Recent Researches in Electrical and Computer Engineering
The optimal placement of wind - solar hybrid power plant Using Hybrid
Particle Swarm Optimization (HPSO) In order to reduce losses in the
city of Anar
Houman Gadari, Fariba Rezazadeh
Department of Electrical engineering
Anar Branch, Islamic Azad university,Anar,Iran
[email protected]; [email protected]
Abstract: - In recent years, many countries have paid attention to Distributed Generations(DG), Because most
of the DGs are dependent on natural factors. Environmental sustainability , and are also effective in reducing
greenhouse gas. In addition to Type of energy source also the location of the source is important in power
system. We consider the location of the hybrid power plant that it have Maximum efficiency in terms of energy
absorption and increase network reliability. Heuristic methods and algorithms are tool to locate the network
resources. In this paper, locate the plant in order to reduce losses and part of the city Anar energy is done using
the HPSO algorithm and Satisfactory results have been presented in this paper.
Key-Words: - HPSO Algorithm - Wind -solar Power plant- Reduce losses- Distributed Generations(DG)
the points search space in the Anar city distribution
network for determine the best location for this plant
then connected to the network and network losses is
evaluated in the presence of the hybrid power plant.
1. Introduction
Today, with advances in technology and
changes in the economic and environmental
policies, local production of energy and distributed
generation (DG) has a good place and it is expected,
In the future, a significant portion of energy to
perform this procedure. DGs
addition to
restructuring led to the formation of the electricity
market in order to increase consumer choice and
they also to be serious economic assessment as an
alternative to purchase electricity from the grid. In
this regard, various technologies such as Micro
turbines- Diesel Generators- fuel cells and wind and
hydro small power plants and solar cells used can
find. But it depending on the area of distributed
generation technology and its climate over the years,
we have many sunny days in South East Iran also
some parts of this area winds are favorable for
plants that predispose them to create hybrid plants.
The area where the project is implemented in terms
of solar and wind energy is appropriate. Thus, at the
first is considered the optimal placement according
to the wind tunnel for the power plant then the role
of the plant to reduce losses in the electricity
distribution network is investigated.[1]
Units of solar cells(PV) and wind generator
(WG) are widely used in feeding loads in remote
areas. Since the characteristics of these systems are
almost complementary, usually used in combination
with each other. In this paper, an algorithm based on
ISBN: 978-1-61804-315-3
2. HPSO
algorithm
comparison
with
PSO
PSO method is one of intelligent optimization
methods. This method like genetic algorithm is one
of population-based methods. The method formed
based on group behavior of birds or fish swarm. In
PSO, each member of a swarm called a particle.
These particles are floating in multidimensional
space, moving and communicating. Position change
of each particle is based on knowledge and
experience of itself and neighbors. Therefore,
neighborhood should be defined in a swarm and also
the way particles communicate in order to
understand function of the algorithm. This method
includes different algorithms that the Best Global is
the perfect one and base of our function in this
article. This algorithm is in accordance with stars
topology. Movement of a particle is done according
to its experience and knowledge of all others. Thus,
it is clear that there is much cohesion in the swarm
and perfect relation among particles. Xi (t) is used to
show the position of particle -Pi in t time. Each
particle also needs parameter of velocity which is
defined as:
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Recent Researches in Electrical and Computer Engineering






Vi (t )   Vi (t  1)  1 x pbest  xi (t )    2 x gbest  xi (t ) 
(1)
Where ρ1and ρ2 are random positive numbers.
Pbest is the best particle and gbest is the best
previous experience of particles. [1]-[3]
If
If
Vi (t )  Vmax
Then
Vi (t )   Vmax
Then
Vi (t )  Vmax
Vi ( t )   Vmax
HPSO is a mechanism of PSO algorithm along
with a superior choice in particle swarm which
usually uses a set of evolutionary calculations like
genetic algorithm. The process is that some of
superior evaluated particles will be added to the set
and some of weak ones will be removed
periodically; as a result, the evolutionary algorithm
of HPSO is not stopped in local minimum and
search all over the space.[2][3]
Fig. 2. Iran wind map
In addition, the number of days or so hours of
sunshine a year in the study area for solar power ,
sun angle is another important climatic parameters
for the planning of the construction of solar power
plants . In this section we specify that The vertical
angle of the sun what angle is in every month of the
year(The angle at which the sun is at its highest
when compared to the state is studied- Anar City ).
Also the vertical angle of each Season,we describe
in detail . In April, the maximum angle of 67
degrees from the sun in the city expeditor .
Maximum angle of the sun on May is 75 degrees. In
the last month of spring sunshine maximum angle of
83 degrees. In July, the maximum angle of the sun is
75 degrees in the Anar city . In August, the average
maximum angle of the sun is 67 degrees in the Anar
city . The highest radiation angle is 59 degrees in
August in the Anar city and Maximum angle of the
sun is 51 degrees in October . In November the sun
at its highest point in the Anar city makes an angle
of 43 ° with the ground and in December a
maximum angle is 35 degrees from the sun to the
earth. In the first month of winter, the maximum
angle of 43 degrees. The sun at its highest point at
51 degrees angle with the ground up in February . In
March a maximum angle of 58 degrees from the sun
in the Anar city .
Fig. 1. flowchart of HPSO algorithm
3. Check the climatic conditions in Anar
city
Zarand city in Kerman province of Iran is
located at 30 degrees 53 minutes north latitude and
55 and is located 18 minutes east , The city is on the
way Yazd - Rafsanjan and Crossroads Tehran Bandar Abbas and Tehran - Kerman is located and
this situation is due to the relatively great time and
Distance to the center of the city ( Kerman ) is 210
Kilometer.
According to the Iran Wind map , we see that
some areas of the city ,wind energy is equal to 169.7
w/m² that it is good high rate and the average wind
speed in the region of 6.2 meters per second.
Marked on the map below .
Fig. 3. The maximum angle of radiation in the
summer in the Anar city
Therefore, the conditions listed this region is
good for a hybrid power plant .
ISBN: 978-1-61804-315-3
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Recent Researches in Electrical and Computer Engineering
3. 1. Wind -Solar Energy in the study area
Wind energy is considered equal to the entire
study area Wind energy can be extracted by passing
it through a generator blades then transfer blades
torque to the generator turbine . In this case, the
power conversion with wind density , area swept by
the blades depends on the wind speed cube . Thus,
the conversion of wind power can be achieved in
this way:
P = 1αρπ r² v³
(2)
In this formula, P be power converted to watts , α
efficiency factor , which depends on the design of
the turbine , ρ wind density in kilograms per cubic
meter , r the radius of the turbine blade in meters
and v is the wind speed in meters per second . The
volume of the air of swept area that passes through
the blades depends on the wind speed and air
density . For example, on a cold day with a
temperature of 15 ° C at sea level air density is
equal to 1.225 kilograms per cubic meter . In this
case, Passing wind speed of 6.2 meters per second at
a 100 meter radius of the rotor will caused 62000 kg
in the wind pass by the blades in swept area
approximately. The kinetic energy of a certain
volume of air is dependent on the square of its speed
and Since the volume of air passing through the
turbine related to speed linearly, The amount of
available power in a turbine is directly proportional
to cube of speed. The total power in the example
above in the turbine with a radius of 100 meters
equal to 2.15 MW that according to Betz law the
maximum amount of energy to be extracted from it
is approximately 1.15 MW that consider to wind
sector half the energy,so consider the 0.58 MW
which consists six of single turbine .[4]
In solar sector, Due to the angle of 23.5 ° is with
the axis of the Earth 's orbit around the sun ,
optimized slope of solar panel during the year is
related to the different seasons and changes. In some
cases, with respect to panels installation condition ,
it is possible change slope them and set the slope
monthly while in many cases, changing the angle of
the panels is not possible and they are to be fixed ,
The calculation of the panel optimum slope is not
difficult and is obtained by the following equation:
Watt hours per day = panel Nominal
sunlight
(4)
watt * Intensity of
As you can see, Amount of radiation depends on the
month and slope panel. For example, suppose you
have a 20 watt solar panel and I n the Anar city in
December , it is both flat and angle of 35 ° placed
and to obtain daily energy intake can be like this :
Flat panel 0.6*20w = 12 w
Panel with a slope of 35 degrees 1.05*20w= 21w
After calculation , the optimum angle of the panel
is derived based on the following table:
Time period
optimal
slope angle
First six
months of year
4ᵒ
Second six
months of year
54 ᵒ
With regard to the production of 1 MW of solar
power ,the amount of energy derived from a Hybrid
Power plant is 1.58 MW that should optimization of
the energy input Check in the Anar city power
network .
4. Placement of solar-wind power plant in
the study area:
You can see part of the Anar city's power grid which
consists of 147 bus that almost covers sensitive and
full load areas, Of course, there are other feeders on
this Substation which covers mainly agricultural
water pumps.
The panel fixed angle during the year = Latitude -90 °
(3)
Fig. 4. (Number one feeder) distribution MV feeders
Anar city power substation
Calculate the electric power production of solar
panels:
Based on the obtained data on monthly radiation by
multiplying the nominal watts of power per panel
can be found the amount of electrical energy in the
day:
ISBN: 978-1-61804-315-3
The total load on the feeder at the peak in
August Active power and reactive power are 845.6
KVAR
, 1815 KW. The power losses in the
network before installing the power plant is 154
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Recent Researches in Electrical and Computer Engineering
KW is equivalent to 8.48 % of the total load . The
proposed algorithm is written in MATLAB and after
47 repetitions with a power plant that production
capacity is 1.58 MW reached to least amount of
losses 11.5 KW that placed at number 75 bus that is
energy injected into the network by the plant.
Figure captions and table headings should be
sufficient to explain the figure or table without
needing to refer to the text. Figures and tables not
cited in the text should not be presented. Refer to
the tale below for a sample.
B
us
number
75
pla
nt
Active
power
capacity
1.5
8 MW
Loss
es before
the plant
154K
W
power
losses
after
installing
11.5
KW
algorithms", Solar Energy xxx(2013) xxx–xxx
(ARTICLE IN PRESS)
Capa
city that
has been
released
142.
2KW
5. Conclusion
With the installation of DG in distribution
network , improve the distribution network
parameters among them, it is network losses that
always been a problem for the electric company .
DG together with problem too , As you saw in the
paper to achieve maximum power from these
sources should be provided conditions, Such as the
angle of slope of the solar panels which can be
combined with this kind of resources and and the
creation of a hybrid power plant to reach maximum
efficiency in energy production .
References
1. Eftichios Koutroulis , Dionissia Kolokotsa ,
Antonis
Potirakis
,
Kostas
Kalaitzakis,
"Methodology
for
optimal
sizing
of
standalonephotovoltaic /wind-generator systems
using genetic algorithms", Solar Energy xxx (2013)
xxx–xxx (ARTICLE IN PRESS)
2. Wichit Krueasuk &Weerakorn Ongsakul
"Optimal Placement of Distributed Generation
Using Particle Swarm Optimization".
3. H. D. Chiang, J. C. Wang, J. Tong, and G.
Darling, “Optimal capacitor placement and control
in
large-scale
unbalanced
distribution
systems:system modeling and a new formulation,”
in Proc. IEEE Power Eng.Soc., 1994, pp. 173–179.
4. Eftichios Koutroulis , Dionissia Kolokotsa ,
Antonis Potirakis , Kostas Kalaitzakis, "
Methodology for optimal sizing of standalone
photovoltaic/wind-generator systems using genetic
ISBN: 978-1-61804-315-3
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