AN EFFICIENT SOLAR / WIND/ BATTERY71)_Naandhini Journal_(p.430-440).pdfbidirectional power flow is...
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Int. J. Engg. Res. & Sci. & Tech. 2015 L Nagarajan and S Nandhini, 2015
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AN EFFICIENT SOLAR / WIND/ BATTERY
HYBRID SYSTEM WITH HIGH POWER
CONVERTER USING PSO
L Nagarajan1* and S Nandhini1
This project presents a method for the optimization of the power generated from a HybridRenewable Energy Systems (HRES) in order to achieve the load of typical house as example ofload demand. Particle Swarm Optimization Technique (PSO) is used as optimization searchingalgorithm due to its advantages over the other. The hybrid system consists of photovoltaic panels,wind turbines and storage batteries. The wind and PV are used as main energy sources, whilethe battery is used as back-up energy source. Two individual DC-DC boost converters are usedto control the power flow to the load. A simple and cost effective control with DC-DC converteris used for maximum power point tracking (MPPT) and hence maximum power is extractedfrom the wind turbine and the photo voltaic array. The objectives are reducing converter losses,improving efficiency of the hybrid system, and to maintaining voltage stability of the system. Themodeling of hybrid system is developed in MATLAB-SIMULINK. As well as to improve the reliabilitycost of conversion optimization problems, Improved optimization algorithms, PSO are used tosolve nonlinear hybrid analysis is any integer optimization problem. on the basis of PSO algorithmstandard techniques then there is the first step convergence factor is applied to improve thedetection performance of both migration are used to improve the ability of the algorithm to findthe best in the whole world.
Keywords: Hybrid wind-photovoltaic system, Cost minimization, Particle swarm optimization,DC-DC converter, dual active bridge (DAB)
*Corresponding Author: L Nagarajan � [email protected]
1 Engg. Annai Mathammal Sheela Engineering College, Namakkal, India.
Int. J. Engg. Res. & Sci. & Tech. 2015
Research Paper
INTRODUCTION
Global warming and climatic shift has become a
major concern now-a-days. Because of this, most
of the countries have begun to turn their attention
towards the clean green renewable energy
sources. This is currently widely used which
poses a bright future for the worlds energy needs.
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Many researchers have started to focus on this
area as these are sustainable and convenient
alternatives. This analysis provides the main ideas
for generation of the active and reactive power
references.
The unbalance created by asymmetrical loads
is analyzed, with the mathematical symmetric
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decomposition theory. An unbalanced three-
phase system can be decomposed into three
balanced symmetric three-phase systems. By
using an oscillating stator active reference,
calculated from the power and torque estimation,
it is possible to eliminate the torque oscillations
and ensure sinusoidal stator currents exchange,
thus avoiding the necessity to calculate the
positive- and negative-sequence components
(Yang B et al., 2010). The operation of the DAB
dc–dc converter has been verified through
extensive simulations. A DAB converter prototype
was designed on the basis of the proposed model
and was built for an aerospace energy storage
application. The square-wave operating mode of
DAB is the best mode for high-power transfer.
The proposed model produced key design
equations for the square-wave mode of the DAB
dc–dc converter. These equations are useful in
predicting losses that occur in the devices and
passive components and enable a study of the
converter characteristics, in addition to aiding in
the practical design of converter prototypes
(Kellogg W D et al., 1998).
For a typical PV array, the output voltage is
relatively low, and a high voltage gain is obligatory
to realize the grid-connected function.
Accordingly, an accurate steady-state model is
obtained and verified by the simulation and
experimental results, and a full-bridge inverter with
bidirectional power flow is used as the second
power-processing stage, which can stabilize the
dc-bus voltage and shape the output current. The
proposed PV system employs a high step-up ZVT-
interleaved boost converter with winding-coupled
inductors and active-clamp circuits as the first
power-processing stage, and high voltage gain
is obtained by the turns ratio selection of winding-
coupled inductors (Chedid R and S Rahman,
1997). Wind turbine generators and PV panels
have their own merits for not contributing pollution
in the environment but they require high capital
and installation costs. Wind turbine generators
and PV panels have their own merits for not
contributing pollution in the environment but they
require high capital and installation costs. The
main objective of the design criteria is to minimize
the total cost which includes initial, operational
and maintenance cost. For achieving optimal
design conditions for this hybrid system particle
swarm optimization is adopted. The hybrid offers
better reliability and lower cost compared to
individual renewable sources of energy. The use
of renewable energy offers substantial
environmental credit when compared to
conventional alternatives.
The proposed analysis allows the user to study
the interaction among economic and operational
factors and hence it offers a useful tool for the
design and analysis of cost effective hybrid power
systems (Abad G et al., 2010). Installation of
experience with traditional power design and
optimization of design and operation cannot be
seen with. To solve the problem in a
comprehensive objective function to present the
objective function of the solar wind. And reliability
of the storage cells can be calculated with an
investment of erosion format system resources,
including the number of solar cells and batteries,
but the type and amount of solar wind to change.
. This analysis allows the user to study the
interaction among economic and operational
factors and hence it offers a useful tool for the
design and analysis of cost effective hybrid power
systems (Yang Bet al., 2010). To achieve a fast
and stable response for the real power control,
the intelligent controller consists of a Radial Basis
Function Network and an modified Elman Neural
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Int. J. Engg. Res. & Sci. & Tech. 2015 L Nagarajan and S Nandhini, 2015
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Network for maximum power point tracking. Thepitch angle of wind turbine is controlled by theModified Elman Neural Network (MENN). Anefficient power sharing technique among energysources are successfully demonstrated withmore efficiency, a better transient and morestability response, even under disturbanceconditions (Naayagi R K et al., 2012; Naveen RamG et al., 2013). The wind turbine was consideredas the only source of power in this study. Usingthis model the system response to a recordedwind gust is investigated by calculating thegenerator current, the rectifier current, the loadcurrent, the battery charging current, and thebattery voltage.
The calculated results are then verified bycomparing them with the actual values obtainedfrom the data acquisition system. The accuracyof the simplified model is demonstrated bycomparing the calculated response with recordedby a data acquisition system (Amam HossainBagdadee , 2014). An accurate steady-statemodel of the converter is obtained and verified bythe simulation and experimental results. A full-bridge inverter with bidirectional power flow isused as the second power-processing stage, tostabilize the dc-bus voltage and shape the outputcurrent. Furthermore, a simple MPPT methodbased in power balance is applied in the PVsystem and represents a good performance.Furthermore, a minimum distance between thenearest existing distribution line and the load wascalculated for each of the three configurationsthat would justify the cost of installing a standalonegenerating system as opposed to constructing aline extension and supplying the load withconventional utility power (Wilmshurst S M B,1988; Borowy B S and Salameh Z M, 1997).
The technique uses linear programming
principles to reduce the cost of electricity while
meeting the load requirements in a reliable
manner. A controller that monitors the operation
of the autonomous/grid-linked systems is
designed such a controller determines the energy
available from each of the system components
and the environmental credit of the system. It then
gives details related to cost, spilled energies, and
battery losses. Hybrid solar-wind applications are
implemented in the field, where all-year energy is
Figure 1: Hybrid System
to be consumed without any chance for an
interrupt. It is possible to have any combination
of energy resources to supply the energy demand
in the hybrid systems, such as oil, solar and wind.
This project is similar with solar power panel
and wind turbine power. Therefore, neither solar
Figure 2: Block diagram of proposed system
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Int. J. Engg. Res. & Sci. & Tech. 2015 L Nagarajan and S Nandhini, 2015
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nor wind power is sufficient alone. A number of
renewable energy expert claims to have a
satisfactory hybrid energy resource if both wind
and solar power are integrated within a unique
body. In the summer time, when sun beams are
strong enough, wind velocity is relatively small.
In the winter time, when sunny days are relatively
shorter, wind velocity is high on the contrast.
Efficiency of these renewable systems show also
differences through the year.
BLOCK DIAGRAM
A. Wind Power
Wind turbines are used to convert the wind power
into electric power. Electric generator inside the
turbine converts the mechanical power into the
electric power. Wind turbine systems are available
ranging from 50W to 2-3 MW. The energy
production by wind turbines depends on the wind
velocity acting on the turbine. Wind power is used
to feed both energy production and consumption
demand, and transmission lines in the rural areas.
Wind turbines can be classified with respect to
the physical features (dimensions, axes, number
of blade), generated power and so on. For
example, wind turbines with respect to axis
structure: horizontal rotor plane located turbines,
turbines with vertical or horizontal spinning
directions with respect to the wind. Turbines with
blade numbers: 3-blade, 2-blade and 1-blade
turbines .On the other hand, power production
capacity based .classification has four
subclasses.
• Small Power Systems
• Moderate Power Systems
• Big Power Systems & Megawatt Turbines
B. Solar Power
Solar panels are the medium to convert solar
power into the electrical power. Solar panels can
convert the energy directly or heat the water with
the induced energy. PV (Photo-voltaic) cells are
made up from semiconductor structures as in
the computer technologies. Sun beam is
absorbed with this material and electrons are
emitted from the atoms that they are bounded.
This release activates a current. Photovoltaic is
known as the process between beam absorbed
and the electricity induced. With a common
principle and individual components, solar power
is converted into the electric power. Solar
batteries are produced by waffling p-n
semiconductors. A current-volt characteristic of
the PV in the darkness is very similar to that of
diode. Under beam, electron flow and current
occurs. In closed-loop, PV current passes I-
through the external load. While in open-loop, the
current completes the circuit through the p-n
diode structure Solar batteries can berepresented with an equivalent circuit of a currentsource, a resistor and a diode in parallel, and anexternal load-resistor as seen in Figure.
It is possible to insert AC-DC converter,charger, accumulator, extra power source, andcontroller depending on the design differences inoperational and functional specifications. Solartype power system could be categorized into twotypes:
Line-independent systems: These are
established in absence of line electricity to provide
Figure 3: Equivalent circuit of solar battery
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electricity. Since the current in these systems are
DC and it must be also available overnight,
energy is stored in accumulators, DC-batteries.
In case of AC-Supply requirements for the
appliances, it is possible to use DC-AC inverter.
Line-Dependent systems: These systems do
not need DC Batteries, since the energy is served
to the demand with the help of an inverter. Line
electricity is being switched in use in case of
insufficient sun beam
LOAD: It is the component responsible to absorb
this energy and transform it into work. The
diversity, amount and complexity of the behavior
of the loads that could be connected to a
photovoltaic system make difficult to be modeled.
REGULATOR: It is the element to protect the
battery against to risking situations as overloads
and over discharges. The theoretical formulation
of the model can be simple, although it is
necessary to consider the peculiar discontinuities
of the model and the inter performance with the
rest of the analyzed models.
INVERTER: The inverter allows transforming the
DC current to AC. A photovoltaic installation that
incorporates an inverter can belong to two
different situations, based on the characteristics
of the alternating network .An isolated system,
where the inverter is the element of the network
and has to feed the set of loads. The inverter is
connected to the public network, to which it sends
the energy generated by the system. The model
must be able to include both situations.
CONVERTER: The positioning of a converter
between the panels and the batteries will improve
the whole photovoltaic installation, allowing
different controls from the system.
BOOST CONVERTER: As stated in the
introduction, the maximum power point tracking
is basically a load matching problem. In order to
change the input resistance of the panel to match
the load resistance (by varying the duty cycle), a
DC to DC converter is required. It has been
studied that the efficiency of the DC to DC
converter is maximum for a buck converter, then
for a buck-boost converter and minimum for a
Figure 4: Circuit Diagram of a Boost Converter
boost converter but as we intend to use our
system either for tying to a grid or for a water
pumping system which requires 230 V at the
output end, so we use a boost converter.
MODE 1 OPERATION OF THE BOOSTCONVERTER
When the switch is closed the inductor gets
charged through the battery and stores the
energy. In this mode inductor current rises
(exponentially) but for simplicity we assume that
the charging and the discharging of the inductor
are linear. The diode blocks the current flowing
Figure 5: Mode 1 Operation of Boost Converter
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Int. J. Engg. Res. & Sci. & Tech. 2015 L Nagarajan and S Nandhini, 2015
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and so the load current remains constant which
is being supplied due to the discharging of the
capacitor.
MODE 2 OPERATION OF THE BOOSTCONVERTER
In mode 2 the switch is open and so the diode
becomes short circuited. The energy stored in
the inductor gets discharged through opposite
through an isolation transformer and a coupling
inductor L, which may be provided partly or entirely
by the transformer leakage inductance. The full
bridge on the left hand side of Fig. 1 is connected
to the HV dc bus and the full bridge on the right
hand side is connected to the low-voltage (LV)ultra capacitor. Each bridge is controlled to
generate an HF square-wave voltage at its
terminals. By incorporating an appropriate value
of coupling inductance, the secondary two
square-waves can be suitably phase shifted with
respect to each other to control power flow from
one dc source to another. Thus, bidirectional
power flow is enabled through a small lightweight
HF transformer and inductor combination, and
power flows from the bridge generating the
leading square-wave.
Although various modes of operation of the
DAB converter have been presented recently for
high power operation, the square-wave mode is
supposedly the best operating mode. This is
because imposing quasi-square-wave on the
transformer primary and voltages results in
trapezoidal, triangular, and sinusoidal waveforms
of inductor current in the DAB converter ac link.
These modes are beneficial for extending the low-
power operating range of the converter although
these modes tend to reduce the switching losses;
the voltage loss is significant due to zero voltage
Figure 6: Mode 2 operation of Boost Converter
polarities which charge the capacitor. The load
current remains constant throughout the
operation.
C) Basic Principal of Operation of Bi-directional Converter
The DAB converter that has been validated under
certain operating conditions for low load, low
efficiency, and low-power operation, but the
device average and RMS current models and
transformer/inductor RMS current models which
could serve useful for hardware design was not
proposed. Moreover, such current models are not
available in the existing literature for either low-
power or high-power converter operation. A
comparative evaluation of single- and three-phase
versions of the DAB converter was performed
the perspective of operating performance and
losses for bidirectional power conversion
applications.
The DAB converter shown below in Fig. 1
consists of two full-bridge circuits connected
Figure 7: Schematic of the DAB dc-dc converter
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PARTICLE SWARM
OPTIMIZATION
The PSO algorithm works by simultaneously
maintaining several candidate solutions in the
search space. During each iteration of the
algorithm, each candidate solution is evaluated
by the objective function being optimized,
determining the fitness of that solution. The PSO
algorithm consists of three steps, which are
repeated until some stopping condition is met,
1. Evaluate the fitness of each particle
2. Update individual and global best fitness and
positions
3. Update velocity and position of each particle
After every iteration, each particle is updated
Table 1: Average Current Model of Devicesin Dab Converter for Boost mode (PowerTransfer from the LV Side to the HV Side)
Table 2: RMS Current Model of Devices inDab Converter for Boost Mode (Power
transfer from the LV side to the HV Side)
periods in the quasi-square-wave, which reduces
the effective power transfer at high-power levels.
Therefore, the contribution highlighted in this
paper forms important research on the DAB
converter.
Figure 8: Waveforms for A Boost Convert
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by following two “best” values. The first one is
the best solution (fitness) it has achieved so far.
The fitness value is also stored. This value is
called “pbest”. Another “best” value that is tracked
by the particle swarm optimizer is the best value
obtained so far by any particle in the population.
After every iteration, each particle is updated
by following two “best” values. The first one is
the best solution (fitness) it has achieved so far.
The fitness value is also stored. This value is
called “pbest”. Another “best” value that is tracked
by the particle swarm optimizer is the best value
obtained so far by any particle in the population.
To understand the algorithm, it is best to
imagine a swarm of birds that are searching for
food in a defined area - there is only one piece of
food in this area. Initially, the birds don’t know
where the food is, but they know at each time
how far the food is. Which strategy will the birds
follow? Well, each bird will follow the one that is
nearest to the food. PSO adapts this behavior
and searches for the best solution-vector in the
search space. A single solution is called particle.
Each particle has a fitness/cost value that is
evaluated by the function to be minimized, and
each particle has a velocity that directs the “flying”
of the particles. The particles fly through the
search space by following the optimum particles.
The algorithm is initialized with particles at
random positions, and then it explores the search
space to find better solutions. In every iteration,
each particle adjusts its velocity to follow two best
solutions. The first is the cognitive part, where
the particle follows its own best solution found so
far. This is the solution that produces the lowest
cost (has the highest fitness). This value is called
pBest (particle best). The other best value is the
current best solution of the swarm, i.e., the best
solution by any particle in the swarm. This value
is called gBest (global best). Then, each particle
adjusts its velocity and position with the following
equation:
v’ = v + c1.r1.(pBest - x) + c2.r2.(gBest - x)
x’ = x + v’
v is the current velocity, v’ the new velocity, x
the current position, x’ the new position, pBest
and gBest as stated above, r1 and r2 are even
distributed random numbers in the interval [0, 1],
and c1 and c2 are acceleration coefficients.
Where c1 is the factor that influences the
cognitive behavior, i.e., how much the particle will
follow its own best solution and c2 is the factor
for social behavior, i.e., how much the particle
will follow the swarm’s best solution.
1. The algorithm can be written as follows:
Initialize each particle with a random velocity
and random position.
2. Calculate the cost for each particle. If the
current cost is lower than the best value so
far, remember this position (pBest).
3. Choose the particle with the lowest cost of all
particles. The position of this particle is gBest.
4. Calculate, for each particle, the new velocity
and position according to the above equations.
Figure 9: THD Analysis using PSO
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Repeat steps 2-4 until maximum iteration or
minimum error criteria is not attained.
EXPECTED RESULT
SIMULATIONS AND RESULTS
The proposed system is implemented in
simulation software platform. The details of
software required, coding and the experimental
results are further discussed here. The work is
done in MATLAB Version 7.12.0(R2011a). The
Image processing toolbox is made use of for the
work. The work is executed in Graphic User
Figure 10: Simulation diagramand Simulation results
WIND OUTPUT VOLTAGE
PV OUTPUT VOLTAGE
DC COMMON GRID OUTPUT VOLTAGE
AC GRID THREE PHASE OUTPUT VOLTAGE
AC PHASE TO LINE VOLTAGE
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FILTERES OUTPUT VOLTAGE
OUTPUT HARMONICS
Interface (GUI). The high dynamic range image
is produced using the software Adobe Photoshop
CS. MATLAB is a high-performance language for
technical computing. It integrates computation,
visualization, and programming in an easy-to-use
environment where problems and solutions are
expressed in familiar mathematical notation.
CONCLUSION AND FUTURE
WORK
The suggested methodology has considered both
accuracy of obtained solutions and computational
overhead of the hybrid system. This paper has
described techniques for particle swarm
optimization. In this proposed method, a hybrid
power generation system including wind power,
solar power and storage batteries is designed on
the basis of cost and their simulation results are
discussed for better understanding. The hybrid
offers better reliability and lower cost compared
to individual renewable sources of energy. The
use of renewable energy offers substantial
environmental credit when compared to
conventional alternatives. The proposed analysis
allows the user to study the interaction among
economic and operational factors and hence it
offers a useful tool for the design and analysis of
cost effective hybrid power systems. This work
can be further carried out in the future by including
the instability in the availability of the renewable
energy sources over a period of time.
REFERENCES
1. Abad G, M A Rodriguez, G Iwanski, and J
Poza (2010), “Direct power control of
doubly-fed-induction-generator-based wind
turbine under unbalanced grid voltage,”
IEEE Trans. Power Electron. vol. 25, no. 2,
pp. 442–452.
2. Amam Hossain Bagdadee ,” Using A Battery
Storage Wind / PV Hybrid Power Supply
System Based Stand-Alone PSO To
Determine The Most Appropriate,”. 1,Energy
Field of Study, AIT Volume-03, Issue-08, pp-
234-242 American Journal of Engineering
Research (AJER) 2014 .
3. Borowy B S and Salameh Z M (1997),
“Dynamic response to a stand-alone wind
Energy conversion system with battery
energy storage to a wind gust,” IEEE Trans.
Energy Convers., vol. 12, no. 1, pp. 73–78.
440
Int. J. Engg. Res. & Sci. & Tech. 2015 L Nagarajan and S Nandhini, 2015
This article can be downloaded from http://www.ijerst.com/National-Conference-on-RTCIT-2015.php#1
4. Chedid R and S Rahman (1997), “Unit sizing
and control of hybrid wind-solar power
systems,” IEEE Trans. Energy Convers.,
vol. 12, no. 1, pp. 79–85
5. Chen Z and Hu Y (2003), “A hybrid generation
system using variable speed wind turbines
and diesel units,” in Proc. IEEE Ind. Electron.
Soc. Annu.Meeting Conf., November, pp.
2729–2734.
6. Kellogg W D, M H Nehrir, G
Venkataramanan, and V Greez (1998),
“Generation unit sizing and cost analysis for
stand-alone wind, photovoltaic, and hybrid
wind/PV systems,” IEEE Trans. Energy
Convers., vol. 13, no. 1,pp. 70–75.
7. Naayagi R K, Member, IEEE, Andrew J.
Forsyth, Senior Member, IEEE, and R.
Shuttleworth, Member, IEEE “High-
Power Bidirectional DC–DC Converter
for Aerospace Applications,” IEEE
transactions on power electronics, vol. 27,
no. 11, november 2012.
8. Naveen Ram G1, J Devi Shree2, A Kiruthiga
( 2013), “Cost Optimization Of Stand Alone
Hybrid Power Generation System Using Pso
,” International Journal of Advanced
Research in Electrical, Electronics and
Instrumentation Engineering, Vol. 2, Issue
8, August
9. Wilmshurst S M B (1988), “Control
strategies for wind turbines,” Wind Eng., vol.
12, pp. 236–249, July.
10. Yang B, Y Zhao, and X He (2010), “Design
and analysis of a grid-connected
photovoltaic power system,” IEEE Trans.
Power Electron., vol. 25, no. 4, pp. 992–
1000.
11. Yang B, Y Zhao, and X He (2010), “Design
and analysis of a grid-connected
photovoltaic power system,” IEEE Trans.
Power Electron., vol. 25, no. 4, pp. 992–
1000.