging station. It can be produced using various biomass feedstocks including, but not limited to forestry and agricultural residues, woody energy crops, and whole tree harvesting. From a financial point of view, bioelectricity has a higher energy return as compared to biofuel processes. Several recent studies are published to examine the possible application of biomass energy in electric transport [37–39]. Despite these advantages, the production of bioelectricity results in a high-polluting environment which makes it unsuitable for densely populated areas. The literature on solar energy for EV charging is much more advanced and diverse. This is because the electricity from solar PV provides more flexibility in integrating with the existing grid. One of the main concepts is to charge the EV directly using the principle of “charging-while-parking”, to replace the more commonly practiced “charging-by-stopping” [40,41]. This gives rise the opportunity to utilize the PV by fitting them at the roof of the car park [42,43]. Consequently, the EV can be conveniently charged by the integrated PV-grid system while the EV owner engages with other activities [44]. P. J. Tulpule et. al.[45] have listed numerous benefits of the PV powered charging station. Since the charging is done during the daytime, where the load demand and electricity tariff are at their peak, the cost savings is substantial. On top of that, the roofed-parking facilities provides free shelters from the sun and rain, which is a favorable feature in hot climate countries [46]. Due to these advantages, the PV-grid based system is more preferred than other renewable energy based systems. A. R. Bhatti et. al.[47] present the case study on charging using a standard grid system, PV-grid system and PVstandalone in the presence of energy storage unit (battery banks). The study concludes that the PV-grid system is more profitable compared to the PV-standalone and standard grid charging systems. Furthermore, a large-scale deployment of EV chargers is analyzed in [48], where solar car-ports are introduced over large parking lots in a medium-sized Swiss city. The authors find that 14–50% of the city's public transportation energy demand could be provided by solar energy. S. Letendre et. al.[49] propose a simple method to estimate the cumulative capacity that can be provided by a PV-grid and V2G (vehicle to grid) stations for the California market. In another work, W. Kempton et. al.[50] discuss the application of PV electricity and storage

Fig. 1. The generalized system architecture of a PV-grid dc fast charging system.

in EVs (i.e. V2G) to supply peak energy to the grid. 4. PV-grid dc fast charging system architecture The existing PV-EV charging papers cover the technological aspects, integration issues, optimization, environmental consequences and its impact on the grid. Furthermore, combining the grid and renewable energy sources is considered attractive within the context of future smart grid framework [19,51–53]. To this end, the PV-grid dc fast charger is investigated from different perspectives—either by simulation or through small pilot projects. For example, L. Liu et. al. [11] present a comprehensive review on PV-grid chargers that focuses on reducing the operational cost of the charging infrastructure. A comparison of different PV-grid integrated system architectures is presented in [54]. While, several microgrid and smart grid based architectural designs to reduce operational cost and to enhance the profit for the system operators are presented in [23,55–60]. Furthermore, M. Gonzalez Vaya, C.-T. Li and J. Zhao et. al. [24,61,62] propose generation cost reduction techniques through the integration of PV and wind power sources. Besides, maximization of renewables, minimization of power loss, optimization of energy management, optimized energy dispatch-the truly major factors [11] to the increment of the operating efficiency of the PV grid integrated system are extensively covered in [21,22,63–66]. 4.1. The power section The general block diagram of the power section of the PV-grid dc fast charging system is shown in Fig. 1. The main components of the system include the PV array with dc-dc converter, energy storage unit (ESU) and the EV charger module —tied together to an internal dc bus through appropriate converting stages. A bidirectional converter stage which links the dc bus with the grid controls the power flow in both directions. 4.1.1. PV power converter with MPPT The energy from the sun is converted to electricity using the PV modules. The most widely used modules are based on poly- or monocrystalline technology [67]. However, recently, the thin film has made inroads into the market, especially for the large PV systems. Despite their lower efficiency, the thin film is easier to manufacture, more cost effective and exhibit better performance at higher temperatures. More advanced technologies such as the heterojunction with 1245

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Fig. 2. The basic MPPT for PV system with converter connected to the dc bus.

size of ϕ is crucial; if ϕ is large, the convergence is fast but it results in large fluctuations in P and vice versa.

intrinsic thin layer (HIT) [68] and multi-junction cells [69] are available, but they are less popular, owing to higher cost. A typical commercial module is rated between 200 and 300 W with an open circuit voltage of about 20–30 V. For the PV-grid charging system, the modules are arranged in series-parallel strings to achieve the required working voltage and power. A unidirectional dc-dc converter is connected as an interface between the PV array and the dc bus as shown in Fig. 2. The variation in solar irradiance (G) and temperature (T) results in nonlinear I–V and P–V characteristic curves. At any time, there exists a unique maximum power point (MPP) that fluctuates continuously as G or T varies. Due to this dynamic, a maximum power point tracker (MPPT) is needed to ensure maximum power is extracted by the dc-dc converter under any environmental condition [70,71]. To achieve this objective, the MPPT algorithm is designed to match the MPP with the converter operating voltage and current. A basic block diagram of a typical PV system with an MPPT is shown in Fig. 2. First, the current and the voltage of the PV array are measured by the current and voltage sensors, respectively. These values are fed into an MPPT block that computes the MPP at that particular sampling cycle. Once found, the MPPT block delivers the reference values for the current (I*) or voltage (V*). Then, the measured power value is compared to the present value of the MPP. If there is a difference between the two, the operating voltage of the converter is adjusted such that it is brought closer towards the MPP. Over the years, numerous MPPT strategies have been proposed [72]. They can be categorized as conventional and non-conventional types. The work in [73] reviews the conventional MPPT methods, which include the perturb and observed (P & O), hill climbing (HC) and incremental conductance methods. The non-conventional MPP methods are based on soft computing, which relies mainly on the search and optimization approach and they have been reviewed by several authors [74,75]. Among the non-conventional MPPTs, the P & O method is the most popular [76,77] due to its simplicity and fast response. The goal of the P & O algorithm is to position the operating point as close as possible to the MPP by climbing the slope of the P–V curve, as illustrated in Fig. 3. First, it calculates the power (P) by sensing the voltage (V) of the PV array, then it provides a perturbation (ϕ) in V, based on the change of power, i.e.:

Xnew = Xold + ϕ × slope (if P > Pold ) [where, X = V orI orD] Xnew = Xold − ϕ × slope (if P < Pold )

4.1.2. Bidirectional dc-ac Converters The bidirectional inverter for EV charging has a dual function: if the power on the dc bus is to be fed back to the grid, it operates as a dc–ac converter (i.e. in inversion mode). On the other hand, if power needs to be drawn from the grid to charge the dc bus, it has to be configured as an ac–dc converter (rectification mode). Thus it must be capable of operating in all four quadrants of the voltage/current regime. Furthermore, it is desirable to operate the inversion mode at a controllable power factor [78]. A typical converter should be able to convert the voltage levels with proper synchronization with the grid and maintain the grid power quality. The two most popular bidirec-

(1) Fig. 3. (a) The movement of operating point in P & O tracking for large perturbation, (b) The movement of operating point in P & O tracking for small perturbation.

where, the slope indicates the direction of the perturbation. Clearly, the 1246

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4.2. Control and protection section

tional dc-ac converter configurations include the isolated or nonisolated type half-bridge and full bridge topologies. For PV-grid charging, isolated or flyback configurations are preferred as they provide galvanic isolation between the ac and dc systems and capable of providing a wide range of voltage level conversion in both directions. Besides, for safety purpose, these converters are required to be equipped with anti-islanding protection schemes as imposed by the international standards [79,80].

The EV charging is controlled by the hierarchy operation of the battery management system (BMS), the charger management system (CMS) and the central control system (CCS), as depicted in Fig. 1. The BMS is normally fitted on-board the vehicle. It carries out many functions: 1) to help the charger module to maintain the accurate charging current and terminal voltage, 2) to estimate the state-ofcharge (SOC) and state-of-health (SOH) of the battery in order to protect against deep discharging/overcharging, 3) to perform cell equalization for safe operation and 4) thermal management of the battery pack [69]. The charger module is controlled by the CMS to maintain the appropriate charging voltage and to avoid unusual dynamic behavior at the output dc bus [91]. For security and integrity of the system, the regular communication between the CMS and the BMS is maintained via the CAN or the PLC protocol [12]. In addition, the CMS also maintains perpetual communication with the CCS for overall system maintenance, optimization, billing and coordination with other charging stations that are scattered in different locations [12]. The anti-islanding protection schemes for the converters at the acdc coupling point can be categorized into two types, i.e. the remote and the local methods. The remote method is realized by establishing the PLC communication between the converter and the remote control station. The goal is to observe any unusual phenomena at the coupling point that calls for protection. Despite being efficient and reliable, the implementation is expensive due to the additional communication hardware. On the other hand, the local methods are simpler and cheaper but they exhibit lower efficiency. The local method can be further subdivided into passive and active methods. The former is based on the detection of the voltage, frequency/phase perturbations

4.1.3. Energy storage unit (ESU) The main function of ESU is to compensate for the intermittent nature of the PV, thus contributing to the stabilization of the bus voltage and increasing the overall system reliability [81]. Typically, each charging station can be equipped with a dedicated ESU; alternatively, a single large ESU can be installed to support multiple stations [31]. In [82], a comprehensive and comparative analysis of the ESU relating to the different power storage techniques, their capabilities, efficiencies and induced investment/maintenance costs is presented. It concludes that for large power applications (≥100 kW), lead acid battery based ESU is most efficient, highly cost-effective and consequently more preferred. On the other side, the determination of the optimal size of the ESU that can store adequate energy at a reduced cost is another fundamental problem addressed in [32,83–86]. For the PV-grid integrated system, a study [30] shows that an ESU with approximately 4 to 7% of the maximum power rating of the PV array can help reducing the output power fluctuations to below 10%. Yet the necessity of integrating the ESU can be debated upon for a number of other reasons—primarily regarding the higher capital and inflated maintenance cost.

4.1.4. DC charger module The dc charger module comprises of parallel off-board converters that interface the internal bus voltage to the output charging bus in the charger module. The output bus voltage is then regulated according to the EV battery pack terminal voltage to charge or discharge the battery pack. The maximum charging current can also be controlled for this purpose. The non-isolated dc-dc converter topologies are more suitable to serve as dc chargers due to their compactness and higher reliability [85]. Fig. 4 shows the general structure of a typical charger module. As mentioned, it is based on a set of modular bidirectional converters, along with their individual protective circuit breakers (CB). The required number of converter units (Unit-1 to Unit-n) is governed by the power rating of the module. The converter needs to be highly efficient to reduce the loss in the process of power transfer to the battery pack. For this purpose, soft switching converters are mostly desired. Additionally, charging voltage and current ripple can be minimized using interleaved configuration to prevent the possible damage to the battery pack.

4.1.5. The dc bus With regard to the dc bus, its application is first reported in [28]. In this work, the dc bus is proposed to interface the PV array, the ESU and the EV battery pack combining other dc powered electronics. The implementation of the dc bus in general leads to higher efficiency and greater system reliability. As obvious, it reduces the necessary power conversion stages. This in return, reduces the loss in the power conversion process and simplifies the control algorithm [87–89]. Furthermore, the dc bus provides seamless power management and increases the prospect of integrating other types of renewable power sources. Despite these advantages, the dc bus and its associated components (e.g. switches, relays, circuit breakers etc.) are more expensive than the ac counterparts, particularly if the bus voltage is very high [90].

Fig. 4. The dc charger module.

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effective than their passive counterparts, the power quality may degrade because of the alteration of the current or frequency output of the converter. For detail evaluation of the remote and the local antiislanding methods, the work in [79] is referred.

and harmonic distortions at the point of coupling. Over and under voltage, over and under-frequency relays are the standard anti-islanding protection requirements and they are generally realized by the software control [92]. However, these methods lack the wider detection zone and need to be assisted by other methods to ensure comprehensive anti-islanding protection. Active anti-islanding methods include power shift, frequency shift, phase shift, current magnitude variation or Sandia voltage shift methods. Although the active methods are more

4.3. The dc charging modes Charging modes are related to the direction of power flow through

Fig. 5. Charging mode scenarios, (a) Supporting grid in peak demand by the PV array (Mode 1), (b) The ESU charging by PV array (Mode 2), (c) Charging the EV by the PV array (Mode 3), (d) The EV charging by the grid and the PV array jointly (Mode 4), (e) Charging the EV and the ESU by the grid and the PV array jointly (Mode 5), (f) The EV charging solely by the grid (Mode 6), (g) The EV and the ESU charging by the grid (Mode 7), (h) The V2G operation (Mode 8), (i) The termination of EV charging (Mode 9).

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the system. In each mode, the power flow direction is determined to balance the power demand and generation throughout the system. To achieve this purpose, a set of predetermined voltage and current thresholds are required to switch the modes as demonstrated in [93]. For the convenience of notation, let the voltage references for dc bus to be Vdc_bus_1, Vdc_bus_2 and Vdc_bus_3. The load at the distribution transformer is iTR and the maximum load is defined by iTR_max. The EV battery voltage and the threshold for terminating the charging are VB and VB_THR, respectively. That is, when VB reaches VB_TH, the charging is turned off by the switched converter. Besides, the ESU voltage and the low threshold are defined by VESU and VESU_TH. When VESU is greater than VESU_TH, the ESU is charged by the system. For the PV-grid charging system that employs ESU, there are nine possible charging modes stated below and illustrated in Fig. 5 [2,94].

•

this case, as shown in Fig. 5(g), the grid supports the charging singlehandedly as the PV array power is unavailable.

VDC BUS < Vdc bus 1, VESU < VESU THR, iTR ≠ iTR max

•

At peak demand situations in Mode 8, the EV battery pack feeds back the grid in V2G scheme. It is also possible to multiply the reverse power flow by utilizing the available power from the PV array and the fully charged ESU. This is shown in Fig. 5 (h).

Vdc bus 3 > VDC BUS > Vdc bus 2, 0 < VB < VB THR, VESU > VESU THR, iTR = iTR max

•

In Mode 1, when no EV is connected to the charger and the ESU is fully charged, the entire PV power is sold to the grid. This situation is shown in Fig. 5(a). Here,

Finally, in Mode 9, when the PV power is not sufficient and the grid is at peak demand, the EV charging operation is terminated as shown in Fig. 5(i). That is,

Vdc bus 3 > VDC BUS > Vdc bus 2, VB = 0, VESU > VESU THR

VDC BUS < Vdc bus 1, 0 < VB < VB THR, iTR = iTR max

•

However, if no ESU is installed to stabilize the internal bus, six modes are possible [2,94]. This situation is very much similar to the previous one except for the disconnected ESU.

In Mode 2, when no EV is connected and the ESU is partially or completely depleted, the PV power is drained to charge the ESU as shown in Fig. 5(b). As the ESU becomes fully charged, the system returns to mode 1. In this mode,

•

Vdc bus 3 > VDC BUS > Vdc bus 2, VB = 0, VESU < VESU THR, iTR ≠ iTR max

•

Vdc bus 3 > VDC BUS > Vdc bus 2, VB = 0

•

If the EV is connected and the PV array is generating sufficient power, the EV is charged solely by the PV array as shown in Fig. 5(c). This situation is depicted as mode 3 charging where the ESU remains fully charged. Here,

•

If there is a shortage of PV array power, the excess power is drawn from the grid and the system enters into Mode 4. Consequently, the EV is charged by both the grid and the PV array as shown in Fig. 5(d). If the grid is at the peak demand, the system enters into mode 9. The load sharing function is implemented through the switch mode converters. The ESU is assumed to remain in fully charged condition. Similarly,

However, if the PV array is not generating sufficient power to charge the EV, the system operates in Mode 3. In this mode, the grid provides the remaining power to balance the charging power demand.

Vdc bus 2 > VDC BUS > Vdc bus 1, 0 < VB < VB THR, iTR ≠ iTR max

•

Vdc bus 2 > VDC BUS > Vdc bus 1, 0 < VB < VB THR, iTR ≠ iTR max

•

When the EV is connected, the system enters into Mode 2. In this mode, the PV array is generating sufficient power and consequently the EV is charged solely by the PV array. If the power generation surpasses the demand, excess power is fed back to the grid. Here,

Vdc bus 3 > VDC BUS > Vdc bus 2, 0 < VB < VB THR

Vdc bus 3 > VDC BUS > Vdc bus 2, 0 < VB < VB THR, VESU > VESU THR

•

In Mode 1, when no EV is connected to the dc charger, the PV power is transferred to the grid. Hence,

If the PV power is not available for technical or any unfavorable weather conditions, Mode 4 is executed and the EV is charged solely by the grid. Similarly,

VDC BUS < Vdc bus 1, VESU < VESU THR, iTR ≠ iTR max However, if the ESU is partially or completely depleted, the system executes Mode 5. In this mode, both the ESU and the EV are charged by the PV array and the grid jointly as shown in Fig. 5(e). Hence,

•

Mode 5 depicts the situation where the EV is operated in the V2G scheme to support the grid at peak demand.

Vdc bus 3 > VDC BUS > Vdc bus 2, 0 < VB < VB THR, iTR = iTR max Vdc bus 2 > VDC BUS > Vdc bus 1, 0 < VB < VB THR, VESU < VESU THR,

•

iTR ≠ iTR max

•

When the PV power becomes unavailable and the ESU is fully charged, the charging of the EV is executed solely by the grid in Mode 6 as shown in Fig. 5(f). Here,

Finally, in Mode 6, when the PV power when PV power is not sufficient and the grid is at the peak demand, the EV charging operation is terminated. That is,

VDC BUS < Vdc bus 1, 0 < VB < VB THR, iTR = iTR max

VDC BUS < Vdc bus 1, VESU > VESU THR, iTR ≠ iTR max

•

4.4. Charging profiles Mode 7 depicts the situation when both the ESU and the EV are charged simultaneously as the ESU is partially or fully depleted. In

The over or under charging can cause permanent damage to the EV battery pack; hence the need for precision control of the charging 1249

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around 98.5–99% of the original value [101]. Additionally, the thermal state of the battery is maintained with the help of temperature sensors and thermal management module. The module executes heating or cooling mechanism to control the battery temperature. Besides, the cell equalization and interaction with the CMS is also performed by the BMS.

5.1. Methods to estimate SOC The coulomb counting is the most widely used method for SOC estimation [102]. It calculates the SOC by observing the total charge transferred to or from the battery. Despite its simplicity, the accuracy highly depends on the correct measurement of the current and the initial charging state of the battery. Furthermore, errors from selfcharging and discharging losses are prominent. The enhanced coulomb counting methods proposed in [102] are designed to estimate and compensate for these losses. The Kalman filtering (KF) is another popular real-time estimation method. However, it requires the knowledge of the electric model of the cell and an extensive computation of their parameters. The extended Kalman filtering (EKF) is the nonlinearization of the Kalman filter to adapt the non-linear behavior due to the changes in the battery characteristics. In [103] the authors reduce the order of the EKF by simplifying the battery model as an effort to reduce the calculation time. More accurate SOC estimation can be achieved by applying sigma point Kalman filtering (SPKF) presented in [104] without significant increment in the computational complexity and cost. The OCV based SOC estimation methods provide high precision measurement. However, the battery needs to be in a long idle period to reach the balance state. Additionally, the non-uniformity of the OCVSOC relationship makes it less reliable for diverse applications.[105] Consequently, the OCV-SOC curve needs to be calibrated for individual batteries, resulting in a time-consuming process. To overcome these issues, OCV method is generally combined with other estimation methods. For example, P. J. Tulpule and S. Lee et. al.[18,105] formulate a unique OCV-SOC relationship that combines the EKF

Fig. 6. Voltage and current profile in three level safe charging of EV battery bank.

voltage and current profiles [95,96]. Generally, the charging can be done independently in any of the three distinct charging profiles [95]: the constant-voltage (CV) charging, the constant-current (CC) charging or a combination of both. In CC charging, the system draws excessive power at the beginning of the charging operation. If not properly controlled, the high current injection at low charging state might reduce the lifecycle of the battery pack. This situation can be avoided in CV charging. Additionally, there is no risk of overcharging the battery as it draws a small amount of current throughout the charging state. However, in doing so the charging time is sacrificed to a great extent. Hence, to overcome these inherent drawbacks and facilitates fast and safe charging, T. Kang et. al.[97] combine the CC and the CV charging by introducing the charging profiles as shown in Fig. 6. They are defined as an initial pre-charging stage, followed by the intermediate CC stage and the CV charging stage at the end. During the pre-charging period, the current is increased in small steps to slowly raise the battery voltage to a certain level, known as the constant current threshold. This ensures controlled power injection at the beginning and protects the battery from damaging. Beyond this point, the charger is controlled to provide a high value of constant current. Subsequently, the battery is charged very quickly and reaches 80% of its SOC. At this point, the charger is forced to move into the CV stage to limit the current and safeguard the battery from overcharging. 5. Functions of the battery management system (BMS) The functional building block of BMS is shown in Fig. 7 which provides an insight into the BMS functions. Besides providing the feedback for required charging current and voltage [98], the BMS is deployed to protect against deep discharging or overcharging by estimating the state-of-charge (SOC) and state-of-health (SOH) of the battery. Estimating the SOC is extremely important as erroneous estimation may lead to severe damage to the battery pack due to overcharging or deep discharging. Overcharging is dangerous for Li-ion batteries for several reasons: lowering life-time and safety, decomposition of electrolytes and formation of lithium dendrites [99]. Furthermore, extremely low charging state can oxidize the negative electrode copper and dissolve in the electrolyte [99]. To avoid this situation, precise measurement of cell voltages and battery current is required. As the open circuit voltage (OCV) OCV-SOC curve is relatively flat around the operating range of the battery, the voltage measurement has to be very accurate. For the LiFePO4 battery, the precision is expected to be 1–2 mV [100]. For other types, the tolerance is higher due to the more slanting nature of the OCV-SOC curves. In general, the acceptable current measurement accuracy is

Fig. 7. The BMS key functional building blocks.

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completely disconnecting the battery from the charging module in case of emergencies. The thermal controller module incorporates temperature sensors along with cooling and heating mechanisms controlled by the thermal management module. The gate driver module is directly controlled by the master DSP to control the converter units for a specific voltage and current. The number of gate drivers is restricted by the number of available PWM channels from the master DSP controller. Hence multiple numbers of slave DSPs’ in gate driver module might be required to handle a higher number of converter units. The I/O controller module in the CMS characterized by a slave DSP is liable for handling the display of information and input from the user interface. The necessary charging information on the display is to be provided by a joint action of the master DSP in the BMS, CMS, and CCS. A dedicated V2G controller is also installed for efficient management of the V2G operation. Communication with the BMS and the CCS are established with the help of communication module through a CAN bus or a PLC [123]. If necessary, the CMS can further relay the operational data to the CCS through a CAN bus. This data is used by the CCS for demand side management, smart metering, and V2G operation control. The thermal state of the module is also sent back to the CCS for constant observation and safety of the overall system. The CCS, in particular, is liable for overall system control, communication with the other station controllers, handling external requests along with the control of the voltage and current output of the charger.

and coulomb counting method along with a measurement noise model. The temperature dependence issue of the OCV-SOC curve is addressed in [106] where the authors propose a temperature based internal resistance battery (Rint) model. The parameters are determined through a dynamic stress test (DST) and federal urban driving schedule (FUDS) at different temperatures. Several artificial neural networks (ANN) and fuzzy logic based SOC estimation methods are proposed in [107–110]. The ANN methods can be adaptive or non-adaptive and have the advantage of being independent of the battery model used for SOC estimation. This enables the ANN methods to be applied for all kind of batteries in all situations. However one of the disadvantages of the ANN algorithm is that it has to be well-trained before implementation. A comparative analysis is presented in [111] for four major model based SOC estimation methods namely Luenberger observer, sliding mode observer, EKF and SPKF. The algorithms are analyzed for voltage disturbances, current disturbances and current sensor drifts. Furthermore, to estimate the comparative speed of the algorithms, the dynamic convergence time to the SOC are measured. Other comparative and detailed analysis on SOC estimation methods can be found in [98,112,113]. However, for pure EV, the coulomb counting method supported by OCV-SOC look up table should provide sufficient and satisfactory SOC estimation due to the large size of the battery pack [99]. 5.2. Battery equalization/cell balancing

6. The dc charger module

The voltage imbalance in the series-connected battery cell is due to the difference in temperature, internal resistance, overcharging and low discharging state of the individual battery cells. Furthermore, aging of the battery worsens the voltage imbalance during charging and discharging periods. Particularly, for the Li-ion cell [114], it needs to be operated within a safe operating region defined by the temperature (−20 °C to 60 °C) and the voltage limits (1.8–4 V), as shown in Fig. 8. Outside the desired window, the battery is considered overcharged, leading to the formation of lithium dendrites or damaged through decomposition and dissolution. Hence, the cell voltages are scrutinized by the BMS at a regular interval to ascertain if overcharging or low charging state occurs. The measurement facilitates the voltage balancing of the individual cell. The voltage equalization methods can be classified into active and passive methods. The active methods can be further subdivided into dissipative and non-dissipative techniques. A general discussion on cell equalization methods is presented in [115], while a more comprehensive review of the balancing methods can be found in [116]. MATLAB simulation-based comparison of cell balancing methods is presented in [117]. In [118], an effective battery equalizing method based on Cuk dc-dc bidirectional converter is proposed. The converter is controlled by a PWM integrated microprocessor module embedded with a fuzzy logic based control algorithm which makes the equalization process fast, adaptive and independent of battery model. Other highly efficient charge equalization methods for series packed Li-ion EV battery cells can be found in [119–122].

6.1. The soft switching dc-dc converter The primary function of a dc charger module is to match the dc bus voltage to the EV battery so that the charging can be effectively controlled. As depicted in the system architecture, the charger module comprises of several units of the bidirectional dc-dc converter. The bidirectional topology is used because of the future expectation that the EV charger will include the V2G function. As the converter is operated at the high switching frequency (75–250 kHz), switching losses (turnon and turn-off) are dominant. Hence, soft switching converters are preferred [124]. Soft switching techniques significantly reduce the EMI

5.3. BMS functional interaction with the CMS A generalized framework for the possible functional blocks of a CMS is shown in Fig. 9. The digital signal processor (DSP) is the core and functional center in the CMS. Each building block module may include a DSP/microcontroller in slave configuration assisting the central master DSP increasing its functional capability. The computation load can be distributed among the slave DSP modules to protect the master DSP from overloading and slowing down. Using the information feedback from the BMS, the CMS precisely controls the charging of the EV battery pack. The voltage and current monitoring modules are used for this purpose. Besides, the CMS is capable of

Fig. 8. The safe operating window of Li ion batteries.

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can be operated at moderate duty cycle ratio (D) leading to the lower EMI and voltage/current stress on the power switches. The disadvantage could be the conduction loss at high frequencies because of the higher number of components and the longer conduction path. Moreover, half bridge configuration of the circuit could introduce trapped energy problem lowering of the expected efficiency. The soft switching range of operation is also limited by the size of the capacitor (CP). However, the circuit is attractive for its compactness and relatively simple control. In [128], the authors propose a half bridge bidirectional topology, as shown in Fig. 13 which is designed to operate in the discontinuous mode (DCM) for minimization of the inductor size. However, unlike pure DCM mode, the inductor current goes towards negative before it starts to rise again. Soft switching turn on is achieved by using a gate signal complementary control scheme to divert the current through the anti-paralleled diode of the inactive switch. For soft switching turn off, a lossless snubber circuit is added across the switches. Interleaved technique is adopted to reduce the inductor size as well to decrease the input current ripple. The complimentary switching scheme facilitates the high switching frequency operation of the circuit by reducing the heat sink size. Sophisticated and subtle parametric design of the inductor and snubber capacitors are required for optimization of turn on and turns off losses. Failure to find the correct values for inductor and capacitors would create charging and discharging imbalance situation in the circuit. Additionally, at higher switching frequencies, the soft switching turn on would be difficult for a narrow range of discharging time for the snubber capacitors. The three level ZVT topology in [129] (Fig. 14) applies two auxiliary resonant networks to execute zero voltage switching (ZVS) for all power switches (i.e. S1, S2, S3, S4). Each resonant network consists of a set of two resonant inductors (Lr1, Lr2 & Lr3, Lr4), one resonant capacitor (Cr1 & Cr2) and one auxiliary switch (Sa1 & Sa2). The ‘three level’ configuration reduces the voltage stress on the power switches significantly for medium and very high power applications. The presence of multiple resonant circuits increases the probability of losing soft switching condition due to the charging and discharging imbalance. The conduction loss at light loads may be significant. Due to a large number of components including the inductors and capacitors, the size and the volume of the circuit are large. Additionally, the adjustable dead-time to compensate step up or step down voltage ratio would introduce higher control complexity.

Fig. 9. The CMS key functional building blocks.

by eliminating large variations of di / dt and dv / dt . Additionally, to ensure the battery is efficiently charged, the input current ripple and the output voltage ripple of the converters should be minimum. To achieve this, the interleaved design can be adopted. Furthermore, due to cost factor, the non-isolated bidirectional topology is preferable. In the non-isolated zero voltage transient (ZVT) topologies, the auxiliary resonant networks are used for soft switching operation at the commutation points. The auxiliary network consists of resonant inductors and capacitors, arranged in a series or parallel formation. Zero voltage turn on (ZVS) and turn off conditions are achieved through the resonance among the inductors and capacitors. Other soft switching arrangements include resonant networks, different types of active and passive snubber cells.

7. Impact of fast EV charging

6.2. Review of selected soft-switching topologies

7.1. Impact on the grid and distribution system

A high voltage conversion ratio bidirectional dc-dc converter (Fig. 10) is proposed in [125]. Its main feature is the ability to operate in a wide voltage range. The soft ZVS is implemented using a resonant circuit consisting of an inductor (La), a capacitor (Ca) and two high power auxiliary switches. The mode of operation of the converter depends on the direction of the inductor current. Interleaved design can be adopted for reduced ripple voltage. However, this circuit is prone to high conduction loss as the inductor La and Ca is positioned in the power flow path for a significant portion of the operation cycle. The circuit in [126] (Fig. 11) applies soft switching technique by using an auxiliary resonant circuit consisting one resonant inductor (Lr), two capacitors (Csa & Csb) and two switches (Sc & Sd). The circuit is operated in CCM mode to limit the peak inductor current and to reduce the conduction loss. In order to minimize the input current ripple and the size of the inductors, interleaved design is adopted. However, the increasing loss at high power applications due to the reverse recovery loss of the body diodes thus lowering the efficiency could be sighted as a disadvantage. The bidirectional converter in [127] (Fig. 12) utilizes an LCL auxiliary resonant network characterized by the inductors- Lr1, Lr2 and capacitor- CP. Due to high step up and step down ratio, the circuit

A considerable number of studies are carried out [8,130–135] to address the effect of EV charging on the existing power system. The rapid, uncontrolled and random charging pattern may lead to voltage deviation, distribution losses, and degradation in the power quality. The transformer and power lines lifetime may be shortened due to the overloading, and system instability can occur. Furthermore, the harmonic currents, voltage deviations, phase imbalance, dc offset, phantom loading and stray flux problems are the major issues

Fig. 10. The ZVT circuit with single inductor and a capacitor in auxiliary network.

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Fig. 11. The ZVT circuit with single inductor and two capacitors in the auxiliary network.

Fig. 12. The ZVT circuit with LCL auxiliary network.

Fig. 14. Two auxiliary resonant circuit based ZVT BDC.

overloading due to the EV integration purely depends on the situation of the network. One part of the network can accommodate 100% of the EV integration, while another part may not due to the insufficient capacities of the individual components. Hence, micro level analysis to identify system sensitive points is recommended to avoid adverse network conditions. A number of studies can be found in the literature which discusses the impact of EV charging on the supply and demand balance. In [137] the study assumes that all vehicles in Perth metropolitan area are EVs and subsequent analysis is carried out to find the impact of charging on the existing grid. It reveals that the peak demand is shifted to a new point on the demand curve. This point is featured as the home arrival time of the electric vehicles when the EVs are connected to the grid for charging. The work suggests that to maintain the demand-supply balance, 93% of the vehicle fleet should be charged during the offpeak time. Besides, on a day with average demand (i.e. week holidays), at least 41% of EV load should be shifted to the off-peak. However, this study considers only Level 1 and Level 2 charging schemes. Thus, the results suggest that for high power dc fast charging systems, the effect on the demand-supply balance could be more impactful. Consequently, larger PV and ESU are required to balance the system, as suggested in Section 4.1.3.

Fig. 13. The Interleaved design of BDC.

contributing to the degradation of the power quality (PQ). In [134], the authors show that the higher harmonic current introduced by the nonlinear EV charger has an adverse effect on the PQ. Obviously, these problems affect the performance and longevity of the distribution equipment. Harmonic current components induce an additional i2R loss in the power transformer windings and cables. Additionally, the eddy current loss in the transformer core results in an abnormal temperature rise, thus reducing the power transfer efficiency. It also affects other distribution equipment such as the capacitors, meters, relays, switch gears, current and voltage transformers. A comprehensive case study on the effect of the EV charging on thermal limitations of system components and network assets is found in [136]. The study incorporates systems in a densely populated urban area with high load density as well as in a rural area with highly dispersed loads. It considers the slow charging points (i.e. ac level 1) connected to LV distribution system as well as the fast charging stations with several points connected to a medium voltage distribution network. Further, the study also covers the V2G operation. It concludes that the required network reinforcement cost can be increased up to 19% in peak hours. However, it also suggests that a significant reduction of the above cost is achievable if smart charging scheme is applied. In addition, due to intermittent nature of the renewables, the power utilities are constantly facing the challenge to stabilize the grid that incorporates a large amount of RE resources. The fast-responding power electronic interface of the charger and the ESU provides effective ways to deal with source intermittency [135]. However, if the vehicle charging is unconstrained [9], the effect on the performance, stability and efficiency of the electric grid can be substantial. Network assets

7.2. Remedial measures The IEEE Standards 519–1992, IEC 61000-3-12/2–4 or EN 50160:2000 describe the recommended practices and requirements for harmonics control in the power system [138]. A recent comprehensive study presented in [6] discusses the impact of the harmonic components on the grid for fast charging of multiple electric vehicles. It is reported that the commercial on-board charger still has poor PQ as it pollutes the system through harmonics [139]. The effect of harmonics alone might be considered as the reason to terminate the power transfer between the EV and the utility grid. Furthermore, the effect of an increase in load and low power factor on the distribution grid should be considered. As the load increases with the number of 1253

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setbacks, the long-term future of the V2G remains optimistic.

vehicles, the harmonic distortion worsens. This raises safety and economic concern, as transformers and feeders are prone to degrade the PQ. A remedy to the injection of high harmonic current in the distribution system is proposed in [140]. The input current quality is improved by modifying the charger control system by introducing an interim voltage source inverter (VSI) that restricts the harmonic components of the current to be fed back into the feeder. Additionally, current control of the inverters (i.e. coupling point inverters or the ac-dc stage of the dc charger) is more feasible than voltage control as it ensures improved power factor and robust suppression of the transient currents [80]. Level 3 chargers with higher efficiencies are expected to alleviate power quality issues and reduce charging time [139]. S. Rahman et. al.[141] claim that uncontrolled charging poses immense voltage deviations and the PQ issues in such a degree that even 10% of additional penetration cannot be absorbed. Hence, a valley filling approach of the system load curve is introduced. This approach releases the stress on the transmission lines and no replacement of components is required. Moreover, the coordinated charging scheme reduces the power loss, voltage deviations, and subsequently improves the PQ. Hence, the demand curve is flattened and the peak demand situation can be entertained. Besides these, K. Clement et. al.[142] suggest a smart multiagent metering system to achieve above targets. The demand peaks raised by the EV load can be partially met by means of the ESU. G. Joos et. al.[143] propose a flywheel and a super capacitor energy storage devices to bridge the gap between the charging station demand and the power grid. However, the lead acid battery storage is more suitable and cost efficient as already mentioned in Section 4.1.3. Besides, the development of smart grid environment and implementing the V2G concepts would certainly help to resolve many of the prevailing grid problems.

8. Conclusions This paper discusses the integration of RE sources into the EV charging system. In particular, the architecture and configuration of the PV-grid integrated dc fast charging are investigated. Several aspects of the control and the protection of the system components are explained. More specifically, two important parts of the control, namely the battery management system (BMS) and the charger management system (CMS) are discussed and their interactions are highlighted. The paper also recommends the installation of the ESU to assist in balancing the electrical grid. Furthermore, the possible bidirectional non-isolated dc-dc converter topologies that can be adopted as the dc chargers are proposed. On the grid side, the EV charging impacts on the distribution system and their remedies are briefly discussed. In addition, the future of the V2G and its prospects are mentioned. Based on this discussion, it can be deduced that it is high time to unify the fast charging standards worldwide for the benefits of the users and the manufacturers. Besides, to provide the EV owners with the similar experience as filling the fuel for the ICE vehicles, the charging time needs to be reduced. With the expected growth in the EV fleet, the fast charger network should be extended, while their power rating needs to be increased. This would remove the driving range anxiety, which is of concern to most EV users. In parallel, the performance of EV battery requires improvement, along with the BMS. Furthermore, there is a need to develop more efficient smart energy management schemes to accommodate the proliferation of the EV into the existing electrical grid structure. There are numerous prospects of work in this aspect, particularly using rule-based algorithms like deterministic and fuzzy logic, and optimization-based algorithms like genetic and particle swarm. The rule-based algorithms support online operation that helps to improve the overall efficiency, control, flexibility and security of the system. This aspect, which is not fully covered in this paper, constitutes an important feature—if the EV charging is to be part of the future smart grid systems. These scopes should provide interesting topics for future research in this area.

7.3. Future directions on V2G The V2G scheme provides an alternative solution to the need for the ESU. By utilizing the EV battery as a storage, an energy buffer is created. During excessive power flow from the PV, the EV battery acts as the storage for the excess energy. Further, when the power from the PV is inadequate, the EV battery compensates for the energy shortage by discharging its energy back to the grid. Besides, the energy transfer from the EV to the grid can be considered when the price of grid electricity is high enough to make a profit. Despite this attractive feature, a number of issues have to be resolved [12]. First, most of the EVs from diverse car manufacturers are not capable of adopting the V2G because the chargers are unidirectional. Furthermore, most charging systems lack the advanced communication modules required for the protocols that ensure safe and reliable V2G operation. They need to be equipped with smart meter and communication modules to safely relay the information in between the CMS and the CCS. Second, the combined battery capacity of the EV fleet on the road, in the aggregate, must be sufficient to function as an energy buffer to the PV-grid charging system. The EV fleet can be considered as a dynamic distributed energy storage for the grid. However, currently, the number of EV are far too few for a successful V2G implementation. Third, the charging and discharging of the EV has to be programmed to meet the power demand of the grid. This requires an advanced scheduling technique, which is quite challenging due to the random mobility of the EV fleet. However, the major concern of the EV owners is the impact of the V2G on the EV battery pack itself, as discussed in [144]. The paper concludes that the EV battery degradation is severe in the case of bulk energy service and high depth of discharge. Therefore, until the battery technology is matured, the V2G may yet be a viable option. For now, the ESU is needed to stabilize the internal bus voltage. The presence of the ESU leads to a less complex control of the intermittent PV power and increases the overall system reliability [81]. Despite these temporary

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