Pc3426502658

A. Sudharshan, Dr. & Prof. M. Yohan / International Journal of Engineering Research and
Applications (IJERA) ISSN: 2248-9622 www.ijera.com
Vol. 3, Issue 4, Jul-Aug 2013, pp.2650-2658
2650 | P a g e
Grid Interconnection of RES for Power Quality Improvement by
Using Fuzzy Logic Controller
A. Sudharshan*, Dr. & Prof. M. Yohan**
*(Department of Mechanical Engineering, JNT University, Anantapur-515002
** (Department of Mechanical Engineering, JNT University, Anantapur-515002.)
ABSTRACT
With the increase in load demand, the
Renewable Energy Sources (RES) are
increasingly connected in the distribution systems
which utilizes power electronic
Converters/Inverters. This paper presents a novel
control strategy for achieving maximum benefits
from these grid-interfacing inverters when
installed in 3-phase 4-wire distribution systems.
The use of non-linear loads in the power system
will lead to the generation of current harmonics
which in turn deteriorates the power quality.
Active Power Filters (APF) are extensively used to
compensate the current harmonics and load
unbalance. The inverter is controlled to perform
as a multi-function device by incorporating active
power filter functionality. The inverter can thus
be utilized as: 1) power converter to inject power
generated from RES to the grid, and 2) shunt
APF to compensate current unbalance, load
current harmonics, load reactive power demand
and load neutral current. All of these functions
may be accomplished either individually or
simultaneously. The inverter is controlled on the
basis of hysteresis and fuzzy logic control. With
such a control, the combination of grid-
interfacing inverter and the 3-phase 4-wire
linear/non-linear unbalanced load at point of
common coupling appears as balanced linear load
to the grid. This new control concept is
demonstrated with extensive MATLAB/Simulink
Keywords - Active power filter (APF), distributed
generation (DG), distribution system, fuzzy
controller, power quality (PQ), Renewable energy
sources (RES).
I. INTRODUCTION
ELECTRIC utilities and end users of
electric power are becoming increasingly concerned
about meeting the growing energy demand. Seventy
five percent of total global energy demand is
supplied by the burning of fossil fuels. But increasing
air pollution, global warming concerns, diminishing
fossil fuels and their increasing cost have made it
necessary to look towards renewable sources as a
future energy solution. Since the past decade, there
has been an enormous interest in many countries on
renewable energy for power generation. The market
liberalization and government's incentives have
further accelerated the renewable energy sector
growth. The sun and wind energy are the alternative
energy sources. Previously, they were used to supply
local loads in remote areas, outside the national grid.
Later, they have become some of main sources.
Renewable energy source (RES) integrated
at distribution level is termed as distributed
generation (DG). The utility is concerned due to the
high penetration level of intermittent RES in
distribution systems as it may pose a threat to
network in terms of stability, voltage regulation and
power-quality (PQ) issues. Therefore, the DG
systems are required to comply with strict technical
and regulatory frameworks to ensure safe, reliable
and efficient operation of overall network. With the
advancement in power electronics and digital control
technology, the DG systems can now be actively
controlled to enhance the system operation with
improved PQ at PCC. However, the extensive use of
power electronics based equipment and non-linear
loads at PCC generate harmonic currents, which may
deteriorate the quality of power [1], [2].
Generally, current controlled voltage source
inverters are used to interface the intermittent RES in
distributed system. Recently, a few control strategies
for grid connected inverters intermittent RES in
distribution systems as it may pose a threat to
network in terms of stability, voltage regulation and
power-quality (PQ) issues. Therefore, the DG
systems are required to comply with strict technical
and regulatory frameworks to ensure safe, reliable
and efficient operation of overall network. With the
advancement in power electronics and digital control
technology, the DG systems can now be actively
controlled to enhance the system operation with
improved PQ at PCC. However, the extensive uses
of power electronics based incorporating PQ solution
have been proposed. In [3] an inverter operates as
active inductor at a certain frequency to absorb the
harmonic current. But the exact calculation of
network inductance in real-time is difficult and may
deteriorate the control performance. A similar
approach in which a shunt active filter acts as active
conductance to damp out the harmonics in
distribution network is proposed in [4]. In [5], a
control strategy for renewable interfacing inverter
based on - theory is proposed. In this strategy
both load and inverter current sensing is required to
compensate the load current harmonics.

2651 | P a g e
The non-linear load current harmonics may result in
voltage harmonics and can create a serious PQ
problem in the power system network. Active power
filters (APF) are extensively used to compensate the
load current harmonics and load unbalance at
distribution level. This results in an additional
hardware cost. However, in this paper authors have
incorporated the features of APF in the, conventional
inverter interfacing renewable with the grid, without
any additional hardware cost. Here, the main idea is
the inverter rating which is most of the time
underutilized due to maximum utilization intermittent
nature of RES. It is shown in this paper that the grid-
interfacing inverter can effectively be utilized to
perform following important functions: 1) transfer of
active power harvested from the renewable resources
(wind, solar, etc.); 2) load reactive power demand
support; 3) current harmonics compensation at PCC;
and 4) current unbalance and neutral current
compensation in case of 3-phase 4-wire system.
Moreover, with adequate control of grid-interfacing
inverter, all the four objectives can be accomplished
either individually or simultaneously. The PQ
constraints at the PCC can therefore be strictly
maintained within the utility standards without
additional hardware cost.
Fig. 1. Schematic of proposed renewable based distributed generation System
Fuzzy logic control theory is a mathematical discipline
based on vagueness and uncertainty. It allows one to
use non-precise or ill-defined concepts. Fuzzy logic
control is also nonlinear and adaptive in nature that
gives it robust performance under parameter variation
and load disturbances. Many control approaches and
applications of fuzzy logic control have appeared in
the literature since Mamdani published his experiences
using a fuzzy logic controller on a test-bed plant in a
laboratory. An extensive introduction to the historical
development, current state and concepts involving
fuzzy control systems can be found in . The
fundamental advantage of the fuzzy logic controller
over the conventional controller is a less dependence
of the mathematical model and system parameters as
known widely.
The paper is arranged as follows: Section II
describes the system under consideration and the
controller for grid-in-terfacing inverter. A digital
simulation study is presented in Section III. Section
IV about FLC. Section V concludes the paper.
II. SYSTEM DESCRIPTION
The proposed system consists of RES
connected to the dc-link of a grid-interfacing inverter
as shown in Fig. 1. The voltage source inverter is a
key element of a DG system as it interfaces the
renewable energy source to the grid and delivers the
generated power. The RES may be a DC source or an
AC source with rectifier coupled to dc-link. Usually,
the fuel cell and photovoltaic energy sources generate
power at variable low dc voltage, while the variable
speed wind turbines generate power at variable ac
voltage. Thus, the power generated from these
renewable sources needs power conditioning (i.e.,
dc/dc or ac/dc) before connecting on dc-link [6]–[8].
The dc-Capacitor decouples the RES from grid and
also allows independent control of converters on
either side of dc-link.

2652 | P a g e
Fig. 2. DC-Link equivalent diagram.
A. DC-Link Voltage and Power Control Operation
Due to the intermittent nature of RES, the
generated power is of variable nature. The dc-link
plays an important role in trans-ferring this variable
power from renewable energy source to the grid. RES
are represented as current sources connected to the dc-
link of a grid-interfacing inverter. Fig. 2 shows the
systematic representation of power transfer from the
renewable energy resources to the grid via the dc-link.
The current injected by renewable into dc-link at
voltage level can be given as
where PRES is the power generated from RES.
The current flow on the other side of dc-link
can be represented as,
unity grid voltage vector templates( Ua, Ub and Uc)
generates the reference grid currents(Ia
*
,Ib
*
and Ic
*
)The
reference grid neutral current(In
*
) is set to zero, being
the instantaneous sum of balanced grid currents. The
grid synchronizing angle (θ) obtained from phase
locked loop (PLL) is used to generate unity vector
template as [9]–[11]
Where Pinv, PG and PLoss are total power
available at grid in-terfacing inverter side,
active power supplied to the grid and inverter
losses, respectively. If inverter losses are
negligible thenPRES=PG
B. Control of Grid Interfacing Inverter
The control diagram of grid- interfacing
inverter for a 3-phase 4-wire system is shown in Fig.
3. The fourth leg of inverter is used to compensate the
neutral current of load. The main aim of proposed
approach is to regulate the power at PCC during: 1)
PRES=0; 2) PRES< total load power(PL); and 3) PRES>
PL; While performing the power management
operation, the inverter is actively controlled in such a
way that it always draws/ supplies fundamental active
power from/ to the grid. If the load connected to the
PCC is non-linear or unbalanced or the combination
of both, the given control approach also compensates
the harmonics, unbalance, and neutral current.
The duty ratio of inverter switches are varied
in a power cycle such that the combination of load
and inverter injected power appears as balanced
resistive load to the grid. The regulation of dc-link
voltage carries the information regarding the
exchange of active power in between renewable
source and grid. Thus the output of dc-link voltage
regulator results in an active current . The
multiplication of active current component wit
the actual dc-link voltage Vdc is sensed and passed
through
A first-order low pass filter (LPF) to
eliminate the presence of switching ripples on the dc-
link voltage and in the generated reference current
signals. The difference of this filtered dc-link voltage
and reference dc-link voltage Vdc
*
given to a fuzzy
controller to maintain a constant dc-link voltage under
varying generation and load conditions. The dc-link
voltage error cerr (n) at Th sampling instant is
given as:
The output of discrete-PI regulator at th sampling
instant is expressed as
Where KPVdc=10 and KI Vdc=0.05 are proportional and
integral gains of dc-voltage regulator. The
instantaneous values of reference three phase grid
currents are computed as

2653 | P a g e
Fig. 3. Block diagram representation of grid-interfacing inverter control
The neutral current, present if any, due to
the loads connected to the neutral conductor should
be compensated by forth leg of grid-interfacing
inverter and thus should not be drawn from the grid.
In other words, the reference current for the grid
neutral current is considered as zero and can be
expressed as
he reference grid currents((Ia
*
,Ib
*
, Ic
*
and In
*
)are
compared with actual grid currents (Ia, Ib, Ic and
In)to compute the cur-rent errors as
These current errors are given to hysteresis
current controller. The hysteresis controller then
generates the switching pulses (P1 to P8) for the gate
drives of grid-interfacing inverter.
The average model of 4-leg inverter can be
obtained by the following state space equations
The switching pattern of each IGBT inside
inverter can be formulated on the basis of error
between actual and reference current of inverter,
which can be explained as:
If IInva < (IInva
*
-hb), then upper switch will be
OFF (P1=0) and lower switchS4 will be ON
(P4=1) in the
Phase “a” leg of inverter.
If IInva > (IInva
*
-hb) , then upper switchS1 will be
ON (P1=1)and lower switchS4 will be
OFF(P4=0) in
the phase “a” leg of inverter.
Where hb is the width of hysteresis band. On the same
principle, the switching pulses for the other remaining
three legs can be derived.

2654 | P a g e
III. FUZZY LOGIC
CONTROLLER
Fuzzy Logic Controller is one of the most
successful applications of fuzzy set theory,
introduced by Zadeh in 1965. Its major features are
the use of linguistic variables rather than numerical
variables. The general structure of the FLC is shown
in Fig 2. As seen from Fig.4, a FLC is comprises
four principal components.
Where VInva ,VInvb and VInvc are the three-phase ac
Switching voltages generated on the output terminal
of inverter. These inverter output voltages can be
modeled in terms of instantaneous dc bus voltage
and switching pulses of the inverter as
Similarly the charging currents IInvad ,IInvbd
,IInvcd and IInvnd on dc bus due to the each leg of
inverter can be expressed as
Fig. 4. Structure of FLC
The fuzzifier converts input data into
suitable linguistic values by using fuzzy sets. The
fuzzy sets are introduced with membership
functions such as triangle, sigmoid or trapezoid. The
knowledge base consists of a data base with the
necessary linguistic definitions and control rule set.
The rule set of knowledge base consists of some
fuzzy rules that define the relations between inputs
and outputs. Usually, fuzzy rules are expressed in
the form of IFTHEN fuzzy conditional statements;
(29)
where um is the mth input variable, v is the output,
Amn
is the nth membership set and Bi is the output
membership set belongs to ith rule.
Inference engine simulates the human decision
process. This unit infers the fuzzy control action
from the knowledge of the control rules and the
linguistic variable definitions. Therefore, the
knowledge base and the inference engine are in
interconnection during the control process. Firstly
active rules are detected by substituting fuzzified
input variables into rule base. Then these rules are
combined by using one of the fuzzy reasoning
methods. Max-Min and Max-Product are most
common fuzzy reasoning methods.
The defuzzifier converts the fuzzy control
action that infers from inference engine to a non fuzzy
control action.
Different defuzzification methods are used such as
center of gravity, mean of maxima and min–max
eighted average formula. Center of gravity is the most
common defuzzification method and given in Eq(30).
(30)
Where μ(z) is the grade of membership that obtained
inference engine, z is the outputs of each rules and z*
is the defuzzified output .
III.1 FLC for Grid Interactive Inverter
The first important step in the fuzzy
controller definition is the choice of the input and
output variables. In this study, the output voltage error
and its rate of change are defined as input variables
and change in duty cycle is the controller output
variable.
The three variables of the FLC, the error, the
change in error and the change in duty cycle, have
seven triangle membership functions for each. The
basic fuzzy sets of membership functions for the
variables are as shown in the Figs. 5 and 6. The fuzzy
variables are expressed by linguistic variables
„positive large (PL)‟, „positive medium (PM)‟,
„positive small (PS)‟, „zero (Z)‟, „negative small
(NS)‟, „negative medium (NM)‟, „negative large
(NL)‟, for all three variables. A rule in the rule base
can be expressed in the form: If (e is NL) and (de is
NL), then (cd is NL). The rules are set based upon the
knowledge of the system and the working of the
system. The rule base adjusts the duty cycle for the
PWM of the inverter according to the changes in the
input of the FLC. The number of rules can be set as
desired. The numbers of rules are 49 for the seven
membership functions of the error and the change in
error (inputs of the FLC).
Fig. 5. Membership functions for error and change in error

2655 | P a g e
Fig. 6. Membership functions for change in duty
cycle
Table: Rule base of FLC
IV. SIMULATION RESULTS
In order to verify the proposed control
approach to achieve multi-objectives for grid
interfaced DG systems connected to a 3-phase 4-
wire network, an extensive simulation study is
carried out using MATLAB/Simulink. A 4-leg
current Controlled voltage source inverter is actively
controlled to achieve balanced sinusoidal grid
currents at unity power factor (UPF) despite of
highly unbalanced nonlinear load at PCC under
varying renewable generating conditions. A RES
with variable output power is connected on the dc-
link of grid-interfacing inverter. An unbalanced 3-
phase 4-wire nonlinear load, whose unbalance,
harmonics, and reactive power need to be
compensated, is connected on PCC. The waveforms
of
Fig. 7. Simulation results: (a) Grid voltages, (b) Grid
Currents (c) Unbalanced load currents, (d) Inverter
Currents.
Using PI controller grid voltage (Va, Vb, Vc) , grid
currents (Ia, Ib, Ic ), unbalanced load current (Ila, Ilb, Ilc,
Iln) and inverter currents
(Iinva, Iinvb, Iinvc, Iinvn) are shown in Fig. 7. The
corresponding Active-reactive powers of grid (Pinv,
Qinv), load (Pload, Qload) and inverter (Pinv, Qinv) are
shown in Fig. 8. Positive values of grid active-
reactive powers and inverter active-reactive powers
imply that these powers flow from grid side towards
PCC and from inverter towards PCC, respectively.
The active and reactive powers absorbed by the load
are denoted by positive signs. Initially, the grid-
interfacing inverter is not connected to the network
(i.e., the load power demand is totally supplied by the
grid alone). Therefore, before time t = 0.72 s, the grid
current profile in Fig. 7(b) is identical to the load
current profile of Fig. 7(c). At t = 0.72 s, the grid-
interfacing inverter is connected to the network. At
this instant the inverter starts injecting the current in

2656 | P a g e
such a way that the profile of grid current starts
changing from unbalanced non linear to balanced
sinusoidal current as shown in Fig. 7(b). As the
inverter also supplies the load neutral current
demand, the grid neutral current (In) zero after t
=0.72 s.
Fig. 8. Simulation results: (a) PQ-Grid, (b) PQ-
Load, (c) PQ-Inverter,
(d)dc-link voltage using PI controller
At t =0.72 s, the inverter starts injecting active
power generated from RES (PRES ~ Pinv) . Since the
generated power is more than the load power
demand the additional
power is fed back to the grid. The negative sign of
Pgrid , after time 0.72 s suggests that the grid is now
receiving power from RES. Moreover, the grid-
interfacing inverter also supplies the load reactive
power demand locally. Thus, once the inverter is in
operation the grid only supplies/receives
fundamental active power.
At t =0.82 s, the active power from RES is
increased to evaluate the performance of system
under variable power generation from RES. This
results in increased magnitude of inverter current.
As the load power demand is considered as constant,
this additional power generated from RES flows
towards grid, which can be noticed from the
increased magnitude of grid current as indicated by
its profile. At t =0.92 s, the power available from
RES is reduced. The corresponding change in the
inverter and grid currents can be seen from Fig. 7.
The active and reactive power flows between the
inverter, load and grid during increase and decrease
of energy generation from RES can be noticed from
Fig. 8. The dc-link voltage across the grid-
interfacing Inverter (Fig. 8(d)) during different
operating condition is Maintained at constant level
in order to facilitate the active and reactive power
flow. Thus from the simulation results, it is evident
that the grid-interfacing inverter can be effectively
used to compensate the load reactive power, current
unbalance and current harmonics in addition to active
power injection from RES. This enables the grid to
supply/ receive sinusoidal and balanced power at
UPF.
The FLC is designed with Fuzzy Logic
Toolbox. A grid voltage sample is sensed with PLL
and is used to generate the current reference signal to
provide the current injected to The grid in the same
phase and same frequency with the grid voltage.
Inverter is the classic IGBT equipped voltage source
full bridge inverter.
Fig.9. shows the various results of grid voltages, grid
currents, unbalanced load currents and inverter
currents that comes by using the fuzzy controller
instead of PI controller.
Fig.10. shows the various results of PQ grid, PQ load,
PQ inv, dc link voltage by connecting to FLC.

2657 | P a g e
Fig 9. Simulation results: (a) Grid voltages, (b) Grid
Currents (c) Unbalanced load currents, (d) Inverter
Currents using fuzzy controller
Here comparing the results of using PI
controller and Fuzzy logic controller. We can
clearly absorb the improvement in the transient state
that in case of fuzzy logic controller than in case of
PI controller. So from this we can know that by
using the Fuzzy logic controller we can improve the
stability of the system and also we can get the
smooth results as compared to other controllers.
Fig10 Simulation results: (a) PQ-Grid, (b) PQ-Load,
(c) PQ-Inverter, (d) dc-link voltage Using Fuzzy
controller.
V. CONCLUSION
This paper has presented a novel control of
an existing grid interfacing inverter to improve the
quality of power at PCC for a 3-phase 4-
wireDGsystem. It has been shown that the grid-
interfacing inverter can be effectively utilized for
power conditioning without affecting its normal
operation of real power transfer. The grid-
interfacing inverter with the proposed approach can
be utilized to:
i) inject real power generated from RES to the
grid, and/or,
ii) operate as a shunt Active Power Filter (APF).
This approach thus eliminates the need for
additional power conditioning equipment to improve
the quality of power at PCC. Extensive
MATLAB/Simulink simulation as well as the DSP
based experimental results have validated the
proposed approach and have shown that the grid-
interfacing inverter can be utilized as a multi-function
device.
It is further demonstrated that the PQ enhancement
can be achieved under three different scenarios: 1)
PRES =0 , 2)PRES
< PLoad , and 3)PRES > PLoad . The current unbalance,
current harmonics and load reactive power, due to
unbalanced and non-linear load connected to the PCC,
are compensated effectively such that the grid side
currents are always maintained as balanced and
sinusoidal at unity power factor. Moreover, the load
neutral current is prevented from flowing into the grid
side by compensating it locally from the fourth leg of
inverter. When the power generated from RES is
more than the total load power demand, the grid-
interfacing inverter with the proposed control
approach not only fulfills the total load active and
reactive power demand (with harmonic
compensation) but also delivers the excess generated
sinusoidal active power to the grid at unity power
factor.
The FLC is designed with Fuzzy Logic
Toolbox and the simulations are performed in
MATLAB/Simulink. Simulation results show that
Fuzzy logic controlled inverter output current tracks
the reference current and is in phase with the line
voltage with FLC. Also, the current harmonics are in
the limits of international standards (<5%). This
controller can be easily implemented with a controller
board, which can integrate the MATLAB/Simulink
simulations.
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A.Sudharshan was born in
Jammalamadugu, India. He received
B.Tech (Electrical and Electronics
Engineering) degree from Vaagdevi
Institute of Technology and Sciences,
Proddatur in 2010: and currently
pursuing M.Tech (EnergySystems) in JNTUACEA,
ANANTAPUR
e-mail:animelasudarshan@gmail.com
Dr. M. Yohan is a Prof & Head of
Mechanical engineering, JNTUACEA,
Anantapur. He has more than 25 years
of experience in teaching field. He started his
education from Diploma in Automobile
Engineering; he completed his Graduation in
Mechanical Engineering and Post Graduation in
R&AC. His specialization in Ph.D is IC Engines. He
was taken all degrees from, JNTUniversity, College
of Engineering, Anantapur from 1986-2013. He
published 13 International and 7 National Journals.
He also attended one National and 2 international
Conferences. Eight candidates are registered for Ph.D
under his guidance. He has membership in
professional bodies of National level like MISTE,
FIE, MSESI, MCI and Red cross life member. He was
awarded as a Best Citizen of India in 2001, issued by
International Publishing House, New Delhi.

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