Frequency regulation service of multiple-areas vehicle to grid application in hierarchical control architecture

International Journal of Electrical and Computer Engineering (IJECE)
Vol. 11, No. 6, December 2021, pp. 4597~4609
ISSN: 2088-8708, DOI: 10.11591/ijece.v11i6.pp4597-4609  4597
Journal homepage: http://ijece.iaescore.com
Frequency regulation service of multiple-areas vehicle to grid
application in hierarchical control architecture
Paramet Wirasanti, Suttichai Premrudeepreechacharn
Department of Electrical Engineering, Faculty of Engineering, Chiang Mai University, Thailand
Article Info ABSTRACT
Article history:
Received Jun 17, 2020
Revised May 11, 2021
Accepted May 28, 2021
Regarding a potential of electric vehicles, it has been widely discussed that
the electric vehicle can be participated in electricity ancillary services.
Among the ancillary service products, the system frequency regulation is
often considered. However, the participation in this service has to be
conformed to the hierarchical frequency control architecture. Therefore, the
vehicle to grid (V2G) application in this article is proposed in the term of
multiple-areas of operation. The multiple-areas in this article are concerned
as parking areas, which the parking areas can be implied as a V2G operator.
From that, V2G operator can obtain the control signal from hierarchical
control architecture for power sharing purpose. A power sharing concept
between areas is fulfilled by a proposed adaptive droop factor based on
battery state of charge and available capacity of parking area. A nonlinear
multiplier factor is used for the droop adaptation. An available capacity is
also applied as a limitation for the V2G operation. The available capacity is
analyzed through a stochastic character. As the V2G application has to be
cooperated with the hierarchical control functions, i.e. primary control and
secondary control, then the effect of V2G on hierarchical control functions is
investigated and discussed.
Keywords:
Adaptive droop control
Frequency regulation
Hierarchical control
Vehicle to grid
This is an open access article under the CC BY-SA license.
Corresponding Author:
Paramet Wirasanti
Department of Electrical Engineering
Chiang Mai University
239 Huay-Kaew Road, Suthep, Muang, Chiang Mai, 50200, Thailand
Email: paramet.w@cmu.ac.th
1. INTRODUCTION
Recently, the electric vehicles (EVs) are taking more market share in a light-vehicle transportation.
It has been foreseen that the high capacity EV battery has a potential to participate and support power system
operation [1], because most of the vehicle usage is in an idle state for a long parking period, e.g. during office
hour or home parking [2]. This kind of behavior leads to a vehicle to grid (V2G) concept that the EVs can
take the power from the grid or inject the power into the grid, while they are connected to the power grid.
To take an advantage of the V2G concept, the electricity ancillary services are widely discussed.
The authors in [3]-[7] have been introduced that the EVs can participate in the following services, i.e. system
regulation, peak shaving, reactive power compensation, and renewable energy support. Form the list of
services, it shows that the V2G concept is able enter in a conventional service of transmission system
operator (TSO) and in a smart grid oriented service for distribution system operator (DSO). The conventional
frequency regulation service, Tenga et al. [8] and Mu et al. [9] has focused on a primary response of
frequency regulation with the level of battery state of charge (SoC). Su et al. [10] and Falahi et al. [11]
introduced voltage control via reactive power compensation from EVs in distribution system. Tomić and

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Int J Elec & Comp Eng, Vol. 11, No. 6, December 2021 : 4597 - 4609
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Kempton [12] has analyzed the economic of the V2G concept, when providing system regulation and peak
shaving. Those mentioned study examples are based on the idea that the EVs are considered as an aggregated
mobile energy storage model. Among variety services of the V2G application, this paper has pointed out the
frequency regulation service, because this service is related to power system stability and required more
power than the service for DSO. Moreover, it has three time control interval, i.e. primary control, secondary
control and tertiary control, that the EVs can be selected for the participation.
The recent studies of V2G in the part of frequency regulation are more oriented to control
architecture of load frequency control. The area control error (ACE) is also considered. Alhelou et al. [13]
and Liu et al. [14] have structured the control area into two interconnected areas, which one area is equipped
with the V2G. However, the EVs are considered as aggregated model. In the same way, Liu et al. [15]
utilized two interconnected areas for the study. The stochastics behavior is included in this study. The idea of
decentralized model of EVs model in the term of parking area is introduced in [16] and [17]. The potential
capacity of each parking area is analyzed. The decentralized V2G system is also presented in [18]. The study
focused on the information sharing between EV stations in order to design power sharing. This research work
is studied based on a single ACE.
Bearing in mind that the connected location of EVs is spread out in distribution grid. Thus, this
article is pointed out that the EVs model cannot be considered as a single aggregated model. Furthermore, the
conformation with the frequency control architecture on TSO level has to be taken into account. Figure 1
shows an overview of proposed architecture. The complete control area consists of three levels [19]. The unit
level is a generation unit, which primary control (PC) is equipped in every generation unit. The higher level
is local level, the secondary control (SC) is located in this level. The highest level is the supervisory level or
tertiary control level (TC). The reference signal is sent from the highest level to lower level. When the V2G
application enters in the hierarchical control architecture, it is located at the unit level in distribution network.
To equip with the power grid, there must exist a coupling factor similar to PC. In the case of EVs, the
coupling factor needs to be driven from the grid side by frequency.
Regarding the coupling factor, a droop factor is generally used, and it has to be a function of SoC. In
current researches, it found that there are two control strategies, i.e. the sectional control curve and the linear
control curve. For the sectional control curve, [20] presented two difference droop factors for charging
process and discharging process. Zhu et al. [21] has divided more section based on the idea of increasing
flexibility. It has been shown that the sectional control curve satisfied the requirement under different
circumstances, when the EVs is concerned as aggregated model. For the linear control curve, the key element
in this strategy is the regulation- or multiple factor that is utilized for the adaptation based on SoC. Liu et al.
[22] used a parabola function to define the relation between droop factor and SoC. Furthermore, the linear
control curve can be a constant factor as in [23] and [24]. Both researches have used it in a combination with
a scheduled charging power as an additional energy management. To conclude, the sectional control curve
has an advantage according to flexibility. On the other hand, the droop adaptation of the linear control curve
is simply adjusted by defining the function of multiple factor based on SoC. Note that the studies of droop
factor of V2G application are mostly aggregated EVs models.
Figure 1. Hierarchical control architecture with multiple-areas of V2G
Unit Level
(TSO)
Unit Level
(DSO)
PC PC PC
V2G based on
PAs
SC
TC
Local Level
Supervisory Level
M

Int J Elec & Comp Eng ISSN: 2088-8708 
Frequency regulation service of multiple-areas vehicle to grid application in … (Paramet Wirasanti)
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According to proposed multiple-areas architecture in Figure 1, this paper is pointed out that the
droop factor in each area has to be independence from each other. Thus, the conventional setting concept of
droop factor is taken into account, which the setting is depended on the sizing of power plant [25]. Larger
plant capacity has to be response more than smaller plant. On the same hand, this can be implied for the V2G
application related to parking area. By this concept, the power sharing between parking areas is worthy for
the investigation. The adaptation of droop factor is clearly based on battery SoC. The practical charging
character is used to define the character of multiple factor, that there is a constant power period and slowly
decreasing power period. In addition, the dead band and the relay function are implemented in V2G droop factor in
order to assign the stop operation band and protect the oscillation at the transition point, respectively.
To summarize, the main contribution of this work are as follow:
 The structure of multiple-areas of V2G application in hierarchical control architecture
 The complete examination of the V2G effect on the frequency regulation, i.e. primary control and
secondary control
 The power sharing including the modelling of available capacity of each parking area
The paper is organized as follow: section 2 provides the structure of conventional hierarchical
control and the V2G control in the part of frequency regulation. Section 3 explains the V2G operation and its
mathematic description. Section 4 proposes the stochastic of parking area model and the calculation of
estimated available capacity. Section 5 presents the implementation of proposed model in DIgSILENT Power
Factory program and the validation of system frequency response. Section 6 presents two case studies, step
response test and continuous test. The simulation results are discussed. Lastly, the conclusions are drawn.
2. HIERARCHICAL CONTROL SCHEMATIC WITH V2G FUNCTION
Understanding the V2G for frequency regulation service, the power system hierarchical control and
the control strategy of EV have to be clarified. The control schematic of both functions in one control area is
displayed in Figure 2, which is consisted of the primary control, the secondary control and the EV control.
The primary frequency control is generally equipped with all generation unit. The primary control is in
charge of stabilizing the power system frequency to a set value after disturbance or load change in the
system. This function is performed by a coupling function, called droop factor. The droop factor has a
responsibility to balance the injection power of the generator and load. It has to mention that the primary
control function does not include the system frequency restoration to the reference values. To restore the
frequency back to the nominal value, this action is done by to the secondary control. This process measures
the system frequency and compares with the reference value. The frequency error is converted to the power
via the droop factor. The output of the secondary control droop is regulated via PI controller and shared to the
generation unit in order to adjust the power for the frequency regulation. In addition to the frequency service,
the secondary control is also managed the power exchange between neighbor control areas.
Figure 2. Hierarchical- and EV control block diagram for frequency regulation
PI
-
Gen
PI
Δω1
ωref
ωact, 1
fref
-
Pref,A12
ωm1
Kf,Gen1
f
P
Δω1
Pref, 1
ΔfA1
ΔPA12
fact, 1
PA12
ΔPA1
-
Pact, 1
-
ΔPA12
'
1/Kf,A1
f
P
Droop
Droop
Primary Control of Generator Unit Secondary Control of Area 1
GRID
1
Sharing
factor
Poffset, 1
(Supervisory)
Adjust Factor
PEV,load
fref +
_
PEV
Adaptive
Control
Limit
PT1
+
_
SoC calculation
EV/PA Control
fact, 1

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In a part of the EV control as frequency regulation service, the control block diagram is shown in
Figure 2 as well. It is obvious that the cooperative with battery SoC is required. As noticed in Figure 2, the
control is a function of battery SoC. This means that the charge/discharge rate of EV for frequency regulation
is depended on SoC level. Further detail of this adaptive control block is provided in the section 3. Next, the
first order characteristic (PT1) is implemented in order to describe the character of EV. Lastly, the limitation
block is needed as a grid interface. It can be implied that the limitation block is a bidirectional inverter. To
summarize, the EV can be directly joined the hierarchical control operation, which the V2G mode is operated
as a support for frequency regulation.
3. PORPOSED V2G OPERATION FUNCTION IN FREQUENCY REGULATION
In this section, the function and mathematic description in EV model part is further discussed. In
Figure 2, the main part of the EV model is an adaptive control block. The function of this block is to convert
the frequency difference between grid frequency and reference frequency to an injected power or a consumed
power in order to support the frequency regulation via a droop factor of EV (KEV), which the KEV is a slope of
regulation character. In addition, the dead band function is defined in the operation curve in order to set the
zone that EV should not be active for frequency regulation [26]. The dead band is the frequency area between
ΔfMax and ΔfMin. The frequency dead band can be set according to the tolerance band, e.g. ±1% of nominal
frequency. The power regulation character is summarized as in Figure 3.
Figure 3. Character of V2G frequency regulation mode
To adapt the regulation character according to the battery SoC, the multiple factor (mF) is
introduced. This factor is a number between 0 and 1, which is a function of battery SoC. As a result, the
mathematic description of V2G regulation power (PREG) is expressed in (1).
,
,
;
P 0 ;
;
F D EV Max
REG Min Max
F C EV Min
m K f f f
f f f
m K f f f
     



     


    


(1)
The mathematic description of regulation power is divided in three parts. Having a look on control
block in Figure 2, if the Δf is positive and more than ΔfMax, the regulation is in discharge process, which the
power is negative. On the other hand, the regulation is in charge process, when Δf is negative and less than
ΔfMin, the power is then positive. In the dead band, the regulation is zero. The relay function is implemented
in order to avoid the oscillation operation at the transition point. This relay function is a dash line in Figure 3.
As mentioned that the multiple function is designed for the adaptive purpose according to battery
SoC. The original idea is referred to the normal charging process of battery that the charging current is
constant, when the charging process is start. Later, when the battery is nearly full, the charging current is
decreased until zero. Based on this information, the multiple factor characteristic curve is come out as in
Figure 4.
The operation range of characteristic curve is defined by the SoCMax and the SoCMin. In charging
process, the multiple factor is kept constant at 1 from the SoCMin to the turning point (SoCTP). When the SoC
level reaches the turning point, the multiple factor is decreased until zero at the SoCMax. For the discharging
process, the multiple factor with the same character but on the opposite direction. To describe the characteristic
curve, a quadratic equation is utilized. The mathematic formulation of multiple factor is written in (2).
Δf
PREG
ΔfMax
fRe+
ΔfMin fRe-
Discharging
Process
Charging
Process

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(a) (b)
Figure 4. Multiple factor based on battery SoC; (a) charging process, (b) discharging process
 
 
, 2
, 2
1 ;
1 ;
1 ;
1 ;
Min TP
F C
C TP TP Max
TP Max
F D
D TP Min TP
SoC SoC SoC
m
a SoC SoC SoC SoC SoC
SoC SoC SoC
m
a SoC SoC SoC SoC SoC
 


 
    


 


 
    


(2)
Where, mF,C and mF,D are the multiple factor of charging process and discharging process, respectively. The
coefficient a is the function of SoCTP and SoC level, which retunes the multiple factor to zero. As a result, the
coefficient aC and aD are obtained as in (3).
 
 
2
2
1
1
C
Max TP
D
TP Min
a
SoC SoC
a
SoC SoC




(3)
To summarize, the proposed active control methodology is functioned as a frequency regulation
supporter. When the Δf is in the operation range, the EV will charge/discharge the active power. The KEV is
the main parameter for controlling charge/discharge rate. It can be implied that the KEV is a primary control of
the EV. The mF is a factor, which adjusts the charge/discharge regarding the battery SoC level. Last but not
least, the proposed methodology can be applied for a single EV model or an aggregated EV model.
4. PARKING AREA MODEL AND ESTIMATED AVALIABLE CAPACITY
As the grid connection of EVs are penetrated in distribution network, therefore, the authors have
pointed out that the aggregation model of EVs should be based on parking area. The proposed parking area
model is devolved based the arrival time and departure time of the EVs. Since the arrival time and departure
time are randomly regarding the driver behavior, the Gaussian distribution is utilized to handle with this
stochastic character [27]-[29]. The Gaussian distribution is a simple distribution, which fits many natural
phenomenas. The arrival time and departure time of the EVs are adjusted through the mean value and the
standard deviation value of distribution [30]. An example of parking area model input is given in Table 1.
Four parking area types are presented. The office and the university type have mean value of arrival time and
departure time. On the other hand, the supermarket and the department store have only the mean of arrival
time. The idea behind this difference is that the office area or the university area have a regular office hour.
So, it has to define arrival time and departure time. The standard deviation in this case is around 1.
Meanwhile, the supermarket or the department store has a variety time range, then the one mean time with
high standard deviation is enough.
Table 1. Example of parking area model input
Parking Area Num. EVs Mean Arr. time Mean Dept. time St. Dev.
Office 100 9 17 1
University 100 9 18 1.2
Supermarket 200 17 - 2.5
Department store 200 15 - 2.0

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The simulation result of parking area model is shown in Figure 5. The random function is used to
generate the hourly arrival- or departure EVs. With this random number of EVs, the available capacity is able
to be calculated. The general formulation of cumulative available capacity is described in (4).
   
   
max , , max , ,
1 1
, min , , min ,
1 1
n m
C arri i cap i dept i cap i
i i
n m
D arrri i cap i dept i cap i
i i
AC SoC SoC EV SoC SoC EV
AC SoC SoC EV SoC SoC EV
 
 
 
 
     
   
 
 
     
   
 
 
(4)
Where, ACC and ACD are the available capacity of charging process and discharging process, respectively.
The EVcap is battery capacity of EV. The SoCarri and SoCdept are the battery state that arrives the parking area
and leaves the parking area, respectively.
Office
4 6 8 10 12 14 18 20
4 6 8 10 12 14 16 18 20
15
10
5
0
15
10
5
0
University
EV number
EV number
4 6 8 10 12 14 16 18 20
4 6 8 10 12 14 16 18 20
15
10
5
0
15
10
5
0
Supermarket
Department Store
EV number
EV number
16 22 [Hr]
22 [Hr]
22 [Hr]
22 [Hr]
Figure 5. Result of parking area model
To demonstrate the available capacity regarding the result in Figure 5, the simplification is made by
the following assumption. The EVcap of all EVs are constant at 50 kWh. The arrival of battery SoC is constant
at 0.7 and the departure battery SoC is constant at 0.4. The operation range of battery SoC for regulation
process is between 0.9-0.3. The estimation of available capacity for charging process and discharging process
is shown in Figure 6. The bar graph in Figure 6 stands for the capacity according to the number of EVs that
arrive or depart parking area in hourly based on the result in Figure 5. For example, in the case of office
parking area, it is defined with two characters, i.e. arrival and departure. When the EVs arrive parking area in
the morning, the available capacity in charge- or discharge capacity is counted. When the EVs leave parking
area, the capacity is withdraw from cumulative capacity. The cumulative available capacity can be calculated
according to (5). In the case of supermarket, as the idea of this area is designed based on the high rate of
arrival and departure, thus, the cumulative available capacity does not consider in this case. The bar graph is
hourly considered as the available capacity in this parking area type.
4 6 8 10 16 18 20
-1000
-500
0
500
Office
Energy [kWh]
10 50
270
420
220
30
-20
-100
-540
-840
-440
-60
20
100
250
290 270
70
-40
-200
-500
-580-540
-140
Char.
Ener.
Disc.
Ener.
Withdraw
Disc.
Ener.
Withdraw
Char.
Ener.
4 6 8 10 16 18 20
-1000
-500
0
500
Supermarket
Energy [kWh]
20 20 20
100
180 210
290 260 300
200
260
70 20
-40 -40 -40
-200
-360
-420
-580
-520
-600
-400
-520
-140
-40
22
22
Char.
Ener.
Disc.
Ener.
[hr]
12 14
[hr]
14
12
Figure 6. Estimated charge- and discharge available capacity

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To recapitulate, the Gaussian distribution is used for the parking area model. The number of EV,
mean value of arrival time or departure time and standard deviation are required. Two parking area models
are defined. The first is the area that has regular office hour and long parking period. The cumulative
available capacity is subsequently applied in this case. The second is the area that has variety time range and
high rate of arrival and departure. In this case, the available capacity is hourly considered. Note that,
calculated available capacity is the estimation value based on the stochastic character. This available capacity
is a kind of reserve power for each parking area.
5. MODEL IMPLEMENTATION AND FREQUENCY RESPONSE VALIDATION
To simulate and evaluate the proposed hierarchical- and EV control block diagram for frequency
regulation, the DIgSILENT simulation language (DSL) in PowerFactory program is considered as a
simulation platform. The DSL can represent the dynamic of power system simulation based on the root mean
square value. As a result, the model of EV and power system according to Figure 2 are implemented based
on DSL. The first step of EV modelling is to select the component that can provide the active power in both
directions according to the behaviors of V2G process. A static generator is considered and picked up as an
interface element between power network and the proposed control strategy. Figure 7 shows the control
frame of V2G model in DSL. The proposed mathematic description of V2G operation function in section 4 is
programmed in the “Pcontrol block”. The “PT1 block” is used for describing the behavior of converter. The
“Phase Lock Loop block” provides the reference angle for the static generator. Note that the “iq_ref” of static
generator is left as an open input port because the active power is only considered in this study. The “Battery
block” is in charge for battery SoC calculation based on the concept of active power integration.
To study the frequency regulation, it is important to chek frequency response. The power system
unit in this research work is applied by a synchronous generator model, which is available in DIgSILENT
library. The governor droop factor is adjusted to examine the primary respose. In addition, the secondary
control block is added. The PI controller is fine-tuned to assure the secondary respose. To test the response,
two step load events, i.e. increasing load 0.1 pu. at 100s and decreasing load 0.1 pu. at 1100 s, are used. The
result is shown in Figure 8, which the frequency response looks proper. When the character of primary
control is observed, it can be noticed from the result that the duration time of primary control action is around
72 s. The frequency drop is around 2%. The recovery time of frequency according to the secondary control is
around 728 s or 12.2 min. Form the operation time of the primary control and the secondary control, both
follow the standard of hierarchical control strategy [20].
Figure 7. V2G control frame in DSL
Figure 8. Response of power system frequency
400 800 1200 1600 [s]
0.9700
0.9825
0.9950
1.0075
1.0200
1.0325
System
frequency
[pu.]
2000
100.0 s
1.000 pu.
172.0 s
0.991 pu
900.0 s
1.000 pu
1900.0 s
1.000 pu.

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6. CASE STUDIES AND DISCUSSION
To study the frequency regulation when the proposed V2G operation is a part of hierarchical
control, two case studies are developed. The first case is the step response test. This case is designed for the
study of V2G effect on the primary control and the secondary control. Moreover, this case is a validation case
for the proposed strategy, which the multiple factor and power sharing are the main examination. The second
case is the continuous test, which means that the V2G operation is investigated along the load profile in one
day. The stochastic of parking area model and the available capacity are considered in this study. Since, the
target of both studies is the operation function test, thus the simple test system in Figure 9 is sufficient. The
system load model is depended on the case studies, the case study 1 is a spot load and the case study 2 is a
load profile. The system bases are set as follow: SBase is equal to 10 MVA, VBase is 22 kV, and fBase is 50 Hz.
Station
Grid
System Load
PA1 PA2
T1
Figure 9. Test system for case studies
The two PA models are designed with difference assumptions. It is assumed that the PA1 has larger
parking capacity than PA2. As a consequence, the droop factor of PA1 should be higher than the droop factor
of PA2. This means that the PA1 should delivered more power than PA2. To check the function of multiple
factor, the SoC level of PA2 is set to lower than the turning point. The frequency dead bands for relay
function are set to ± 0.01 pu. and ± 0.005 pu. The PA’s parameters are shown in Table 2.
Table 2. Parameters of parking area
Parameters PA1 PA2
Initial SoC 0.7 0.5
SoCMax/SoCMin 1/0.3 1/0.3
SoCTP,C/ SoCTP,D 0.8/0.6 0.8/0.6
Droop factor 4 2
fMax/fMin 1.01/0.99 pu. 1.01/0.99 pu.
fRe+/fRe- 1.005/0.995 pu. 1.005/0.995 pu.
6.1. Case study 1–Step response test
The objectives of step response test are the study of primary control and secondary control under
frequency regulation service and the validation of proposed V2G operation. From the introduced test system,
the 0.05 pu. step load is applied at 100 s. The simulation results, i.e. the frequency response, the active power
of parking areas and the multiple factor of parking areas, are discussed as follow.
Having a look on a comparative system frequency responses in Figure 10(a), there is a different
during the primary control period and the secondary control period. In the primary control period, the EVs
are activated as V2G when the frequency is dropped to their operation range. According to this fact, there is a
small delay in delivering the power from PAs, see Figure 10(b). This means that the V2G operation is not a
typical primary control, but it functions as a supporter. Regarding the frequency response in this period, the
response is surely faster than the system, which does not have the support from V2G.
To bring the frequency back to the nominal value in the secondary control part, the EVs also support
this working process until the frequency is back to fRE. In Figure 10(b), the active power from PAs is
continually supplied by the system. But the supplied power is slowly decreased according to the increasing of
frequency. In the same time, the generation power from the main grid is increased in order to cover the load
change. At 875 s, the system frequency is back to fRE, but the delivered power from PAs is not immediately
stopped. This is the proposed relay function. The support power in the secondary control process effects
directly on the frequency response. The frequency response of the system that has a support from EVs is
slower than the normal system. The cause of this point is that the main system delivers less power, then the

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frequency recovery is accordingly slower. In summary of the primary control and the secondary control
under frequency regulation service, the V2G operation works as a support in frequency regulation. It helps
system frequency in fast response during primary control process, but the frequency response is slightly
slowdown in secondary control process.
Next, the proposed V2G operation is examined. The main point in this part is the power sharing
between PAs and the multiple factor of each area. The consideration of this part is the delivered active power
in Figure 10(b) and the multiple factor of PA. Having a look on the highest delivered power, the active power
of PA1 is around 0.022 pu and the active power of PA2 is around 0.01 pu. As the droop factor of PA1 is a
double value of PA2, then the power from PA1 should be two times more than PA1. However, there is a slightly
difference around 0.02 pu. This difference is the effect of multiple factor, see Figures 10(d) and 10(f). The
multiple factor of PA1 is equal to 1, while the multiple factor of PA2 is less than 1. This is the cause of SoC
level. Since the SoC level of PA2 is less than the turning point, then the multiple factor is a parabola
function, see Figure 3. Let’s check the SoC level of PAs after the frequency regulation service, see
Figures 10(c) and 10(e). The change of SoC level is correct, as the change of PA1 is around two times more
than PA2. Remark, the capacity of both PAs in this study are equal. Up to this point, the study of step
response confirms that the mathematics function of proposed strategy works correctly.
(a) (b)
(c) (d)
(e) (f)
Figure 10. Simulation results; (a) power system frequency response, (b) active power from parking areas
(c) SoC of PA1, (d) multiple factor of PA1, (e) SoC of PA2 and (f) multiple factor of PA2
6.2. Case study 2–continuous test
In continuous study, the V2G action in daily operation is the main investigation. The estimated
available capacity of parking area is taken into account. The estimated available capacity office area and the
supermarket in Figure 6 is applied. The estimated available capacity is implemented as a limitation in V2G

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control frame. The set parameters of office area and the supermarket area are referred to PA1 and PA2 in
Table 2, respectively. The standard load profile of general commercial area [31] is selected for the study.
At the first step of the continuous test, the V2G operation is observed. When there is no system
event in the system, the V2G is not active, see a dash line in Figure 11(a). Because the process of secondary
control brings the system frequency back to rated value, the frequency is not enter into the operation range of
V2G process. This scenario also supports the result in the case study1 that the benefit of V2G operation is
mainly on the primary process. Next, the system events are created in order to investigate V2G action in daily
operation and available capacity of parking area. Two system events are assumed. The 0.1 pu. load is added
to the grid at 10 a.m., and this amount of load is removed from the grid at 2 p.m. This event can be referred to
a lockout of small generation unit due to a fault. Figure 11(b) shows the action of V2G process. It is obvious
that the PAs inject the power into the network during event1 and consume the power during event2.
The zoom display of active power and energy of both PAs during event1 and event2 are shown in
Figures 11(c)-11(f). Having a look on the injection power during event1, the PA1 delivers more power than
PA2 according to the SoC level. However, the interesting point is that the PA2 has reached limitation
regarding the available capacity. Then, the delivered power from PA2 is stopped. This can be easily noticed
by response in Figure 11(d) that the used energy level of PA2 enters the steady state faster than PA1. In the
part of event2, the response of PA1 and PA2 become similar, see Figure 11(f). This means that the available
capacity of both PAs is enough for the operation. Considering the amount of energy of both PAs during V2G
process, 100 kWh is used during event1 and 120kWh during event2. Comparing this amount of energy to
available capacity in Figure 6, it still has an energy gap that the EVs can support frequency regulation. To
this point, it has to mention that the energy usage depends on the level of power system event and the setting
of droop factor in each PA.
(a) (b)
(c) (d)
(e) (f)
Figure 11. Simulation results; (a) system frequency, (b) active power from parking areas,
(c) active power event 1, (d) energy event 1, (e) active power event 2 and (f) energy event 2

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To conclude, this study case confirm that V2G operation is only active when there is a power system
event. Because in normal operation, the frequency is kept to rated value by secondary control process. This
emphasizes that the V2G operation is a supporter for frequency regulation. Since the power system event
may not happen every day, the available capacity can be considered as power system reserve.
7. CONCLUSION
The integration of V2G application in hierarchical control architecture has been researched in the
part of frequency regulation. The research focus is how the V2G in distribution level effects the convention
control in transmission system level. Furthermore, this work pointed out that the EVs cannot be considered as
one single group of V2G operation, but it has to be operated as multiple-areas of V2G and related to the
location in distribution network. Achieving the aim of this study, the V2G model is developed. The model
consists of two main parts, i.e. the power regulation part and the estimated available capacity part. In the part
of power regulation, the EV droop control function is proposed. The droop is developed based on the
nonlinear function of multiple factor and battery SoC level. In the part of estimated available capacity, the
Gaussian distribution is used. The number of EV, the mean of arrival time, the mean of departure time, and
standard deviation of each parking areas are the input for the calculation of available capacity.
To demonstrate multiple-areas of V2G operation in hierarchical control architecture, two simulation
case studies, i.e. the step response test and the continuous test, are introduced. The proposed V2G control
function and the power sharing between parking areas with the limitation of available capacity have been
proved by these tests. In addition, it was found that the V2G operation effected the primary control period
more than the secondary control period. As its control strategy can conform the hierarchical control
architecture. The V2G application can be considered as power system reserve.
ACKNOWLEDGEMENTS
This research was supported by the Office of the Higher Education Commission and the Thailand
Research Fund (Grant No. MRG6180068).
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BIOGRAPHIES OF AUTHORS
Paramet Wirasanti, he received the B.Eng. degree in Electrical Engineering from Chiang Mai
University, Thailand, in 2003, the M.S. degree in Mechatronic from Leibniz University
Hannover, Hannover, Germany, in 2008, and Ph.D. degree in Electrical Engineering from South
Westphalia University of Applied Sciences, Soest, Germany collaboration with University of
Bolton, UK, in 2014. Currently, he is a lecturer at Department of Electrical Engineering, Chiang
Mai University, Thailand. His research interests are in the areas of automated control function in
distribution power supply systems and power systems management.

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Suttichai Premrudeepreechacharn, he received the B.Eng. degree in Electrical Engineering
from Chiang Mai University, Chiang Mai, Thailand, in 1988 and the M.S. and Ph.D. degrees in
electric power engineering from Rensselaer Polytechnic Institute, Troy, NY, USA, in 1992 and
1997, respectively. Currently, he is an Associate Professor at the Department of Electrical
Engineering, Chiang Mai University. His research interests include micro grid system, power
system protection, power system analysis, and power system planning.

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