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Performance improvement of hybrid renewable energy sources connected
to the grid using artificial neural network and sliding mode control
Dr. S Vijaya Madhavi [1]
,Boda Himabindhu [2]
, Katrotu Girisha [3]
, Alakuntla Archana [4]
, Riya Sahu[5]
Department of Electrical and Electronics Engineering
MALLA REDDY ENGINEERING COLLEGE FOR WOMEN
(Autonomous Institution-UGC, Govt of India)
Maisammaguda, Secunderabad-500 100
Telangana-India.
ABSTRACT:
The main purpose of this paper to compare and
analyze three types of controllers in the three phases
DC–AC inverters in hybrid renewable energy source
(HRES) systems. To achieve this, two modern
controllers are developed and compared based on
sliding mode control (SMC) and artifcial neural
network techniques. The HRESs comprise
photovoltaic (PV), wind turbines, battery storage
systems, and transmission lines connected to infnite
bus bars via a step-up transformer. The developed
controllers at the inverter side utilize both voltage
control and current regulation. A DC–DC boost
converter is employed to set up a voltage demand at
the point of common coupling (PCC). Then, the
formulation of an HRES with the developed
controllers is presented. The developed controllers
are considered to operate under various solar
radiations, temperatures, and wind speed loading
conditions.
INTRODUCTION:
Most people throughout the world are interested in
switching from diesel to renewable energy. Clean
energy, which is what we call renewable energy, does
not contribute to environmental degradation. Since
the usage of fossil fuels for energy has resulted in a
steady decline in air quality throughout the world, it
is imperative that the world transition to renewable
energy sources. [1]. Numerous studies in various
fields rely heavily on controllers. Using this method,
researchers may acquire the necessary feedback from
a variety of controller kinds. Three distinct inverter
controller architectures have emerged as the norm in
recent studies. PI control is a common sort of
traditional control used in manufacturing and other
fields where automatic process regulation is required.
Sliding mode control (SMC) is a type of
discontinuous control that is referred to as adaptive
control. It is a robust control method SMC is
composed of equivalent control, and it maintains
trajectories on the sliding surface and variable
structure .SMC was used to improve convergence
performance by designing suitable parameters for the
traditional SMC Traditional SMC has been widely
applied in nonlinear systems due to its ease of
implementation, fast response, and robustness to
disturbances and uncertainties ANN is a cutting-edge
The International journal of analytical and experimental modal analysis
Volume XV, Issue X, October/2023
ISSN NO: 0886-9367
Page No: 442
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method of control. The great pattern recognition
power of ANNs has led to its use as a technique of
estimate across many branches of engineering. ANNs
have benefts such as the fact that they do not have
any requirements for knowledge of internal system
parameters, which results in the less computational
efort and provides a more compact solution. In
addition, ANNs have been used to solve very
complex problems . The authors of developed a PV
with SMC at three phases grids connected with an
LCL flter. In HRES systems, this gives even more
impetus for the advancement of adaptive and cutting- edge controllers. While there is a plethora of
literature on SMC and ANN in a variety of fields,
research on the use cases and comparative
evaluations of ANN and Spm controllers for
networked HRES is scarce. With such a difficult goal
in mind, this work provides the following
improvements to the existing body of knowledge:. (1)
Developing SMC and ANN control techniques. (2)
Verifying the efectiveness of the developed SMC and
ANN through a fair comparison with classical PI
controllers, integral order PI controllers, adaptive
controllers, and advanced controllers, while
considering the changeable conditions of PVs
(irradiance and temperature) and wind turbines (wind
speed). (3) Presenting a mathematical formulation for
a HRES system and developing a dynamic
MATLAB/Simulink formulation with the developed
controllers. The HRES in this paper is a combination
of PV and wind turbine systems with battery storage.
Renewable energy is collected from renewable
resources, which are naturally replenished on a
human timescale, such as sunlight and wind, and a
system of energy storage is used to supply the power
demand during bad weather . Power is generated by a
solar PV array (model SPR-305E-WHT-D), stored in
a Ni-MH Battery (model 200 V, 6.5 Ah), and
generated by a wind turbine (model PMSG). The DC- DC converters link the three different power sources
together. Wind power generation systems using PI
controllers use maximum power point tracking.
Using a phase-locked loop (PLL), DC electricity
from the D-bus bar is transformed into three-phase
AC power. The PLL is utilised to invert a two-pole
line into a three-phase alternating current one.
SYSTEM DESCRIPTION
igure 1 shows the HRES proposed in this paper. The
system consists of a wind energy system, a PV
energy system, a battery storage system, a DC–DC
converter, a DC link, a 3-phase inverter, PI, SMC,
and ANN controllers, a step up 3-phase transformer,
and the grid.
PV SYSTEM
The PV mathematical modeling of PV panels is an
important step in the analysis and design of
photovoltaic control systems. Figure 2 presents a one- diode model of a PV cell. This electrical equivalent
circuit of a PV cell introduces the efect of series
resistance Rs while neglecting the efect of shunt
resistance Rsh. Equations that describe the
relationship between the voltage and current of the
PV cell are given as:
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From Fig. 2, the output current of the PV cell (Ic) is
estimated as the subtraction of the photo-generated
current (Iph) and the diode current (Id) illustrated in
Eq. (1). Thus, the PV cell output voltage is calculated
from Eq. (2). For PV module consisting of ns: the
series-connected cells, output current (I), and voltage
(V) of the PV module are presented in (3) and (4),
respectively. Photo-generation as a function of solar
radiation (G) and temperature (T) is given in Eq. (5),
and the reverse saturation current (Io) is estimated in
Eq. (6). The module output power can be detected
simply as the product of the output voltage and
current of the PV module as given in Eq. (7) [26].
From the PV model, the I–V curve and P–V curve are
given in Fig. 3. The incremental conductance plus the
integral regulator technique is utilized to fnd the
global MPPT of the PV module.
Wind turbine
The permanent magnetic synchronous generator
(PMSG) is one of the most common types of wind
turbine energy source used. It has more gravity in
wind-energy applications since it has a magnetic feld
instead of winding. In addition, it has several
advantages. It has over-fxed speed generation such as
increased energy capture, it is operated at the MPP,
its efciency is improved, and it has highquality
power. The PMSG has received a great deal of
attention in wind energy applications, has high- efciency, and has high power factor operation
.
The tip speed ratio of a wind turbine can be
calculated in (15). Figure 4a shows a typical Cp
versus λr curve for the PMSG of a wind turbine. To
track the maximum power from a wind turbine, the
wind turbine should operate at the optimal tip speed
ratio (λopt), which gives the associated maximum
power coefcient (Cpmax) obtained from Fig. 4b.
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Page No: 444
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Consequently, the maximum power is obtained from
Fig. 4d. This is controlled via the control circuit
illustrated in Fig. 4c.
A controller is used to delimit the blade pitch angle
(β) in accordance with the generator speed. The wind
turbine model receives the pitch angle together with
the generator speed and the wind speed to provide the
required mechanical torque to the PMSG generator as
demonstrated in Fig. 4c. The optimal tip speed ratio
(휆) is controlled based on the generator and wind
speeds. Another controller is employed to determine
the optimal power coefcient (CP) to maximizes the
wind extracted energy as shown in
topology of the DC/DC boost converter, which is
presented in Sect. 2.4, was utilized for both the PV
module and wind turbine based-PMSG. The collected
power from the PMSG is rectifed through a three- phase bridge rectifer and fed to the DC/DC converter.
At this bus, the harvested energy from all of the
resources is fed to the DC/ AC inverter, which tries to
maximize the power provided to the grid.
Battery storage
The Ni-MH battery is used in this HRES and it is
connected to a DC–DC boost converter. It is very
important in this system [29] due to the intermittent
nature of renewables. The battery storage has a great
deal of usage such as providing the power demand to
the grid and local loads
PROPOSED CONTROLLERS:
As shown in Fig. 6, the overall controller system uses
four steps simultaneously. First, the controller starts
by converting the stationary reference frame voltages
and currents into the corresponding rotating reference
frame values via Park’s transformations. Thus, the
currents (Iq and Id) are compared with the
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commanded references. In the second control loop, a
process regulates the AC voltage that controls the
size of the AC voltage from the VSI where the
reference current (Iqref) is accordingly set to zero to
maximize the power supplied to the grid. Thus, the
VSI is operated at a unity power factor. The DC-link
capacitor voltage is sensed and fed to the regulator,
which sets the d-axis current command (Idref). The
second and third controls are developed particularly
for regulating the size and phase of the VSI output
currents at appropriate values under diferent
operating conditions in terms of wind and solar
radiations to maintain the inverter output power
factor. The outputs of the current regulators are
transferred into the PWM block, which in turn sends
signals to the VSI electronic switches. Another
important issue is related to the AC/DC VSI used to
integrate the HRES system. Therefore, the PLL loop
is used for frequency sensing, where the angle (θ) is
generated so the other regulators and consequently
the electronic switches work in harmony to supply
power to the main grid. Figure 7 demonstrates a
complete flowchart of the proposed control
techniques, where each of the regulators is decided
according to the controller type.
Classic proportional integral controller (PI)
PI control is still the most popular type of industrial
control. The PI controller is the type of classic
control. PI control has two constant parameters: Kp
for the proportional term, and Ki for the integral
term. The PI controller is considered to be an
automatic controller and an important technique [33]
that it has been used in HRESs. It is a stable state
error of zero to step input the operation of long-term
conditions. The summation of the two terms adjusts
the process through a control element as in (17).
Figure 8 shows a schematic diagram of the internal
structure of the PI block.
Sliding mode control (SMC)
SMC is a type of discontinuous control that it is used
in the controllers of variable structure systems. This
method has complex computations and requires
measurements .
In SMC control systems, the operating point moves
through or moves within the sliding surface. At any
instant of time, the controller output is composed of
two terms. The frst one is the area of error versus
time, and the other is the extent of the error. The
proportion gain can increase the response of the
output controller and control accuracy of the system
by using sliding mode control. For the HRES system
input, the general equations for a simple description
of SMC are given in (18) and (19).
The sliding surface design is obtained as follows. The
frst is the defnition of a certain scalar function of the
system state, σ (x): Rn→ R. Often, the sliding surface
depends on the tracking error ey(t) together with a
certain number of its derivatives.
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The function σ should be selected in such a way that
its vanishing at the steady-state gives rise to a stable
diferential equation. Any solution, ey(t), of the
diferential equation eventually tends to zero. The
most typical choice for the sliding manifold (surface)
is a linear combination of the following as in (21).
The control input design is obtained as follows. The
main purpose of this step is to select a controller
action at the sliding manifold (surface). The control
action is able to steer σ to zero in a fnite amount of
time. The standard (or frst-order) sliding mode
control is employed in this work to control in the
inverter of the HRES. The control is discontinuous
across the manifold. A SMC block of a VS regulator
controller is shown in Fig. 9. A current regulator
controller block of a SMC is shown in Fig. 10.
Simulation results
G
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Vw
Ppv
VabcB1
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IabcB1
CONCLUSION:
This paper introduced a comparative analysis of two
modern controllers for three-phase grid-connected
HRES. The problem of transferring power to the
main grid was tackled via developing current and
voltage regulators. The developed SMC and ANN
have high capability in terms of keeping the HRES
stable under various wind speeds, irradiations, and
loading conditions. The effectiveness of the SMC and
ANN controllers was demonstrated by a fair
comparison with the classic PI controller. Based on
digital simulation results, the following conclusions
can be drawn. (1) The developed controllers are
straightforward and have strong capability when it
comes to damping out oscillations with short settling
times. (2) The developed regulators avoid
complicated signal measurements since they rely on
voltage at the DC-link as well as voltages and
currents at the inverter side without complicated
power measurements. Then the HRES presented in
this research is considered as an initial step to
enhancing the power provided to the grid. It seems
that solar radiation and wind speed variations have
more impact on the power delivered to the grid than
PV ambient temperature.
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ISSN NO: 0886-9367
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