A review of optimization techniques for hybrid renewable energy systems

Abstract

Solar photovoltaic and wind power systems are very much dependent on climate variations. Wind and solar photovoltaic systems are unreliable without storage units like batteries and diesel generators as a backup. The addition of storage devices increases the reliability of the hybrid system consisting of solar photovoltaic and wind turbines. During cloudy and slow windy days, sufficient battery bank capacity is required to meet the load demand. This review paper gives new ways of hybrid energy generation. It discusses several optimization approaches and ideas for hybrid networks. Hybrid systems are gaining more popularity and fame in the current energy crisis scenario and environmental pollution. This research has provided a comprehensive assessment of existing optimization strategies, particularly those associated with the isolated microgrid in the literature. Artificial intelligence offers noteworthy optimization for microgrid operation without long-term weather data, as evidenced by the current optimization pattern for hybrid renewable sources.

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A review of optimization techniques for hybrid
renewable energy systems
Mohammad Shariz Ansari, Mohd. Faisal Jalil & R.C. Bansal
To cite this article: Mohammad Shariz Ansari, Mohd. Faisal Jalil & R.C. Bansal (2022): A review
of optimization techniques for hybrid renewable energy systems, International Journal of Modelling
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A review of optimization techniques for hybrid renewable energy systems
Mohammad Shariz Ansari
a
, Mohd. Faisal Jalil
b
and R.C. Bansal
c,d
a
Department of Electrical and Electronics Engineering, KIET Group of Institutions, Ghaziabad, India;
b
Department of Electrical Engineering,
Faculty of Engineering and Technology, Aligarh Muslim University, Aligarh, India;
c
Department of Electrical Engineering, University of Sharjah,
Sharjah, United Arab Emirates;
d
Department of Electrical, Electronic and Computer Engineering, University of Pretoria, Pretoria, South Africa
ABSTRACT
Solar photovoltaic and wind power systems are very much dependent on climate variations. Wind
and solar photovoltaic systems are unreliable without storage units like batteries and diesel
generators as a backup. The addition of storage devices increases the reliability of the hybrid
system consisting of solar photovoltaic and wind turbines. During cloudy and slow windy days,
sucient battery bank capacity is required to meet the load demand. This review paper gives new
ways of hybrid energy generation. It discusses several optimization approaches and ideas for
hybrid networks. Hybrid systems are gaining more popularity and fame in the current energy crisis
scenario and environmental pollution. This research has provided a comprehensive assessment of
existing optimization strategies, particularly those associated with the isolated microgrid in the
literature. Articial intelligence oers noteworthy optimization for microgrid operation without
long-term weather data, as evidenced by the current optimization pattern for hybrid renewable
sources.
ARTICLE HISTORY
Received 14 June 2022
Accepted 28 August 2022
KEYWORDS
Optimization techniques;
Hybrid renewable energy
systems (HRES); Solar
photovoltaic systems; Wind
turbine system; Artificial
intelligence
1 Introduction
Energy plays an innovative role in economic and social
progress everywhere. These days, almost everywhere
globally, energy demand is being supplied by fossil
fuels considering increasing population, increasing
load requirements, and exhaustion of diesel.
Generations of electrical energy have gone into another
phase of progress, which deeply portrays the develop-
ment of climate change; the economy based on hydro-
carbon changes the effective organization of the energies
[1–4].
Petroleum products that represent natural gas, coal,
and oil are the world’s primary energy sources. The
twentieth century’s reliance on non-renewable energy
sources depleted the natural reserve of these resources.
Primarily utilized renewable energy sources (RES)
mainly are wind turbine generators (WTG), solar
photovoltaic (SPV), and hydropower. RES is
a significant alternative source, so these are considered
in various countries. Hybrid renewable energy systems
(HRES) can combine WTG, hydropower, and SPV. In
such scenarios, there are storage batteries and diesel
generators in the form of a backup unit to meet the
demand for the peak hour. Optimizing the proposed
design is necessary to make good use of electrical energy
by using energy sources such as WTG, SPV, and build-
ing management systems [5,6].
Almost all the RES like WTG and SPV are environ-
ment-friendly and clean. The hybrid microgrid, com-
bined with WTG and SPV, has been analyzed by many
researchers. It is clear from the analysis that HRES
performance is better and less expensive than individual
WTG or SPV systems [7–10]. If hybrid WTG and SPV
are not correctly designed, there are fewer disadvantages
than conventional sources. For example, the heteroge-
neous nature of solar radiation and wind speed, which
fluctuate in power generation, can be compensated
using the storage battery bank. These batteries can
store the extra power, and the load is supplied when
there is a shortage of electricity [11]. The overseeing
problem of WTG and SPV avoids using the battery
storage system. If the battery is at its maximum charging
state and there is still some extra power available, it
should be avoided if the unit loses generation. The
cost of energy (COE) can be reduced by decreasing
this unutilized excess power. The use of a storage battery
system also reduces the oversizing problem of WTG and
SPV sources [12]. However, when the battery has
charged to its extreme value and is still lost with the
additional power generation units, which is to be
avoided sometimes. Lowering this unused extra energy
can reduce the cost of energy (COE) [13]. Therefore, the
optimum size of all renewable energy sources (RES) is
essential to confirm the genuine load.
CONTACT R.C. Bansal rcbansal@ieee.org Department of Electrical Engineering, University of Sharjah, Sharjah, United Arab Emirates
INTERNATIONAL JOURNAL OF MODELLING AND SIMULATION
https://doi.org/10.1080/02286203.2022.2119524
© 2022 Informa UK Limited, trading as Taylor & Francis Group

Electrical energy production has attracted more
attention to alternative energy sources such as WTG
and SPV. Since the 1970s, electrical energy has been
widely used to replace fossil fuels due to the crisis of
oil. Still, such alternate energy sources are slow to
develop, and transformation to another development
phase appears to be difficult due to the various acumens
of the problems [14]. Environment and cost-effective
issues are not only pleasing but also other factors like
societal and emotional impact on people’s behavior
[15]. Apart from this, new approaches for energy pro-
duction from alternate energy sources have tested the
improvement in the efficiency of microgrid generation
and the reliability of electric energy production nets in
alternate sources, including communication and infor-
mation technology practices. That is why an electrical
firm is developed as a more flexible and dynamic and
supports distributed units of storage [16]. However, in
some alternate energy like WTG and SPV, as
a stochastic nature, the transition to squat carbon civi-
lization will need a multi-solution [17].
Non-renewable resources such as fossil fuels can be
replaced by renewable energy sources, which will
require specialist forecasting. It will be combined and
required for multi-HRES, such as WTG, SPV, Hydro,
Geothermal, Biomass (BM), nuclear, and Hydrogen at
the central part of power generation and customer level
in reorganized RES [9,10,18]. HRES is a term used to
describe a power system with two or more energy
sources. Compared to techniques that employ only one
energy source, these systems occasionally have the best
reliability and lowest cost. As a result, the adoption of
HRES in the power market is contingent on the primary
technique that may be used to optimize the design of
various types of HERS [19]. The optimization difficul-
ties are explored to choose the ‘best’ collection of system
elements from a search space or set of feasible solutions.
It includes a selection of one or more optimization
problems and problem constraints and an Objective
Function (OF). One or more optimization variables
should drive the limitations and the OF [20].
Furthermore, due to the non-linear behavior of the
system components, the problem becomes even more
challenging in a few RES (for example, WTG and SPV),
the stochastic obtained ability, the optimization vari-
ables, and considered constraints. Electric energy has
an essential role in the personal and economic HRES
[21]. A well modeled HRES has a good result in various
parameters such as it reduces cost, improving the qual-
ity of life, and high reliability. In maximum cases, WTG
and SPV supplement each other; though, both systems
are very unorthodox in terms of rapid variation of wind
and solar insolation speeds. The WTG-SPV and hydro-
power hybrid systems were used by references [22,23] in
the remote villages of Nepal. Reference [24] gives fea-
tures for a separate microgrid HRES and their effect,
which are related to the consistency of the microgrid.
HRES is exceptionally dependent on its element. So, the
accurate modeling of each component for HRES pro-
vides a tool to identify the model’s operation better and
helps optimize HRES [25]. This paper reviews the opti-
mal sizes for hybrid power systems on large-scale opti-
mization criteria and small WTG, SPV, hydropower,
and battery storage devices. Tables have shown optimal
design and numerous optimization ways to help you
understand easily [26]. Wherever necessary, flow charts,
mathematical models, and figures have been included.
Using appropriate references will show a new trend in
the global energy situation and develop restraint on
future energy demand of the load. Various mathemati-
cal models such as probabilistic approaches [27–29],
genetic algorithms (GAs) [30,31], artificial neural net-
works (ANN), and particle swarm optimization (PSO)
[32,33] suggested dealing with multi-OF.
1.1 Architectures of hybrid RES
The standard HRES model is represented by Figure 1.
These energy systems are referred to as ‘hybrid’ because
they include the required electrical load and two or
more renewable energy sources (RESs) to feed the AC
or DC load or both at the same time. Energy can come
from non-renewable, renewable, or energy storage
sources [34]. In this methodology, the lack of some
energy units is augmented by firming other units in
a controlled or natural manner. It can be displayed
that despite some alternate sources (such as WTG and
SPV), they have unexpected availability, and they pre-
sent supplementary designs [35,36]. HRES can be oper-
ated in grid-connected and standalone mode.
HRES can be used as grid-connected to meet the local
energy demand, and if excess energy is available, it can
be supplied to the grid [37]. However, in rural areas,
a standalone system can be used to generate energy
independently. Auxiliary power sources such as fuel
cells, battery units, and a backup diesel engine can be
considered for the HRES, which consists of WTG or
SPV. As a result, it is indicated to avoid random access
to these energy supplies [38]. Accessibility to energy
sources is crucial to reaching balance. There are several
indices used in the past years to evaluate the perfor-
mance of HRES. Some of them have been presented in
the section ahead [39].
2M. S. ANSARI ET AL.

1.2 World energy status
According to the Energy Information Administration,
energy utilization worldwide rises by 2.3% every year
[40]. About 20% of the total electricity in Denmark is
supplied from WTGs. In contrast, less than 1% of the
total electricity is provided from WTG, but WTs are
very fast diffusing energy sources. From 2008 to 2035, it
is expected that global energy use will increase by 53 per-
cent [40]. Figure 2 depicts the most rapid increase in
international energy use.
In Figure 2, it is seen that even though the share of RE
will increase by a few percent, conventional fuels such as
coal and natural gas are still dominated. The whole
economic development depends on the variations of
the climate and whether the increasing demands of
energy can be fed or not [41]. Fossil fuels throughout
the world are not evenly dispersed, and if the worldwide
economy is reliant on them, then local or global strug-
gles can cause an energy crisis. Nowadays, the global
environment has been harmfully affected due to
Energy storage
components
Conventional source
of energy
Control Unit
DC loads
AC loads
DC/AC
inverter
Alternative source 1
Alternative source N
Alternative source 2
Continuous line - Energy flow
Dotted line - Communication line
Figure 1. General HRES architecture.
Figure 2. Consumption of world energy, 1990–2040.
INTERNATIONAL JOURNAL OF MODELLING AND SIMULATION 3

conventional fuels, and the atmosphere of estimated
areas has been severely damaged [42]. From 2000 to
2040, SPV and WTG variations development is depicted
in Figure 3. Hydroelectric RE was virtually equal to
hydroelectric production in 2013 because of the
increased output of SPV and WTGs sources.
Hydroelectric RES production will account for more
than two-thirds of overall RES production by 2040.
The share of total RE in all power generation increased
from 13% in 2013 to 18% in 2040 [43]. The percentage
of RE production in entire power generation has
increased due to lower natural gas prices and higher
diesel prices. However, it is predicted that RE will
expand slowly to 15% of total generation in 2040.
2. Types of small power systems (SPS)
In remote areas, SPS is utilized to provide power. Small
grid growth has accelerated with decreased costs of SPV,
WTG, and Power Inverter systems. The SPS can be
classified as a network connected to the grid or
a separate power system called as off grid power system
or standalone system. Figure 4 shows the types of power
networks and Figure 5 shows the schematic diagram of
small HRES system.
2.1 O-grid power system (Stand-alone)
All SPSs planned for isolated rural areas are separate
grid systems based on the electricity demand. The stan-
dalone system is not connected to the power grid. In
rural locations, standalone systems vary significantly in
size and use.
2.2 Grid-tied power systems
Grid-tied or grid-connected systems are power systems
that are connected to large independent networks,
usually a utility grid, and supply energy directly to the
grid. An inverter is needed to convert DC electricity into
AC to supply power to a grid [16].
3. Hybrid renewable energy system
In the United States, the first distant village HRES with
a diesel generator and SPV was erected in 1978. Until
the electrical grid was installed in 1983, the power gen-
erated by this microgrid was used to supply the com-
munity refrigerators, washing machines, lights, and
pumps [44]. Nowadays, in HRES, a combination of
RES is used. With or without storage units, SPV, Micro-
Hydro, and small WTG sources are used in rural areas
Figure 3. Generation of renewable electricity by fuel type, 2000–2040.
Power systems connected to the grid Off-grid power systems (Standalone)
Hybrid energy
Single energy Hybrid energy
Single energy
Mini-grid
DG
Small power systems
Figure 4. Classification of small power systems.
4M. S. ANSARI ET AL.

to supply electrical power to the loads. The benefit of
many alternative sources with different generation char-
acteristics is the water flow in a river that fluctuates
depending on the weather. Summer solar insolation is
higher than winter, with intense daytime radiation and
no nighttime radiation [45]. At the same time, airspeed
is similar, with WT speed being high in a few regions in
the summer. Depending on local renewable energy
environments, two renewable energy sources or more
can be added to a system. Many HRES such as WTG,
SPV, and Hydro systems results in no emissions. Small
hybrid reactors are less expensive than large, compli-
cated nuclear reactors. For HRES, fuel is abundant,
accessible, and endless [46]. As a result, the power gen-
erated by small hybrid units is not dependent on local
fuel prices. The high-cost battery capacity and diesel
requirement can be decreased by combining the benefits
of SPV and WTG. In addition, for the best performance
of the SPV-WTG system, the conditions are intense
solar radiation and WTG energy. The environment,
WTG capacity, SPV capacity, location, loads, storage
device capacity, and generation site are all part of the
hybrid WTG/SPV/diesel system’s operation and cost.
According to the authors [47], the overall performance
of the WTG/SPV/hybrid microgrid can be analyzed
using the computer-modeling method in the
MATLAB/ Simulink software package. The microgrid
in [7] shows the strategy for making optimal mainte-
nance of multi-SPV-based distributed generators. In
[48], the author presented mathematical modeling to
Hybrid SPV units to consider the loss of load probability
(LOLP). If SPV contributes 75% of the required energy
in this context, an optimal solution can be obtained.
A comparison of the reliability effects of SPV and
WTG on a microgrid in a rural area of Egypt is con-
ducted [10]. In this work, WTG is shown, which helps
microgrid so that its energy does not have a deficiency of
2.92% and some obstructions to 1.57% each year
improve, but SPV power is modeled by 1.46% per year
improves the interruption period. With the usage of
HOMER, it is possible to reduce the consumption of
fossil fuels to feed the demand of the GSM base station
at Ikwerre, as shown in [49]. Context [50] tested the
reduction in fuel usage by using diesel engines and
batteries in the SPV hybrid microgrid using the
HOMER software. The use of PSO technology in [51]
creates uncertainty when assessing the economics of
operating a microgrid with WTG, SPV Generation,
Diesel Engines, and Storage Units. The impacts of
changes in the SPV array area, battery units, and HERS
WTG capacity were studied in [52]. In [40], the author
developed a decision-making tool for policymakers to
decide on a practical element in a grid-connected SPV-
WTG system plan. The parameters were calculated
Figure 5. HRE systems schematic diagram.
INTERNATIONAL JOURNAL OF MODELLING AND SIMULATION 5

using an analytical technique in this reference, which
confused the HPS planning. The research was based on
social, economic, and political factors [53].
Figure 5 shows a block diagram for HRE. The hybrid
converter connects two sources in this diagram (WTG-
SPV). If the hybrid microgrid’s power supply is insuffi-
cient, battery storage units are employed to store extra
power and feed it to the load. The inverter converts the
power supply from DC to AC to meet the load require-
ment. The variance in energy production is caused by the
immediate difference in solar radiation and wind speed,
which necessitates an appropriate design for a reliable
hybrid microgrid to supply the load under changing
weather circumstances. A detailed procedure should be
performed to reduce the cost of a microgrid [54].
3.1 Solar photovoltaic system
Solar energy directly from the sun is converted to elec-
trical power by solar panels. The largest SPV power-
houses are located in California Valley Photovoltaic
Ranch (USA) and Agua Caliente Photovoltaic Project
(Arizona, USA), which produce electrical power over
250 MWP [40]. Due to the high price of solar panels,
their use is limited to 1% of the global electricity genera-
tion. SPV can’t produce electricity 24 hr a day, and there-
fore due to its intermittent nature, battery storage is
needed. Amongst systems fixed in 2011, the average
stated cost for applications in small commercial establish-
ments upto10 kW was approximately 6.13 $ per Watt,
and for applications in commercial establishments higher
than 100 kW was about 4.87 USD/W [55]. The econom-
ical solution is the SPV system to provide energy in the
rural sector. In a decentralized generation, the SPV sys-
tem’s economic feasibility has been checked and verified
for its electiveness for villages with about 100 families. An
SPV-hybrid microgrid consists of a diesel generator as
backup is shown in [56]. Concerning the unit capacity of
the battery, the threshold of starting and then stopping
for the backup diesel generator considering the diesel
unit’s pre-operating time was evaluated using
FORTRAN in the model for hybrid SPV in [57].
A technique has been established to feed the load demand
to attain the optimal combinations of the battery unit and
SP [58]. A statistical model has been used to find the load
and insulation. In [59], a solution approach based on the
closed procedure of the disconnected (SPV-battery sto-
rage) hybrid microgrid was used to compute the losses of
power supply probability (LPSP). Based on the cost of
electricity production, the optimal combinations are
necessary for expansion from the nearby power line, tilt,
and azimuth angle [60]. Under extensively fluctuating
load conditions, performance calculation is done based
on reliable sources by using iterative optimization of the
hybrid solar photovoltaic system. For analysis of the
capacity of batteries, WTG and SPV array technique
with minimum price has been proposed in [61].
Evaluation of the powers of a battery in a grid-tied SPV
system is presented in [62].
3.2 Wind turbine system
Novel ways are now being developed to harness the
required energy using WTG. WTG was previously
used to maneuver the boat and pump water. In
1887 windmill was built in Scotland to produce elec-
tricity. The design of WTG is often customized to
specific characteristics of the place. Low wind speed
locations are ideal for oversized rotors, while high
wind speed locations are designed for small rotors
[63]. Many WTGs are designed in variable pitch or
variable speed mode to control loads. In 1887 during
the winter season, Charles was the first person who
produced electricity by using a wind-powered gen-
erator [64]. The chosen area must have significant
wind energy potential throughout the year to exploit
the hybrid WTG more effectively and economically.
WTG is now associated with large and small WTG
for various constructions. Unlike solar energy, the
operating time of WTGs is extended due to which
they generate power throughout the day and night
and on cloudy days [65,66]. The electricity produc-
tion from wind power in Europe is approximately
only about 35,000 MW. Due to low wind speed
speeds, WTGs can’t produce electrical power; there-
fore, other sources are required to feed the load. As
a result, both wind and solar systems require energy
storage devices to store extra energy and use it when
there is a lower supply of power to meet load
demand without load shedding [67].
In contrast, encouraging probabilities are that con-
sumers who can produce their energy by building small
SPVs and WTG farms can meet the daily load demand.
Based on speed data of wind turbines on an extended
period basis, the authors presented the windmill effect
as constraints on a capacity factor (CF) in [68]. CF is an
essential component of the hybrid WT system for select-
ing a specific WTG at a particular location. In
a standalone WTG, for the calculation of LPSP along
with storage units, a closed procedure solution method
was proposed in [69,70]. A Monte Carlo simulation-
based method for generating probability index, which
helped in the appropriate determination of penetration
in WTG for the current system considering economic
aspects and reliability, is proposed in [71].
6M. S. ANSARI ET AL.

3.3 Hydropower system
The forerunner of the current turbine is the water wheel,
which converts hydraulic power to mechanical power,
which is then converted to electrical energy by
a generator. In 1882, the first hydroelectric station was
placed in Wisconsin, producing 12.5 kW. Hydroelectric
power generation has gradually increased by roughly 3%
per year over the previous four decades worldwide. In
2011, in more than 160 countries, about 16% of global
electrical energy had been developed from hydropower.
Most energy production in Paraguay, Venezuela, Nepal,
Ethiopia, Norway, Bhutan, and Egypt is through hydro-
power [34].
In contrast to the quickly fluctuating and unpredict-
able nature of SPV and WTG, hydropower has an
unlimited seasonal cycle. Based on the season of
the year, water streams vary slowly. Therefore, the
requirement for energy storage units is absent. In 2010
the greatest utilized RESs was hydropower accounting
for 16% of the total electrical energy production [72].
4. Future of HRE systems
Distributed hybrid networks reduce the cost of energy
and power loss in a distribution and transmission net-
work. As a result, there is a need to identify places for
WTGs and SPVs before connecting them to the utility
grid to lower electric power rates without disrupting the
network’s current state.
Worldwide the role of RESs is essential in meeting
energy demands. The continuous fall of the RES
technology price, especially SPV and WTGs, has gradu-
ally become competitive with traditional technologies.
In a hybrid system unit, reliability during environmen-
tally changing conditions and the network’s cost are the
main concerns that need attention. Several authors
endeavored to optimize one or all these concerns.
A bubble diagram for the field of this article is shown
in Figure 6 [73].
5. HRES optimization techniques
The optimal size of the SPV array, battery banks, WTG,
power from hydroelectric generators, and alternative
systems for a standalone or grid-tied hybrid renewable
energy system to the essential load and the perfect LPSP
based on many factors are provided by the well-made
simulation of the system. The electrical loads which are
supplied have a measurable probability called LPSP. The
electrical loads will be fed when the generation of elec-
trical energy from renewable energy and the energy
provided from battery storage is more than the energy
needed to supply the electrical loads [74]. LPSP equals
zero in an ideal power system where the complete loads
are fulfilled by the supply and one in a power system
where electrical loads are not fed. A portion of these
criteria is named system capacities, minimum system
price, LOLPs, LPSPs, the quantity of battery storage
units, and maximum generation of electrical power gen-
eration. The numerous optimization methods like gra-
phical construction [51,75–79], probabilistic
methodology, iterative method, artificial intelligence,
linear programming (LP), dynamic programming
Figure 6. Diagram showing the different steps used in the literature review.
INTERNATIONAL JOURNAL OF MODELLING AND SIMULATION 7

(DP), and multi-objective were considered for improve-
ment of the hybrid WTG/SPV model by the many
researchers. Table 1 gives the various techniques that
utilize various methods of optimization.
5.1 Graphical construction method
A challenge of two plan variables is graphically solved in
a graphical construction method that shows how it
changes from one to the other. On the same chart, the
functions of constraints are plotted. The optimal point is
found by visual inspection and sketching the OF shape of
a possible area. In [81], optimum siting was achieved by
superposition. The authors have utilized long series of
radiation of solar energy, so optimum siting was per-
formed by the superposition of low solar radiation climate
cycles per day [116]. An optimal size technique is proposed
for the hybrid SPV/WTG system. The performance of the
Hybrid SPV/WTG microgrid was made hourly dependent
by stabilizing WTG. By attracting the curve’s tangent, the
goal of an annual LOLP with various capacities of the array
of SPV and battery storage units was determined, and the
optimal configuration in terms of cost and LPSP was
obtained.
5.2 Probabilistic approach technique
In this current technique, the dependence of randomness
is based on the collected data. That’s why the position of
the variable is unknown for personal values, and it is
somewhat chosen to be employed as one of the statistical
tools. Per-hour calculation has been done for the optimal
sizing of the SPV/WTG hybrid system. Every month
during which minimum solar radiation exists for solar
PV and lower electricity is available from the wind,
a Hybrid SPV /WTG evaluation can be carried out. In
this technique, two benefits are lower system cost and
minimal collection of electrical load data.
5.3 Deterministic approach method
In this technique, the evaluation of parameters in
a model is done individually for each set of the variable
and plants by considering the value of earlier states to
assess these variables. As a result, unlike the probabil-
istic technique, there is always a single optimal solution
for known parameters. The authors in [88] estimated
solar PV installation system sizes and costs in Nepal.
5.4 Iterative approach method
An iterative process is a mathematical technique imple-
mented by the computer that calculates the approximate
sequence of filtering with the optimal result of the problem
being obtained until expiry criteria are accomplished. By
using this method, the estimated time exponentially
increases variables for optimality are increased in number.
This method has been used for an optimal SPV-WTG-
battery HRES dependent on LCC minimization [93].
5.5 Models of AI approaches
AI is a branch of computer science that focuses on
creating software and machines. Fuzzy Logic (FL),
Table 1. Types of optimization techniques.
Methods of
optimization Energy Sources Ref. Comments
A Graphical
Construction
Battery storage and SPV [80–84] Two parameters are used in this method.
B Probabilistic
approach
Performance of hybrid-system [85–87] Data collecting is based on a statistical technique.
C Deterministic
Approach
Stand-alone SPV with battery
storage
[88–90] Equations are used to determine specific values based on constant
parameters.
D Alternative Approach
Hybrid SPV with WTG
Based on LPSP, a plausible solar-wind combination was discovered.
1 Hill Climbing [35, 83, 91–93]
2 Dynamic Programming [94, 95]
3 Linear Programming [96, 97]
4 Multi-objective [85, 96]
E Artificial Intelligence Hybrid SPV-WTG with battery
storage
Based on the evolution Technique
1 GA [98–102]
2 PSO [103, 104]
3 FL [105, 106]
4 ANN [107–110]
5 Hybrid of AI [109–112]
F Homer Software All RE element [61, 73, 75, 113–115] An input file containing all relevant data is provided. The software
handles other tasks.
8M. S. ANSARI ET AL.

ANN [117,118,119,120], GA [102], and hybrid
approaches that combine two or more branches make
up AI. The proper application of AI tools leads to
systems with a superior AI act or other structures that
may not be suited for out-of-date methodologies.
5.6 HOMER software
HOMER aids in the development of both off-grid and
grid-connected systems. HOMER can perform analyses
to solve a range of research questions/problems:
●What should be the component size?
●Which are the most operative systems costs?
●What effect would price, or load variations have on
the scheme’s economics?
●Is the RES acceptable?
National RE Laboratory (NREL), USA, has designed
HOMER software used to create and analyze
a hybrid system. The inputs to HOMER software
are electrical load, solar insulation, wind speed,
prices, hybrid microgrid technological aspects, con-
trols, limitations, and type of dispatch scheme. The
energy balance computations are done by HOMER
every hour per year. The HOMER software analyses
the thermal and electrical loads to the energy gener-
ated that a network can supply every hour. If any
system has batteries as a storage, HOMER decides
for every hour how the control of units should be
done and whether the storage battery can be dis-
charged or charged. HOMER calculates the total
cost by considering the original, operation and main-
tenance, replacement, interest, and fuel costs if the
hybrid system delivers the loads for the entire year.
Each component’s energy flows hourly, and the
annual cost can be calculated. In [115-121],
a detailed techno-economic analysis was done by
Hrayshat with HOMER to design an optimal hybrid
diesel-SPV battery system model for the rural houses
in Jordan. Table 2 gives explicit references for all
types of optimization approaches.
6. The HRES design criteria
HRES is sized by combining all sizes of renewable and
conventional energy sources and a storage battery to
fulfill predicted load demands with a higher level of
safety. Researchers have formulated design criteria for
optimal HRES that rely on the reliability, economics,
and type of electric loads. The customarily used plan of
optimum HRES criteria is shown in detail in Table 2.
7. Conclusions
Nowadays, due to the lower cost of WG and SPV,
HRES is gradually being used for the electrification
of rural areas. It is supposed to support providing
power for more than one billion people who are
deprived of electrical energy in developing countries.
Power reliability can be increased by using HRES
instead of only one generation source, either solar
PV or wind turbine generator. In this literature
review, the main contribution of the HRES microgrid
has been systematically carried out in the context of
the present global energy scenario. A compact math-
ematical modeling and comprehensive review of
numerous RES and battery storage unit and optimi-
zation methods are described. The details of the
optimization approaches and dependency of the
HRE microgrid on several important criteria are
presented. The review carried out in this study
emphasizes improving HRE microgrid with and
without utility grid using various tools by the
researchers.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Table 2. HRES optimal sizing methods.
Optimization Based on Objective function Ref.
Economy Capital Cost [121, 122]
Annualized Cost [83]
Reliability LPSP [113, 123]
EENS [86]
LOLP [124]
Techno-Economic Analysis
System Cost
[49, 125]
Yearly-Monthly-Hourly [91]
Average Method
Most Unfavorable Month Method [126, 127]
Electrical Load:
1. Constant Load [128]
2. Variable Load [87]
INTERNATIONAL JOURNAL OF MODELLING AND SIMULATION 9

Notes on contributors
Mohammad Shariz Ansari has received his Ph.D. from
Electrical Engineering department, Jamia Millia Islamia
(JMI), New Delhi, India in 2020. He has obtained his B.E.
and M. Tech from Electrical Engineering department, Aligarh
Muslim University, Aligarh, India in 2005 and 2007, respec-
tively. He joined the Electrical and Electronics Engineering
department, KIET Group of Institutions, Delhi-NCR,
Ghaziabad, India on 31st July 2010 and worked as an
Assistant Professor for 11 years. Currently he is working as
an Associate Professor in the same institution since 2021. He
has published several research papers in reputed journals and
conferences. His research interests include renewable energy
systems, distributed generation, and smart grid.
Mohd Faisal Jalil has more than 10 years of teaching and
research experience. He is a Senior Member of IEEE.
Currently, he is working as an Assistant Professor in the
Electrical Engineering department, Aligarh Muslim
University, Aligarh, India. He has also served as Assistant
Professor at KIET Group of Institutions, Delhi-NCR,
Ghaziabad, India, during 2013–2021. He received his Ph.D.
from the Electrical Engineering department, Jamia Millia
Islamia (JMI), New Delhi, India. He obtained his B. Tech
and M. Tech from the Electrical Engineering department,
Aligarh Muslim University, Aligarh, India, in 2010 and
2012, respectively. He has published several research papers
in reputed journals and conferences. His research interests
include electrical machines, renewable energy systems, and
PV systems under partial shading conditions.
R. C. Bansal has more than 25 years of teaching, research,
academic leadership, and industrial experience. Currently, he
is a Professor in EE Department, University of Sharjah (UAE)
and extraordinary professor at University of Pretoria. In pre-
vious postings, he was Professor and Group head (Power) in
EEC Department, University of Pretoria (South Africa) and
worked with the University of Queensland (Australia);
University of the South Pacific (Fiji); BITS Pilani (India);
and Civil Construction Wing, All India Radio. Prof. Bansal
has published over 400 journal articles, conference papers,
books, books chapters. He has Google citations of 15,000
and h-index 58. He has supervised 25 Ph.D. and 5 Post
Docs. He is an Editor/AE of IEEE Systems Journal, IET-
RPG, Tech. Eco. Smart Grids, and Sust. Energy. He is a
Fellow, and CP Eng. IET-UK, Fellow SAIEE (South Africa)
and Fellow Institution of Engineers (India). His research
interests include renewable energy, power systems, and
smart grid.
ORCID
R.C. Bansal http://orcid.org/0000-0002-1725-2648
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