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IEEE TRANSACTIONS ON POWER SYSTEMS 1
A Seamless Control Methodology for a GridConnected and Isolated PV-Diesel Microgrid
S. Mishra, Senior Member, IEEE, D. Ramasubramanian, Student Member, IEEE, andP. C. Sekhar, Student Member, IEEE
AbstractIn this paper, a seamless control methodology hasbeen proposed for a photo voltaic (PV)-diesel generator (DG)microgrid to operate both in the grid connected and islandedmode. It does not require any islanding detection mechanism, to
change the control philosophy from the grid connected mode tothe islanded mode. A second order sliding mode control has beenused to control the voltage source converter of the PV sourcewhose set points have been generated by PI controllers. The max-imum power point tracking algorithm for the PV system has beenaugmented with an auxiliary signal obtained using the electrical
power output of the DG to reduce the output power of the PVsystem for economical operation of the DG unit. The DG unit is
regulated with the frequency of the microgrid while the inverterused in the PV system regulates the voltage at the point of commoncoupling. Similarly, if the DG is uncontrollable due to any reason,
the PV system is further added with an auxiliary signal based onthe frequency deviation to maintain frequency stability. Simula-tion of the system has been carried out in MATLAB/SIMULINKwith different levels of insolation and load to verify the proposedcontrol scheme.
Index TermsDerating, distributed generation, islanding, mi-crogrid, photovoltaic cells, sliding mode control.
NOMENCLATURE
The following notation has been used throughout this paper.
PV Photo voltaic.
VSC Voltage source converter.
DG Diesel generator.
PCC Point of common coupling.
MPPT Maximum power point tracking.
IPP Independent power producer.
PV array power and dc power into VSC,
respectively.
dc link capacitor and voltage, respectively.
ac powerfrom PV array and DG, respectively.
Power consumed by local load.
Manuscript received November 21, 2012; revised December 14, 2012, Feb-ruary 11, 2013, and April 21, 2013; accepted April28, 2013. Paper no. TPWRS-01296-2012.
The authors are with the Department of Electrical Engineering, In-dian Institute of Technology, Delhi, India (e-mail: [email protected];[email protected]; [email protected]).
Color versions of one or more of the figures in this paper are available onlineat http://ieeexplore.ieee.org.
Digital Object Identifier 10.1109/TPWRS.2013.2261098
Filter resistance, inductance and capacitance.
Winding resistance, reactance and intertia
constant of DG.
DG governor gains.
DG governor time constants.
Resistance and inductance of connecting line.
Resistance and inductance of distribution line
to main grid.
dq frame current components of VSC.
dq frame components of modulation index
of VSC.
System frequency.
Sliding mode controller gains.
PI controller gains.
I. INTRODUCTION
M ICROGRIDS with multiple sources are emergingrapidly in the distribution network. With renewablesources, these microgrids can be self-sustainable sources of
energy. Control of the converter used in the renewable sources
becomes complex due to the coupling of the equations on the
AC side of the converter. The standard methodologies to control
such systems usesa technique known as feedback linearization
to decouple and linearize the equations followed by either the
usage of PI controllers or sliding mode controllers. The PI
controller based approach has been demonstrated in [1], [2],
and[3]. The entire system, from the dc capacitor to the infinite
grid, has been represented in the set of equations. This ap-
proach, though efficient, has a drawback in that the information
about the grid connected points is not always readily available
as the grid may be located far away from the converter. On
the other hand, in [4], authors have used a first order sliding
mode controller to regulate the real and reactive power output
from a PV system. This control methodology is very robust
as the error always converges to the sliding surface. However
the drawback of the first order sliding mode control for a grid
connected PV system is that three equations have to be solved
simultaneously. This gives three control variables which then
have to be linked with each other. A second order sliding mode
controller will help in overcoming this dependency. This has
beenproposed in[5] for a rectifier-inverter HVDC link.
0885-8950/$31.00 2013 IEEE
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2 IEEE TRANSACTIONS ON POWER SYSTEMS
To achieve the maximum power point (MPP), in case of a PV
system, various schemes have been suggested in [6], [7], and
[8]. One technique proposes using sliding mode control for ob-
taining the MPP on the basis of maximizing the power equation
of the PV cell[9]. This is a first order sliding mode technique. A
second order technique has been presented in[10]for the max-
imum power point tracking (MPPT) process.
When the microgrid gets isolated from the main grid, due to
any reason, the setpoints for the controller have to be changed,
as we need to move from - to - mode. In[11], a flex-
ible control structure has been proposed that can operate both
in the grid connected mode and in the isolated mode without
the usage of a mechanism for islanding detection. Knowledge
of the electrical power, frequency and power angle is required
to achieve this control. The control that has been implemented
by the authors is based on the philosophy of modelling a VSC
as a synchronous generator. This results in the development of a
pseudo swing equation depicting the performance of the VSC.
The swing equation of any machine requires the specification
of a reference power level which acts as the setpoint for thatmachine. For all power sources that have been considered by
the authors of [11], a reference power level can be defined a
priori. However, for varying sources like PV arrays, it is im-
possible to define a reference power level as the power output
from these sources aredependent on the vagaries of nature. With
these sources of power, such a control scheme cannot be imple-
mented as maximum power has to be always extracted. This
philosophy has been adopted in[12]. In the isolated mode of a
PV-DG system, the PV array output will be bound between zero
and MPPT while the DG operation will be restricted within its
minimum and maximum limit of power output [12]. The PV
power output can be reduced from MPPT by increasing the dcvoltage of thePV array whereas the diesel inputto the DG can be
regulated to alter its real power output. Therefore, depending on
the load demand and insolation level, the dc voltage and diesel
input needs to be regulated. In [12], the authors have proposed
two approaches. In the first approach, a mathematical method is
used to obtain the dc voltage reference value by constructing the
PV array characteristics. This method requires the information
from the irradiation and temperature sensors that are located on
the PV panels. As per the data sheet of one of the manufacturer
[13] the accuracy is %. On the other hand the accuracy of
the temperature, voltage and current sensors are %. There-
fore, it can be concluded that the involvement of an irradiation
sensor makes the calculation of dc reference voltage erroneous
making the control loop inaccurate. Besides, as the irradiation
and temperature sensors are in general costly as compared to
voltage/current sensors and we need large number of such sen-
sors in an array, the cost of the entire control scheme will be
quite high.
In the second approach that has been proposed by the au-
thors of[12], the current level is maintained using a dc-dc con-
verter. However, the reference current level is obtained by using
look up tables that requires the information about irradiation and
hence all the limitations discussed above are also valid for this
scheme. Further, with change in environmental conditions, the
validity of the results from the look up tables is subject to dis-cussion. Changing the data in the look up tables to match the
environmental changes is a time consuming process. Thus the
overall complexity of this control scheme is high.
Keeping in mind the above mentioned issues, in this paper,
a seamless controller is proposed. The controller aims at elim-
inating the drawbacks of the control schemes presented in[11]
and[12]. Incorporation of a renewable energy source, namely a
PV array, calls for the need for change in control structure and
this issue has been addressed by the proposed controller. Fur-
ther, it eliminates the need of relying on the PV array character-
istics and local load information in order to obtain the required
setpoints. In addition, the control scheme that is proposed in this
paper does not require knowledge of the PV array characteris-
tics as is required in [12]. Thus this controller is suitable for
photovoltaic sources.
The salient features of this controller are:
1) suitable control scheme for energy sources from which
maximum power has to be extracted and thus a reference
power level cannot be defined;
2) no requirement of measurement of the local load level;
3) no requirement for a look up table or information about thePV array characteristics to decide the voltage reference in
the isolated mode;
4) reduced cost of control scheme as there is no requirement
for additional sensors to measure non-electrical quantities
like solar irradiation and temperature.
The technique has been tested with various DG generation
levels, multiple load power levels and multiple solar irradiation
levels both in the grid connected mode and in the isolated mode.
The paper is organized as follows. The system considered is
presented in Section II. Section III looks at the development
of the control structure with the simulation results presented in
Section IV.Section Vprovides an estimation of the cost of thecontrol structure. The limitations and scope for future research
are presented in Section VI while Section VII concludes the
paper.
II. SYSTEMMODEL
The microgrid considered is shown inFig. 1. In the grid con-
nected mode, maximum power is extracted from the PV array
as it operates at its maximum power point. The power delivered
by the diesel generator depends on the total amount of power
the IPP has to deliver according to its contract. In the isolated
mode, which is brought about by the isolator switch, the total
power produced depends on the local load level. The DG then
operates within the minimum and maximum level with the PV
array supplying the remaining power. The sources of power are
connected to the grid through a transformer.
The power produced by the PV array is shown in Fig. 2for
three different insolation levels of 500 Wm , 750 Wm and
1000 Wm . As it can be seen from the figure, the amount of
power extracted from the the PV array depends upon the mag-
nitude of the voltage across the capacitor . The value of
the voltage for maximum power extraction and the maximum
power that can be produced at a particular insolation level are
shown inFig. 2. This voltage level can be obtained by imple-
menting a suitable MPPT algorithm and thus maximum powercan be extracted from the PV array. The Perturb and Observe
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MISHRAet al.: A SEAMLESS CONTROL METHODOLOGY FOR A GRID CONNECTED AND ISOLATED PV-DIESEL MICROGRID 3
Fig. 1. Single line layout of utility and microgrid.
Fig. 2. Power-voltage curves of the photovoltaic array.
TABLE IASSUMPTIONS
MPPT algorithm used in this paper is on the lines of the algo-
rithm mentioned in[14].
III. CONTROLSTRUCTURE
A multiple control loop structure is proposed in this paper.
The PV control loop is responsible for the generation of
the firing pulses for the switches in the VSC while the sec-
ondary/setpoint control loops are responsible for generating the
setpoints/reference values of the PV control loop. In order to
observe the capability of the VSC to meet the reactive power
demand, the VSC is made responsible for the maintenance of
voltage at point A and thus, no automatic voltage regulator
is present on the DG. To ensure the completeness of the -
mode, the DG is made responsible for the maintenance of
frequency in the microgrid.
The assumptions that have been made in this paper are tabu-
lated inTable I.
Fig. 3. Reference frames.
A. PV Control Loop
The PV array converter is controlled using a second order
sliding mode controller. The second order controller is realised
by first implementing the feedback linearisation technique in
order to obtain the output variables in terms of the control vari-
ables. The reference point for this controller is taken as the local
point A. As , a new frame of reference located at
an angle to the network frame is defined as shown inFig. 3.
The angle is obtained from the phase locked loop (PLL) lo-
cated at point A. This new reference frame is formed such that
and . This aids in the decoupling
of the equations of the system. The differential equations shown
in(1)(3)represent the system from the PV array to point A, in
this new frame of reference:
(1)
(2)
(3)
The terms and can be neglected as the resistance
of the filter is negligible. Neglecting the losses in the converter,
the equations for power can be written as
(4)
In order to construct the second order system,(1) is differenti-
ated once with respect to time. Equation(2)is then used to sub-
stitute for the term that is obtained[5]. As a result, the
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4 IEEE TRANSACTIONS ON POWER SYSTEMS
output variables are expressed in terms of the control variables.
In these set of equations, the active power is controlled by the
voltage level of the dc bus capacitor while the reactive power
is controlled by quadrature axis current. Thus and are
the output variables. The control variables are the modulation
indices, and , of the converter. The resultant system of
equations, in per unit, written in the form of a matrix is given
by(5):
(5)
where
and
These equations can be represented in a general form as
(6)
where . A reduction in the number of equations
and a direct link between the output and control variables is thus
obtained.
A sliding surface is defined for the output variables and
. This surface represents the surface. The slidingsurfaces, as defined in[5], are given by(7a)and(7b):
(7a)
(7b)
To satisfy the condition for Lyapunovs stability, , the
differential of the sliding surface is defined in terms of a
function. Hence using these definitions the left hand side of(5)
can be represented as given by(8):
(8)
The final value of the control variables is given by
(9)
where, with reference to the solution of from(6)after substi-
tuting for from(8)
(10)
In this manner, the values of the control variables can be ob-
tained.
Fig. 4. Active power control loop.
B. Setpoint Control Loops
Three setpoints are required in this control structure, namely
and . The first two setpoints are for the VSC
while the third sets the mechanical power input of the diesel
generator.
1) Setpoint: The control block diagram to set the dc
voltage reference for the PV array is shown in Fig. 4. In any
mode of operation, the DG output needs to be greater than or
equal to the minimum power level to achieve fuel consumption
economy [12]. Similarly, since our energy management strategyis PVfirst, it has to operate at MPPT whenever possible. There-
fore, in the grid connected mode the setpoint needs to be ob-
tained from the MPPT algorithm. This is achieved by setting a
lower limit of zero on the integrator block, as the DG output is
always to its minimum level. When the microgird gets iso-
lated from the main grid, the total generation must be equal the
total load plus losses in the line between the PCC and the local
load. In this case, when the total local load plus loss is less than
the sum of maximum power of the PV array and the minimum
power output of the DG, the PV array has to be derated to main-
tain the DG power output at its minimum level.
This can be achieved by taking the advantage of the inertialresponse of the DG following the isolation. As the PV power
will not change unless the dc reference is changed, immedi-
ately following the isolation under the above mentioned oper-
ating condition, the motoring of DG will occur as has been ex-
plained in Scenario 1 ofSection IV [12], thus its electrical power
output will fall below its minimum level. At this instant, the
error (Fig.4) will be positive and thus the output of the integrator
will increase with a positive slope until the error exits. When
this adds to the MPPT algorithm output, the dc voltage refer-
ence will increase, leading to a reduction in the output power of
the PV array. On the other hand, when the load scenario forces
the power generated by the DG to be greater than its minimumlevel, the error signal will be negative and the integrator will
start to reduce its output until the error becomes zero. By set-
ting a lower limit of zero on the integrator, it is ensured that the
net dc voltage reference does not go below the MPPT value and
hence the PV array always operates in the stable region of its
power-voltage curve.
The error in frequency is used when the DG is to be operated
in an uncontrolled mode. Thus the value of is set as the
setpoint of the DG and an auxiliary signal proportional to the
frequency error is added to the loop.
2) Setpoint: The control block diagram to set the reac-
tive power is shown in Fig. 5. In both the grid connected and
the isolated mode, the functionality of this loop is based on the
error between the voltage at point A and its reference value.
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MISHRAet al.: A SEAMLESS CONTROL METHODOLOGY FOR A GRID CONNECTED AND ISOLATED PV-DIESEL MICROGRID 5
Fig. 5. Voltage control loop.
Fig. 6. Frequency control loop.
This voltage reference is set as 1 pu. The reactive power refer-
ence value is obtained from the error in voltage at point
A. The value of can be obtained from the reactive power
equation of(4).
3) Setpoint: The block diagram of this control loop isshown inFig. 6. By taking the frequency error signal, the me-
chanical power setpoint of the DG is controlled. The governor
for theDG hasbeen modelled on thelines of thegovernor mech-
anism explained in[15]. In the grid connected mode, since there
is no deviation in frequency from the reference, the frequency
error will be zero and the setpoint will be as desired. In the
islanded mode, due to a mismatch in the generation and load
levels, the frequency will deviate from the reference and thus
the setpoint will change to maintain the frequency.
C. Design of Control Parameters
The parameters of the control structure have to be tuned to en-sure satisfactory operation. The control structure proposed has
a combination of nonlinear and linear control elements. The PV
control loop is non linear while the setpoint control loops are
linear in nature.
1) PV Control Loop: Three parameter values have to be
tuned in the second order sliding mode control scheme. These
parameters are and . Consider a process equation given
by(11):
(11)
The state variableis while thecontrol variable is . Theslidingsurface for this equation can be defined as
(12)
The condition for Lyapunovs stability is . Substituting
from(11), we get
(13)
By taking and ensuring
, the stability criterion will be satisfied. In ad-
dition to this, stability will be ensured when the value of
. This ensures that the second term on the right hand side
of(13)will always be greater than the first term. Due to the neg-
ative sign the stability criterion will be maintained.
The second order sliding surface is defined as
(14)
On differentiating the above equation, we get
(15)
In this situation also, we can ensure that the stability criterion
is maintained by taking . However, to decide
the value of , the original first order equation of the control
variable has to be considered. In this case, the originalfirst order
equation is(2).
In this manner the value of and can be obtained. Once
these values have been obtained the value of can be suitably
adjusted to ensure a fast response.
2) Setpoint Control Loops: The setpoint control loops com-prise of linear controllers. The values of these controller param-
eters can be obtained by evaluating the characteristic equation
of the control loop.
a) Active Power Control Loop: With reference toFig. 4,
the signals and the output of the MPPT al-
gorithm can be considered as disturbance signals. The transfer
function of the incremental control loop can be written as
(16)
where is the integral gain, is a gain that can be used
to obtain the power extracted from the PV array from the dc
bus voltage and ms is the time constant of the sliding
mode controller. As this is a second order system, (16)can be
compared with the general equation of a second order system as
given by
(17)
The value of can be obtained by referring toFig. 2. As the
initial transient will occur around the MPPT, the controller pa-
rameters are obtained with respect to this point. In incremental
form, the change in power extracted from the PV array can be re-lated to the change in the voltage level by the slope of the curve.
The power-voltage curve can be approximated as a straight line
in the region of the maximum power. For an insolation level of
500 Wm , the slope of the line is obtained as
(18)
To obtain in per unit, this value of is divided by the
base power. Thus, with and assuming a value
of damping ratio . When the DG is to
be operated in an uncontrolled mode, and the frequency
error gets added to the loop after being processed by a propor-
tional gain of . In the DG controlled mode, . The
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6 IEEE TRANSACTIONS ON POWER SYSTEMS
Fig. 7. Frequency response of the active power control loop.
frequency response of the open loop transfer function when DG
is controllable is as shown inFig. 7.
b) Reactive Power Control Loop: With reference to
Fig. 5, the transfer function of the incremental control loop can
be written as
(19)
where is the integral gain, is a gain that will give voltage
at the point A from the current and ms is the time
constant of the sliding mode controller. It is assumed that a pos-
itive value of reactive power relates to an injection of reactive
power at point A by the VSC. An increase in the reactive power
injection will increase the voltage level at point A. However,
from(4), it can be seen that an increase in reactive power causes
to become more negative. Thus the value of is taken as
the negative of the impedance . On comparing(19) with
(17), with and . The fre-
quency response of the open loop transfer function is as shown
inFig. 8.
c) Frequency Control Loop: With reference toFig. 6, the
transfer function of the loop can be obtained. The governor
model consists of two blocks which simulate the actuator and
the engine dead time, respectively. While forming the transfer
function of the control loop, the dead time has to be represented
as a rational transfer function. The most common way of ob-
taining this representation is by using the Pad-approximation.
The dead time is represented by the engine torque constant
and the engine dead time . In addition, the signalsand can be treated as disturbance signals. A second order
Pad-approximation is used to represent the engine dead time
as given in(20):
Fig. 8. Frequency response of the reactive power control loop.
Fig. 9. Frequency response of the frequency control loop.
(20)
where and . The transfer functionis thus given as shown in (21) at the bottom of the page, where
and are the proportional and integral controller gains.
, where is the inertia constant of the generator.
and are the actuator constant, current driver constant
and the actuator time constant respectively. The gains of the
PI controller have been chosen based on the commonly used
values as mentioned in[15]. Thus, as a result, and
. This loop operates only when the DG is operating
in a controlled mode. The frequency response of the open loop
transfer function is as shown inFig. 9.
IV. SIMULATION ANDRESULTS
The system described in Section II has been simulated inSIMULINK. Various scenarios have been considered to vali-
date the proposed control scheme. In the first scenario, the need
for the seamless controller is showcased with both the PV array
(21)
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MISHRAet al.: A SEAMLESS CONTROL METHODOLOGY FOR A GRID CONNECTED AND ISOLATED PV-DIESEL MICROGRID 7
Fig. 10. Scenario 1. (a) DC bus voltage. (b) Power. (c) Frequency.
and the DG being uncontrolled. The second scenario validates
the performance in the grid connected mode with varying solar
insolation. Thus, the flow of power between the main grid and
the microgrid can be observed from this scenario. Further, with
the initial DG power level at 25 kW and the initial solar insola-
tion at 500 Wm , two separate scenarios varying in load pat-
tern and insolation level have been considered. These scenariosshow the performance of the control scheme when the microgrid
gets isolated from the main grid. In this isolated condition, the
power output of the sources have to be controlled according to
the varying demand and the varying insolation. Further, the phi-
losophy of extracting maximum power from the PV array while
simultaneously operating the DG in an economical manner is
also shown by these scenarios. The final scenario is considered
to validate the performance of the control scheme when only
the DG is non-controllable. This non-controllability of the DG
arises under the umbrella of market participation of the sources.
Though this mode of operation is essentially in a grid connected
scheme and has been observed from the second scenario, thisscenario shows the completeness of the seamless controller in
scheduling power between the sources even in the isolated mode
with the limiting factor being the schedule of the sources.
In the formulation of the control scheme, the resistance of the
filter and the converter losses have been neglected. However,
while running the simulation, these network elements have been
represented. With the addition of an integral controller in the PV
control loop, this does not cause a problem in the performance
as any slight variation in the network parameters is compensated
by the integral control[1].
A. Scenario 1
Even with a philosophy of extracting maximum power from
renewable energy sources, a need arises at times to reduce the
power extracted from such sources. To achieve this a control
methodology is required that will schedule the power generated
by these sources accordingly. This scenario showcases the op-
eration of the system when no control has been applied on the
level of power generated by the sources.
The system is operated with the setpoint of the DG being 10
kW and the solar insolation level is assumed to be 500 Wm .
From the PV curves, the power that is extracted from the PV
array is seen to be 27 kW. The local load consists of a 10 kW, 5
kVAR static load and a 25 kVA induction motor dynamic load.
The local load level is assumed to be 20 kW with 10 kW of static
load and 10 kW of dynamic load. Thus, there is a generation
surplus of 17 kW in the microgrid. In the grid connected mode,
this power (to the tune of 15 kW after losses) is pumped into
the grid. At s, the microgrid is isolated from the main
grid and the system performance is as depicted inFig. 10. It can
be seen fromFig. 10(a) that the dc bus voltage is the same as
in the grid connected mode. Thus maximum power is extracted
from the PV array even in the isolated mode, as can be seenfromFig. 10(b). Since there is very little change in the voltage
levels, the power consumed by the loads remains constant. As
the generation levels are higher than the load, it results in a rise
in frequency of the system as depicted inFig. 10(c). The surplus
power of 15 kW that was previously exported to the grid, is now
consumed by the DG resulting in the motoring of the DG. This
can be observed from Fig. 10(b) wherein the DGpoweris 10kW
before isolation and it drops to kW after isolation. A simple
calculation reveals that the electrical power is now balanced in
the system with the DG operating as a motor. However, the fre-
quency continues to increase as the input mechanical power to
the DG is constant resulting in the acceleration of the machine.Thus it can be seen from this scenario that when the microgrid
gets isolated from the main grid a suitable control scheme is
required in order to reduce the generation levels and thus switch
the operation of the control scheme from a - mode to a -
mode.
B. Scenario 2
The power generated by the DG is defined by the setpoint
of its governor while the power extracted from the PV array is
dependent on the incident solar irradiation. In this scenario, the
microgrid is always assumed to be connected to the main grid.
With afi
xed setpoint for the governor andfi
xed level of localloading, the power that is either consumed or delivered by the
main grid is dependent on the level of solar insolation. With
decrease in solar insolation, the total power generation in the
microgrid may be insufficient to meet the demands of the local
load and thus the deficit in power will have to be supplied by
the main grid. Under these circumstances, since the frequency
of the system is maintained by the grid, the frequency control
loop does not alter the governor setpoints, and thus the DG does
not deviate from its schedule. The satisfactory performance of
the control scheme can be observed fromFig. 11which shows
the plots of the dc voltage of the capacitor , the powerflows
and the frequency of the system. The insolation level is assumed
to be 750 Wm until s. At this insolation level the
maximum power that can be extracted from the PV array is 41
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8 IEEE TRANSACTIONS ON POWER SYSTEMS
Fig. 11. Scenario 2. (a) DC bus voltage. (b) Power. (c) Frequency.
Fig. 12. Scenario 3. (a) DC bus voltage. (b) Power. (c) Frequency. (d) Motor speed. (e) Voltage at point A. (f) DC current.
kW. The DG setting is maintained at 10 kW. Thus the total
power generation in the microgrid is 51 kW. The power level of
the local load is 37 kW with 10 kW being a static load, 25 kW
being an induction motor load and 2 kW being the losses. This
load level is also maintained constant for the entire scenario.
It can be observed fromFig. 11(b)that with these power levels,
the microgrid has surplus power and thus this extra power, to the
tune of 14 kW, is sent from the microgrid. Due to further losses
in the transformer and line, 11 kW of power is sent to the main
grid. The dc voltage level, shown in Fig. 11(a), is maintainedat the MPP value of 796 V. At s, the insolation level is
decreased to 500 Wm thereby reducing the maximum power
extraction from the PV array to 27 kW. From the dc voltage plot
it can be seen that the MPPT algorithm successfully tracks the
PV curve in order to extract the maximum power at a voltage
level of 782 V. However, at this reduced insolation level, the
total power generated in the microgrid is slightly insufficient to
meet the local load demand and the losses. Thus 2 kW of power
flows in from the grid into the microgrid. From the frequency
plot ofFig. 11(c)it can be seen that with the disturbance there is
a perturbation which thus causes a perturbationin theDG output
power. This however does not alter the governor settings during
steady state as the grid frequency is maintained at 50 Hz. The
perturbation in frequency occurs as a result of the sudden power
mismatch that occurs. However, with the inflow of power from
the grid, the mismatch is reduced. At s, the insolation
level is further decreased to 300 Wm resulting in a larger
inflow of power from the grid to the tune of 12 kW.
It can be seen that the DG power level is maintained at the
initial setpoint level and thus the DG can maintain its schedule.
The flow of power between the microgrid and the grid is also
observed from this scenario. Thus the performance of the con-
troller in the grid connected mode is validated.
C. Scenario 3
The insolation level, in the grid connected mode, is taken as
500 Wm with the maximum power that can be extracted from
the PV array being 27 kW. With the DG setpoint as 25 kW, a
total of 52 kW of power is generated by the IPP. The microgrid
isislandedfrom the maingrid at s.The insolationlevel is
assumed to remain constant at 500 Wm throughout the sce-
nario. The dc voltage of the capacitor , power, frequency,
speed of the induction motor, voltage at point A and dc current
are shown inFig. 12.
Referring toFig. 12(b), the total power that is supposed to
be consumed by the local load is 20 kW, with 10 kW being the
static load consumption and 10 kW being the induction motor
load. However, the static load is represented as a constant
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MISHRAet al.: A SEAMLESS CONTROL METHODOLOGY FOR A GRID CONNECTED AND ISOLATED PV-DIESEL MICROGRID 9
Fig. 13. Scenario 4. (a) DC bus voltage. (b) Power. (c) Frequency. (d) Motor speed. (e) Voltage at point A. (f) DC current.
impedance load with 10 kW being the power consumed by it
at rated voltage. Due to the drop in the line from the PCC, the
voltage at the local load is lower than the rated voltage. Thus,
the power consumed by the static load is lesser than 10 kW.
Hence, inFig. 12(b), the total input electrical power to the load
(including the losses in the induction motor), is lower than 20
kW. When the microgrid gets isolated from the main grid, since
the load level remains the same, the PV array has to be derated
in order to maintain the DG output at its minimum level. The
maximum power of the DG is considered to be 80 kW with aminimum power of 4 kW[12].
Increasing the voltage of the capacitor will reduce the
power extracted from the PV array as shown inFig. 12(a)and
(b). After islanding, the dc voltage is raised from theMPPT level
of 782 V to 890 V. At this voltage level, the power extracted
from the PV array is 17 kW while the DG produces 4 kW. Thus
the total generation is 21 kW while the consumption is almost
20 kW. The losses in the line and the load are to the tune of
1 kW. At the moment of islanding, the difference between the
total load and the total generated power is to the tune of 32 kW.
Due to this, there is a rise in the frequency of the system and
thus a corresponding rise in the speed of the induction motor.This can be observed fromFig. 12(c)and(d), respectively. Due
to surplus power, as depicted in Scenario 1, the DG consumes
power and the generated power goes below its minimum level
and thus according to the control loop in Fig. 4, the dc voltage
reference is increased. As the difference in power is more than
the initial generation level of the DG, the speed of the generator
and thus the frequency of the system increases by a large value
as shown inFig. 12(c). The speed of the motor, as seen from
Fig. 12(d) rises from 1476 RPM to 1576 RPM in 0.5 s. This
corresponds to a of 20.94 radsec , which agrees with
the swing equation of the motor. FromFig. 12(a)and(c)the
difference in the speed of operation of the electrical loop con-
trolling the dc voltage reference and the mechanical loop, i.e.,
the governor, controlling the input to the DG can be observed.
Due to the dead time and also the fuel flow time, the governor
action is very slow compared to the action of the electrical loop.
The per unit voltage at point A is shown inFig. 12(e). It can be
seen that the voltage control loop maintains the voltage level at
the reference value of 1 pu.
At s, the induction motor load is increased from 10
kW to 18 kW. The total load on the system at this point is 28
kW and the losses in the motor are to the tune of 2 kW. This
power level is greater than the maximum power of the PV array
for this insolation level, i.e., 27 kW. However, since the DGhas to be operated at a minimum level, the PV array has to still
operate in the derated mode. This increase in load is met by
releasing power from the kinetic energy of the DG. This can be
seen fromFig. 12(b). Due to this, the speed of the DG drops
and this is reflected as a drop in the frequency of the system
as shown in Fig. 12(c). As the MPPT algorithm changes the
voltage reference, the DG power returns to its minimum value
and the PV array takes up the additional load demand as seen
from the PV power curve in Fig. 12(b). Thus, 26 kW is extracted
from the PV array while the DG operates at its minimum level
of 4 kW.
At s, the induction motor load is increased from 18kW to 25 kW. Since the total electrical load is now greater than
the sum of the maximum power of the PV array and the min-
imum value of the DG, the PV operates at MPPT and the deficit
is taken care off by the DG due to the action of the frequency
control loop. The DG thus now produces 12 kW of power. It
can be observed fromFig. 12(f)that when there is an increase
in the induction motor load, negligible transients appear in the
dc current. Thus the switches in the converter will be able to
withstand the changes in the current.
D. Scenario 4
The microgrid is islanded from the main grid at s. A
step change in the insolation level is assumed to occur at
s from 500 Wm to 750 Wm . Further at s a ramp
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10 IEEE TRANSACTIONS ON POWER SYSTEMS
Fig. 14. Scenario 5. (a) DC bus voltage. (b) Power. (c) Frequency.
increase in the insolation level is assumed from 750 Wm to
1000 Wm at a rate of 250 Wm s . The total active power
consumed by the local load at the time of islanding is again
20 kW with 10 kW being the static load and 10 kW being the
induction motor load. At s the induction motor load is
increased to 25 kW and thus the total active power load on the
microgrid is 35 kW. The dc voltage of the capacitor , power,frequency, speed of the induction motor, voltage at point A and
dc current are shown inFig. 13.
The response of the system until s is the same as
the previous situation. It can be seen that in the isolated mode,
due to the increase in insolation level, the PV array is able to
fully support the load and thus the DG always operates at its
minimum level. Referring toFig. 13(c), at s, when the
load power level increases, the frequency of the system drops
slightly as the DG tries to support this increase in load by re-
leasing power from its kinetic energy. The MPPT algorithm
reduces the voltage level of thereby increasing the power
extracted from the PV array. Since the insolation has also in-creased, the algorithm brings the capacitor voltage to a level as
defined by the power voltage curve of this new insolation level.
The DG then settles at its minimum value. It can be observed
fromFig. 13(f)that when there is an increase in the induction
motor load at s, a very short duration transient appears
in the dc current. The IGBTs in the VSC however will be able to
handle this current transient as its magnitude and rate of change
is small.
When there is a ramp increase in the insolation level from
s, the MPPT algorithm tracks the change in the in-
solation and thus the dc voltage level increases to maintain the
output power level of the PV array the same as before the inso-
lation change. Thus due to the increase in insolation, the load is
supported at all times by the PV array.
For the two scenarios considered above, the frequency of the
microgrid in the isolated mode is maintained within 50.05 Hz
and 49.95 Hz. The voltage at point A is also maintained at 1
pu. Hence, the voltage and the frequency of the microgrid are
controlled.
E. Scenario 5
In this scenario, the DG is operated in an uncontrolled mode
with a constant setpoint. Thus in the active power control loop
ofFig. 4, the minimum value, , is set equal to the setpoint
of the DG. However, due to this loop, a three point oscillation
occurs in the output power of the DG due to the influence of the
P&O algorithm. Thus, for the operation of the loop, a band of
0.05 kW is specified around . The plots of the dc voltage,
power and frequency are shown inFig. 14.
The setpoint of the DG is 10 kW while the PV array power is
27 kW at a solar insolation of 500 Wm . The local load level
is 20 kW as in Scenario 3. As expected, the system frequency is
stable in the grid connected mode. At the moment of islanding,at s, the DG output power remains at its setpoint, while
the PV array operates in a derated mode with 12 kW of power
being extracted from it. As the frequency is now not controlled
by the DG, an auxiliary signal proportional to the frequency de-
viation is added to the output of the MPPT algorithm. This en-
sures that the frequency is controlled and thus helps in the sta-
bilization of the system. As the load level increases at s,
the PV array is still able to support the load with the DG oper-
ating at its setpoint and the frequency stabilises. With a further
increase in load, at s, maximum power is extracted
from the PV array. However, the load level plus losses is now
higher than the combined output of the DG and the PV array.There is a slight inertial disturbance in the output power of the
DG but it settles back at the initial setpoint. The frequency how-
ever begins to drop and the system loses stability. Thus we can
see that the control methodology with an auxiliary signal is able
to perform satisfactorily even when the DG is to be operated in
an uncontrolled mode as long as the load level is lower than the
generation levels.
This validates the performance of the control scheme in all
operating scenarios.
V. COSTESTIMATION
The control scheme that has been proposed in this paperis cost efficient when compared with other similar schemes
that have been documented in the literature [12]. Sensors to
measure frequency, voltage and current are common to all
schemes. The data from these sensors are then used by a digital
signal processor chip to implement the control scheme. The
estimated cost of building this proposed control scheme falls
around $350$400 based on the cost of the sensors reported in
[16][18]. However, the scheme mentioned in[12]requires an
additional temperature sensor and a solar irradiation sensor for
the each PV panel. As per the manufacturer data sheets [19],
[20], each sensor costs around $160. Thus the total cost of real
time implementation of the control scheme increases by $320
per PV panel. Thus, with a large solar park with multiple PV
panels, the cost will be increased proportionally.
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12 IEEE TRANSACTIONS ON POWER SYSTEMS
[14] A. Yazdani, A. Di Fazio, H. Ghoddami, M. Russo, M. Kazerani, J.Jatskevich, K. Strunz, S. Leva, and J. Martinez, Modeling guidelinesand a benchmark for power system simulation studies of three-phasesingle-stage photovoltaic systems,IEEE Trans. Power Del., vol. 26,no. 2, pp. 12471264, Apr. 2011.
[15] S. Roy, O. Malik, and G. Hope, An adaptive control scheme for speedcontrol of diesel driven power-plants, IEEE Trans. Energy Convers.,vol. 6, no. 4, pp. 605611, Dec. 1991.
[16] [Online]. Available: http://in.rsdelivers.com/product/lem/lv-25-p/hall-effect-pcb-mount-volt age-transducer/0286361.aspx.
[17] [Online]. Available: http://in.rsdelivers.com/product/lem/cksr-50-np/current-transducer-50a-low-drift-5v-vs/6668214.aspx.
[18] [Online]. Available: http://www.ti.com/product/tms320f2812.[19] [Online]. Available: http://www.civicsolar.com/product/fronius-irra-
diance-sensor.[20] [Online]. Available: http://www.civicsolar.com/product/fro-
nius-module-temperature-sensor.[21] I.-S. Kim, Sliding mode controller for the single-phase grid-connected
photovoltaic system, Appl. Energy, vol. 83, no. 10, pp. 11011115,2006.
[22] , W. Perruquetti and J. P. Barbot, Eds., S liding M ode Control in Engi-neering. New York, NY, USA: Marcel Dekker, 2002.
S. Mishra (M97SM04) received the B.E. degreefrom University College of Engineering, Burla,Orissa, India, and the M.E. and Ph.D. degrees fromRegional Engineering College, Rourkela, Orissa,India, in 1990, 1992, and 2000, respectively.
In 1992, he joined the Department of ElectricalEngineering, University College of EngineeringBurla as a Lecturer, and subsequently became aReader in 2001. Presently, he is a Professor withthe Department of Electrical Engineering, IndianInstitute of Technology Delhi, New Delhi, India. His
interests are in soft computing applications to power system control, powerquality, renewable energy, and microgrids.
Dr. Mishra has been honored with many prestigious awards such as the INSAYoung Scientist Medal in 2002, the I NAE Young Engineers Award in 2002, andrecognition as the DST Young Scientist in 2001 to 2002. He is a Fellow ofthe Indian National Academy of Engineering, the Institute of Engineering andTechnology (IET), London, U.K., and the Institute of Electronics and Commu-nication Engineering (IETE), India.
D. Ramasubramanian (S10) received the B.E.degree from Visvesvaraya Technological University,Belgaum, India, in 2011. Currently, he is pursuingthe M.Tech. degree at the Indian Institute of Tech-nology Delhi, New Delhi, India.
His research interests are in integration of renew-able energy into the existing grid, microgrids, andpower system dynamics and control.
P. C. Sekhar (S12) received the B.Tech. from Jawa-harlal Nehru Technological University, Hyderabad,India, and the M.Tech. degree from National Insti-tute of Technology Rourkela, India. Currently, he ispursuing the Ph.D. degree at Indian Institute of Tech-nology Delhi, New Delhi, India.
His research interests are soft computing applica-tions to design and control of microgridbased powersystems.