This document discusses optimization techniques for sizing hybrid photovoltaic (PV) and wind energy systems. It describes three common sizing methods - yearly average, worst month, and loss of power supply probability. It also covers optimization techniques like graphical construction, probabilistic, iterative, and artificial intelligence methods. These techniques are used to simulate different system configurations and minimize total cost while maintaining reliability. The document concludes that hybrid systems can significantly reduce life cycle costs compared to standalone systems, while providing a more reliable power supply through combining energy sources.

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Investigation of Optimal Sizing Techniques in Hybrid PV-Wind Energy
Conversion Systems
V. Rajesh Kumar1, K. Suriaprakash2, S. Premnath3
1AP/EEE, PSN CET, Tirunelveli, Tamil Nadu, India
2HoD/EEE, R.V. Reha Polytechnic College, Paruvakudi, Tamil Nadu, India
3HoD/EEE, Sri. S.R.N.M. Polytechnic College, Sattur, Tamil Nadu, India
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Abstract- This paper introduces a basic report philosophy
and systems to enhance the size of a hybrid photovoltaic
(PV) and wind generator energy(WG). The estimating
strategies surveys the diverse hybrid PV–Wind sustainable
power source hybrid frameworks utilized for power
optimization. This paper outlines three basic utilized
measuring procedures for PV–Wind frameworks. In addition,
the paper will talk about some streamlining methods of the
PV–Wind these procedures are utilized to look at the
specialized exhibition and cost of vitality for various
framework arrangements utilizing reenactment approaches.
Keywords: Wind/PV Hybrid; Sizing; Optimization.
1. INTRODUCTION
Hybrid Renewable Energy Systems (HRES) are
characterized as an electric energy framework which is
comprised of at least one sources. These sources could be
unsurprising or renewable or blended, that works in off-
framework or in an on matrix united mode. The center
component of hybrid renewable energy systems is to
syndicate at least two renewable powers thus they can
address releases, consistency, effectiveness, and practical
restrictions of single renewable energy source. HRES are
getting to be famous for individual power age in
disconnected region because of the improvement and
efficiency increase in renewable energy advancements and
power electronic converters. In view of the availability of
the common neighborhood assets, there are a few points of
interest of the hybrid framework. Higher natural security,
green house gas emanation, particularly CO2 and
abatement in different toxins emssions is relied upon
because of the lower utilization of fuel. The cost of sunlight
based and wind energy can be sensible with atomic and the
decent variety and security of characteristic assets who are
free, sufficient, and immense. The majority of these
apparatuses can be effectively introduced and they are
quick conveyed. Monetarily, the expenses are predictable
and not slanted by fuel value vacillations. Be that as it may,
in view of the photograph voltaic (PV)– Wind erratic
nature and reliance on climatic changes and climate, a
typical downside to PV and wind control ages is that both
would need to be larger than usual to make their
independent systems dependable for the occasions when
neither one of the systems is creating enough electric
capacity to satisfy the heap.
In the most recent decade, a few HRES have been
introduced in various nations, bringing about the
expansion of systems that can play with regular; fuel based
remote zone power supplies. In any case, there are a few
mixes of hybrid energy framework which for the most part
rely upon the regular accessible assets, the wind or the sun
oriented energy for all intents and purposes speaks to one
wellspring of the hybrid renewable energy systems. With
the development improvement of the hybrid PV–Wind
systems for electrical power age, the objective to
accomplish reliable and proficient execution wound up
troublesome assignment.
This paper condenses three regular utilized measuring
strategies for hybrid PV–Wind systems. Additionally, the
paper will examine some streamlining procedures of the
PV–Wind HRES. These methods are utilized to look at the
specialized presentation and cost of energy for various
framework designs utilizing recreation approaches. The
points of this examination is to analyze the hybrid sun
oriented wind systems estimating strategies for
streamlining.
2. PV-WIND ENERGY
The utilization of little disconnected HRES is required to
develop hugely sooner rather than later, both in creating
and industrialized nations.
Sun based and wind are normally relating as far as the
two assets being all around coordinated to hybrid systems.
HRES consolidate PV–Wind systems to benefit as much as
possible from the territory's occasional sunlight based and
wind assets; sun powered moderately increasingly
accessible in summer months and during winter's sunlit
days and with wind generally progressively accessible in
winter months and around evening time.
These HRES give a more steady all year yield than either
sunlight based or wind-just systems and can be intended to
accomplish wanted characteristics at the most reduced
conceivable expense. Most HRES have reinforcement
control through batteries or/and diesel motor generator.
Additionally, Fig. 1 shows about PV framework capital
expenses of three basic PV advancements. The expense of
power of the three PV advancements has tumbled from 15
to multiple times; and network associated PV systems
presently sell for around 5–10$ per crest Watt (20–50
¢/kWh), including bolster structures, control molding, and

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land. Interestingly, the framework effectiveness of the
three advances has expanded to around 10–13% , the wind
capital expense of class 4 and 6 wind turbines is appeared
in Fig. 2. The expense of the two systems has dropped by
180 $ per kW over the most recent two decades.
The two Figs. 1 and 2 shows guaranteed figures for the
genuine speculations of the sun based and wind HRES, the
ideal structure of hybrid framework ends up troublesome
through vague renewable energy supplies equivocal
burden request, non-straight qualities of the assets with
the expanded multifaceted nature, the requirement for
down to earth estimating and ideal configuration turns
into a significant issue.
3.ESTIMATING TECHNIQUES OF PV-WIND HRES
Before the installation of a new HRES, it is essential
sizing using instinctive method of the individual
components to obtain the initial capital investment cost
and possibility study . Division sizing is basically a method
of defining the right practical sizing of the HRES
components by reducing the system cost,while
maintaining system consistency.
The right sizing is to decide the wind generator limit
(size and number of wind turbines), the number of PV
boards and number and limit of battery banks required for
the standalone framework. Note that it is essential to keep
up ideal asset the executives in a hybrid age framework so
as to maintain a strategic distance from wrong sizing. Over
sizing the framework segments will build the framework
cost though under sizing can prompt disappointment of
intensity supply to satisfy the heap prerequisites.
The literature has presented three techniques of sizing.
Chart-1: Capital cost for PV system with different
technologies.
Chart-2: Capital cost of wind system with different classes
3.1The Yearly month to month normal estimating
method
The PV boards and wind generators size are resolved
from the normal yearly month to month estimations of
energies explanation. This computation depends on the
normal yearly month to month information of sun
powered radiation and wind speed.
3.2 The Most Troublesome month method
The PV and wind generators are being determined in the
most horrible month. For the most part the month most
contradicted in wind is sure in illumination. Here the
framework must be dimensioned in two most contradicted
months (restricted illumination and wind months). At the
point when the framework worked in these months it's
consequently worked in different months.
3.4 Loss of power supply probability (LPSP)
technique
The LPSP is the likelihood that a lacking force supply
results when the HRES can't fulfill the heap demand . This
procedure comprises in deciding the ideal number of the
batteries and the PV modules as indicated by the
enhancement standard knowing: the unwavering quality,
which depends on the idea of the likelihood of loss of
energy, and on the expense of the framework. This strategy
exhibits the bit of leeway that the presenting of the wind
generator licenses to limit the expense of the PV
standalone framework, by limiting the size of the PV
generator and capacity number of batteries .Two
techniques can be utilized for the utilization of the LPSP in
structuring an off-matrix hybrid PV–Wind HRES. The first
depends on ordered reproductions. The subsequent
methodology utilizes probabilistic procedures to
coordinate the unsteady idea of the asset and the heap,
accordingly taking out the requirement for time-
arrangement information.
4. OPTIMIZATION TECHNIQUES OF PV -WIND HRES
Optimization techniques for PV–Wind HRES when all is
said in done, are utilized to furnish the best framework
sizing with least expense. Numerous techniques are
utilized for this reason, however the most famous models

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are changed in this part, to be specific Graphic
Construction, Probabilistic, Iterative and Artificial
Intelligence optimization techniques.
Optimization techniques of the PV–Wind HRES are
utilized to set up the ideal configuration of renewable
energy configuration. Reenactment techniques are utilized
to think about the exhibition and cost of energy for various
framework configurations. A few software instruments are
accessible for structuring of hybrid systems, for example,
homer.Contingent upon the benefit capacity of the
metrological information, two methodologies are pursued
to accomplish the right ideal sizing. The ordinary
techniques depend on the energy equalization and
dependability of supply and they utilize the metrological
climate information. In the event that the climate
information are not accessible, the framework must be
improved utilizing various techniques as will be talked
about in this area.
4.1 Realistic Development Procedure
This technique can configure the optimum combination
of PV array and battery for a standalone hybrid PV–Wind
system based on using long-term data of solar radiation
and wind speed recorded for every hour of the day for very
long years. Other applications used the monthly-average
Markvart . For given load and a desired LPSP, the optimum
sizing of the HRES PV–Wind can be achieved by supposing
that the total cost of the system is linearly related to both
the number of PV modules and the number of batteries.
The minimum cost will be at the point of tangency of the
curve that represents the relationship between the number
of PV modules and the number of batteries.
4.2 Probabilistic technique
The impact of variety of the sun powered radiation and
wind speed are the principle factors in the framework
structure of this technique.. The likelihood thickness for
day by day augmentation or decrement of capacity level
was approximated by a two-occasion or three-occasion
likelihood circulation. This strategy was reached out to
represent the impact of correspondence between everyday
radiation esteems.
Different applications exhibited the probabilistic
technique dependent on the convolution technique. The
fluctuating idea of the assets and the heap is fused, in this
way killing the requirement for time-arrangement
information for the evaluation.
4.3 Iterative technique
The iterative optimization technique pursues the LPSP
model and Leveled Cost of Energy model for power
unwavering quality and framework cost, individually.
Three sizing parameters are considered, for example the
limit of PV framework, appraised intensity of wind
framework, and limit of the battery bank. For the ideal
LPSP esteem, the ideal configuration can be recognized at
last by iteratively looking through all the potential
arrangements of configurations to accomplish the most
reduced Leveled Cost of Energy.
An iterative optimization technique was displayed to
choose the wind turbine size and PV module number
utilizing an iterative system to have the effect between the
produced and demanded control (DP) as near zero as
conceivable over some undefined time frame. From this
iterative technique, a few potential blends of PV–Wind age
limits were acquired. The all out yearly expense for every
configuration is then determined and the stage with the
lowermost expense is assigned to speak to the ideal blend
4.4 Artificial intelligence technique
There are diverse man-made consciousness techniques
which are generally used to streamline a HRES so as to
boost its monetary advantages, for example, Genetic
Algorithms, Artificial Neural Net-works and Fuzzy Logic.
Hereditary Algorithms are additionally comprehensively
utilized in the proposition of huge power conveyance
systems in light of their capacity to handle complex issues
with direct or non-straight cost capacities. Ideal sizing
technique dependent on Genetic Algorithms by utilizing
the Typical Meteorological yearly information, while
wanted LPSP with least Annualized Cost of Sys-tem is kept
up. Two optimization factors that are not usually observed,
PV cluster incline edge and turbine establishment tallness
have been considered. Such calculations are pertinent for
the traditional optimization strategies, for example,
dynamic programming and slope techniques.
Contrasting between the referenced models has been
made, which they are the most pervasive models,
consequently Graphic Con-struction, Probabilistic, Iterative
and Artificial Intelligence has been looked at in term of
precision, time utilization and intricacy. In Table 1,
exactness of optimization techniques arranged as (high,
low, reasonable) and for time utilization as (quick, long,
reasonable). Other than the class of unpredictability as
(high, low, reasonable).
Iterative and computerized reasoning techniques have a
superior outcome than different techniques due to low
average of RMS mistake esteem. From the opposite side
realistic development and probabilistic techniques are
basic with the worthy exactness. Moreover, Iterative and
man-made consciousness are more unpredictable than the
other two techniques. At long last, choosing the
optimization technique rely upon embraced criteria,
accessible data, and straightforwardness and exactness of
the technique.

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Table -1: Technical details of the load and different
sources
Modeling technique Accuracy Time Complexity References
consumption
5. CONCLUSION
This investigation tends to the ideas of off-lattice
HRES for electrical power age. HRES permits high
amplification in the power unwavering quality, with high
precision and quick optimization techniques, high
framework effectiveness, and decrease the framework
necessities for stockpiles gadgets. The paper has likewise
exhibited distinctive sizing techniques for off-network PV–
Wind HRES. Definite sizing of HRES can fundamentally
decide the underlying capital speculation while keeping up
framework unwavering quality at least expense. The
optimization techniques of the PV–Wind HRES were
additionally talked about. It has been shown that hybrid
energy systems can altogether lessen the all out life cycle
cost of stand-alone power supplies by and large, while in
the meantime giving an increasingly solid supply of power
through the mix of energy sources. By and by hybrid power
systems may comprise the most affordable arrangement in
numerous applications.
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[2] Erdinc O, Uzunoglu M. “Optimum design of hybrid
renewable energy systems”: Overview of different
approaches. Renew Sustain Energy Rev
2012;16:1412– 25.
[3] Marques AJ, Boccaletti C, Ribeiro EFF. “Uninterruptible
Energy Production in Standalone Power Systems for
Telecommunications” presented at the Inter-national
Conference on Renewable Energies and Power Quality
(ICREPQ’09) Valencia (Spain), 2009.
[4] Chong WT, et al. “Techno-economic analysis of a wind–
PV hybrid renewable energy system with rainwater
collection feature for urban high-rise applica-tion”.
Appl Energy 2011;88:4067–77.
[5] Kazem HA. “Renewable energy in Oman: status and
future prospects”. Renew Sustain Energy Rev
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BIOGRAPHIES
V. Rajesh Kumar, Working as AP/EEE in PSN
CET Tirunelveli. He has completed his B.E.
(EEE) in the year of 2009, at IFET College of
Engineering Villupuram. He also done
Doube Master Degree in the Specialization
of CSE and Power Electronics in the year of
2011 and 2018 at P.S.R. Engineering College,
Sivakasi respectively. Moreover he has published more
than five International Journals particularly in ICTACT and
IOSR. He is an active member in Technical society like of
ISTE, MIACSIT, MIAENG.
Suriaprakash. K, presently working as
HoD/EEE in R.V. Reha Polytechnic College,
Paruvakudi. He has completed his B.E. (EEE)
and M.E., (PED) in the year of 2014 and
2018 at P.S.R. Engineering College
respectively; he has industrial and teaching
experience. Moreover he is an active life
member in ISTE, IEEE.
Premnath.S ,presently working as
HoD/EEE, in Sri. S.R.N.M. Polytechnic
College, Sattur.He has completed his B.E.(
EEE) and M.E.,(PED) in the year of 2016
and 2018 at P.S.R. Engineering College
respectively,he has interest in power
system Analysis and renewable energy
system. Moreover he is an active life member in ISTE, IEEE
.
Realistic Development
Procedure
Low Fast Low
Probabilistic
technique
Fair Fast Low
Iterative
technique
High Long High
Artificial intelligence
technique
High Long High