A review of hybrid energy technologies tenets, controls and combinational strategies

1. Introduction

A system that comprises of more than one source is known as hybrid system. In case of renewable energy source, it consists of wind, hydel energy and geothermal or solar energy (Bansal, 2006). This system is combination of both renewable and non-renewable energy sources. A shown in Fig. 1, HES is basically a combination of both old as well as new sources of energy (Naz et al., 2021). Conventional source of energy includes hydel energy, wind energy and solar energy while renewable sources include biomass, energy from tides, geothermal energy, photovoltaic cells etc. to make system cost effective and efficient (Lu et al., 2020). The conventional sources of energy are somewhat replaced by some clean energy sources that is the Fuel cells and turbines at smaller levels (Bansal, 2006; Lazarov et al., 2005). In remote areas where generation of electricity is done by petrol or diesel-based engines is replaced by the renewable sources i.e. solar panel etc. (Ejikeme, 2016). It has been deduced from the repeated experimentation that HES installations has decreased the cost of system and hence helped in improvement of efficiency of system. The price of standalone system is reduced (Nema et al., 2009) while more consistent power is provided when more than one sources are used for generation of electricity. The most used term that includes a combination of renewable as well as non-renewable energy source is an energy system which is stand-alone (Chong et al., 2016).

Hybrid energy system can use both system like grid connected system and standalone system (Kaundinya et al., 2009). Hybrid power system can best be described by defining in a statement that it is the amalgam of energy producer as well as energy storage medium. The word hybrid depicts the meaning of energy production as well as energy storing. RE (renewable energy) can be produced by using energy sources that can be reused. They are majorly solar energy, wind energy, energy obtained from tides etc. Now these renewable energy sources are extended to energy from biomass, energy from biofuels that are used for transportation. The biggest advantage of this system is the optimized cost, and these systems are cheaper along with its environmental friendly attribute because there is no smoke and dust which are in systems using conventional sources of energy. But the biggest disadvantage that has been faced in this system is that it requires the installation on very smaller and domestic level along with storage problem on very small scale (Bhattarai et al., 2012).

Also, generation of electricity using solar energy varies from place to place depending upon its installation techniques, ratings of solar panels, atmospheric conditions i.e. generation varies from atmospheric conditions. It is different in rainy day, cloudy day and in different times of a day. This in fact means that maximum efficiency cannot be achieved by using this system. There are much areas that needs more attention that can lessen the cost and hence results in improvement of efficiency (Ejikeme, 2016). So there is a major field over which work can be done that will provide the basis for the meeting the targets and hence diminishing the fossil fuels based energy expenditures (Shankar et al., 2017). However more research is being done in order to improve the systems that have been installed already and also the infrastructure of newly installed system is improved to make it cost friendly system (Yang, 2010).

The development of hybrid system to its current state is not a result of a day but it is the results of research that is being done in number of fields. It is a result of evolution of electricity by using simple hydel energy and the advancement in systems and improvement in efficiency by using semiconductor devices and then the advancement to a level where an amalgam of different energy sources is used and generated energy can be accessed through this system with the best part in it is the little maintenance.

Micro controller plays a vital role in hybrid system where control of energy source is very important that which source is used at proper time for energy generation. Lead acid batteries are more consistent source of energy and they do have more consistent operation in AC and DC applications. The factors involved in optimization of structural, design and operation parameters are given in Fig. 2. The structural optimization is done through components of the system and connections between them. The optimization of design is done by considering the capacity, type and quantity of the system components. Hybrid system acts as controller of power flow in system and its ability to interact with other systems. Different energy sources need to harmonize in a way so that higher efficiency is achieved rather than using single source of energy. If there are multiple hybrid sources of energies, then there is more consistency and excellency in utilization of energy generated but the control of multiple hybrid sources is complex. That's the reason of major research is being done on hybrid systems nowadays (Lazarov et al., 2005). There are different types of hybrid systems as described in Table 1.

Table 1. A comparison of different combinations of HESs.

Types/Combinations	Description
PV-Fuel cell	These are integrated designs that can be used for both systems i.e. System that is either grid connected or stand-alone (Bhave, 1999)
PV Solar-Wind	These PV Solar-wind cells are used for HOMER (Hypergeometric Optimization of Motif Enrichment), PPA (Power Pinch Analysis) and for the technical and economic analysis for different systems sizes (Rozali and Yahaya, 2016)
Fuel cell-PV-Wind	These types of renewable energy sources are used in different applications in Saudi Arabia as well as in Yanbu and simulations of this system are being done using software (HOMER). There are three systems through which it should pass through in order to have complete cost analysis assessment in developing countries (Fathabadi, 2016)
PV Solar-Battery	These types of renewable energy sources are used for micro-generation by using the MIMO controller application and it basically helps in less consumption of grid energy (Allison, 2017)
PV Solar-Thermal	These types of energy sources are used for collector systems that are of air type, PVT system of liquid type along with flat plate photovoltaic thermal collector system (Chow, 2010)
Wind-Diesel	These are used for different optimization techniques and their objective functions are (ISE), (ITAE) and (ITSE) are measured (Behera et al., 2016)
Fuel cell-Wind	These types of hybrid energy systems can give its efficiency up to 99.28% and 99.41% by using (MPPT) (Fathabadi, 2016)
Wind-Thermal	Required and limited power flow by using an algorithm in MATLAB or SIMULINK by using IEEE 30 at test systems (Panda and Tripathy, 2016)
Fuel cell-Battery	They are used in ESS devices which have high power and energy. ESS is basically a Heterogeneous Energy Storage System (Hemmati and Saboori, 2016)
Solar-Diesel-Fuel cell – Hydrogen	These are the most important source of energy used for sizing of units, management of energy, cost optimization as well as modelling of renewable energy components.(Bajpai and Dash, 2012)
Diesel-Wind-Fuel cell	They can be used for every type of system connection i.e. grid connected, isolated or standalone system as well as in different controllers such as PID and PD controllers (Tah and Das, 2016)
Wind-Diesel-Hydro	They do have applications in FACTS devices and STATCOM devices used for the improvement of power factor (Mohanty et al., 2016)
Biomass-Solar	There are two combined cycles systems are integrated. First used for thermal integration with following the second system for thermochemical hybrid routines (Liu et al., 2016)

As summarized in Table 2, a HES is a more efficient system because it uses different energy sources to help the system to upgrade its performance. For example, if we have combined system i.e. MT and FC for both power and heat operations increase the combined efficiency and slow dynamic response can be improved by storage devices in combined hybrid systems. Hybrid systems can meet power and energy demands for different requirements because they use hybrid source of energy (Bhave, 1999). Hybrid systems are basically introduced in the market for cost reduction and using environmental friendly resources of energy. Hybrid system basically provide flexibility in operation for different markets (Ibrahim and Khair, 2015). HES are environment friendly because it provides no emission such as in non-renewable sources. The detailed description of some of the renewable resources is listed below:

•
Photovoltaic effect: The concept of photovoltaic effect was introduced in 1839 and it basically consists of multiple layers of silicon. The working phenomenon of this system is when light is incident upon silicon, it excites the electrons of silicon and they start to move which results in generation of electricity. This is a good system because it requires little maintenance because of its non-loveable contacts of PV cells. It also produces electricity without emission of harmful and hazardous gases that cause damage to environment (Panda and Tripathy, 2014).
•
Wind energy: The variation in wind energy is basically because of the pressure and intensity variation in solar energy. Depending upon the pressure of air generation takes place and wind turbines have installed on commercial scale for long time. Small wind turbines play an important role in standalone systems and hence meeting the required energy requirements. The novelty could be done in wind turbines by research and ESS (Nagaraj et al., 2016).
•
PVT System: A photovoltaic system consists of PV cells and thermal systems. This system is used for electricity and heat generation. The main purpose of PV cells in this amalgam is as a thermal absorber. They both are alternates for PVT integration. There are different classes of this system depending upon the type of operation being required. For example, flat plate or concentrator's types, thin-film solar cell, polished or unpolished panels and stand alone or integrated features etc. Different mechanisms can be performed depending upon different type. Design and modelling are done depending upon thermal to electrical yield. All the factors and mechanisms that are being performed in this system is used to improve performance of stem (Chow, 2010).
•
Biomass: they are the hybrid sources that are by product of forests and agricultural products. They acquire the functions of soil conditions, rainfall and temperature features. Some more biomass fuels are bagasse, animal dunk leading fuels in hybrid biomass energy resource. Crop residues are used as a fuel for energy production (Hall, 1979).
•
Grid: The grid systems are used when renewable energy sources are not used. Grid connected systems can be used as backup power source. When energy from renewable source is not generated, energy from grid can be utilized (Carrasco et al., 2006).
•
The battery bank: Battery banks are the source of energy generation and it consists of more than one battery. The modelling can be done by using a software HOMER that is used to study and completely analyze the charging and discharging status of batteries. The system is initially designed for one battery and complete study of this battery being done (Momoh, 2009).
•
Generators: This is also used as a backup power source in which duet is burnt to generate electricity. But heat is exhaust harness are its byproduct. Different kinds of cycles are used in generators and they could be Stirling engine, by using fuel cells, and engine consisting of both diesel and petroleum fuel. HOMER is also used to model the complete behavior of a generator, which engine needs to be selected, which fuel is being used in order to make it most efficient. The basic features that are of concern are lifetime of generator, their maximum and minimum capacity, curve of fuels and which fuel type should use to generate electricity (Momoh, 2009).

Table 2. Summary of economic value of HESs tested in different parts of world.

Technology		Plant size range (MW)	Variability: Characteristic time scales for power system operation (Time scale)	Dispatchibility (See legend)	Geogrephical diversity potential (See legend)	Predictibility (See legend)	Capacity factor range (%)	Capacity credit range (%)	Active power, frequency control (See legend)	Voltage, reactive power control (See legend)
Bioenergy		0.1–100	Sesons (depending on availability of biomass)	***	*	**	50–90	Similar to thermal and CHP	**	**
Solar energy	PV	0.004–100	Minutes to years	*	**	*	12–27	<25-75	*	*
Solar energy	CSP/thermal storage	50–250	Hours to years	**	*	**	35–42	90	**	**
Geothermal		2–100	years	***	N/A	**	60–90	Similar to thermal	**	**
Wind energy		5–300	Minutes to years	*	**	*	20-40 onshore 30-45 offshore		*	**
Hydropower	Run of river	0.1–1500	Hours to years	**	*	**	20–95	0–90	**	**
Hydropower	Reservoir	1–20000	Days to years	***	*	**	30–60	Similar to thermal	**	**
Ocean energy	Tidal range	0.1–300	Hours to days	*	*	**	22.5–28.5	<10	**	**
	Tidal current	1–200	Hours to days	*	*	**	19–60	10–20	*	**
	Wave	1–200	Minutes to years	*	**	*	33–31	16	*	*

Dispatchability.

* low partial dispatchability, ** partial dispatchability, *** dispatchable.

Geographical diversity potential.

* moderate potential, ** high diversity potential.

Predictability.

* moderate prediction accuracy (typical <10% RMS error of rated power day ahead, ** high prediction accuracy.

Active power and frequency control.

* good possibilities, ** full control possibilities.

1.1. Hybrid energy systems designing and cost comparison

It is not easy to design hybrid energy systems rather it is a tough task depends upon several factors which affect the performance of this system. Some of the major feature that is considered while designing is cost and whether it is accessible or not (El Khashab and Al Ghamedi, 2015). Fig. 3 provides a cost comparison of different renewable energy sources in cents/KWh (Naz et al., 2021).

Designing of hybrid system is complex because it needs grouping of different hybrid sources along with its sizing, type of energy sources and storage system for energy along with its capacity to deliver to the system. The sources availability in a given area is of importance whether the source is cheaper (Abuelrub et al., 2020). Installation cost and running cost both are the parameters that are considered while installing a hybrid system. There are some factors which are considered while designing a system and they are greenhouse gas emissions, their social affects, environment friendly behavior and the reliability of the system. One another reason of using hybrid system usage is because of its efficiency. Cost analysis and sizing of system play a vital role in deciding whether the system is reliable and efficient.

To design a HES, there are several parameters that need to be noticed before installation. Some of them are capacity of system, type of renewable energy source, type of system connection, what should be the storing device for charge, should be single unit or multiple units. After deciding all these parameters some of the restriction that has been faced is optimization of cost, reliability and efficiency of system. So practical installation of a system is very complex rather than only designing a system on software.

A comprehensive study is being done in designing of hybrid system and several algorithms have been proposed to develop a reliable and efficient system. The algorithms are genetic algorithm and linear programming etc. Different software's have been used to make modelling accurate. HOMER(Allison, 2017), RETScreen (Slotine and Li, 1991), Hybrid (Cheng et al., 1988) and HOGA (Arif et al., 2013).

Hybrid systems designing is studied and different software are used for modelling. These softwares help in proper sizing and generation technique of generating stations 39-42 and thus helps in reduction of money wastage. Designing of hybrid systems using software has become interesting. Some focuses only on the designing and sizing of systems while there are some other algorithms that help us in control algorithms as well. These help us in reduction of fuel cost and hence optimize the cost of system. But there is a compromise between reliability and cost of system (Ge et al., 1996).

2. Methodologies

Because of the advancement in the field of renewable energy, many researches have been made in this field with the accurate results and efficiency. The best way is to make the system cost effective so different methods and procedure have been compared depending upon the external conditions such as weather and available resources.

2.1. Microgeneration technology

This technology deals with the energy efficiency requirement of building in future and deals with usage of renewable resources to obtain the secured and sustainable future. These technologies are the source of energy generation in the building and by looking into scale of electrical grid; it develops its own centralized power station. Micro generation is normally called as the energy storage system and defined as sourced of distributed resources in various regions.

This generation has the advantage of storing renewable resources and whenever demand of building is increased then it acts as a supplier to supply this energy to the building. Different other electrical power generation sources are also connected with the electrical energy storage system to get assistance from this system because there is distinctive difference between the supply and power generation demand.

As there was single input and single output system is used initially but with the advancement of latest technology and new researches has been made to give the control of multiple input and multiple outputs (MIMO). The main purpose of using these micro energy generation systems is to compensate the issues of energy storage within a building if the connection of local electrical network fails. This technology will now serve as the distributor of energy within the building to meet the electricity demand.

There are two main reasons which are the cause of imprecision in the system. These are:

•
Uncertainty of the system

As the building structure and heat capacity of different buildings are different, so it is hard to find out system parameters accurately. So huge disturbance occurs and influence the system efficiency.

2.1.1. Simplified dynamics

The model which is presented in the system sturdily is the simply the explanation of various physical systems such as the structure of building's model and it excludes considering model of components which are at high frequency and it does not consider the internal components of the plant. It considers the transfer of heat as linear quantity.

These two fields are main cause of uncertainty and it mainly considered as structured uncertainty which is related to the system parameters and also other unstructured parameters which deals with the order dynamics of the system. For the reduction of these problems, robust controllers are used which consists of two parts one is known as inner model reduction component also the external component. The inner model reduces the feedback linearization or inverse control laws while the outer model deals with all the uncertainties.

2.2. Modelling of hybrid PVT

There are two major sources of energy in hybrid system, heat as well as electricity. In hybrid system there is inconsistency in performance of electrical as well as thermal. Based upon the research and different studies, it is concluded that these two factors contribute to the performance of this system:

1.
Solar collector's covering factor
2.
Collector unit's cooling flow rate

The goal of this system is to make the system extra efficient by supplying the pint of hot water to the system and also increase the supply of electricity if we consider the average house with bathroom kitchen and bedroom and also look at the condition that the emission of CO2 is minimum.

To achieve the goal, different modelling techniques were considered that how different system parameters are considered and how to utilize them for better efficiency. To define the system completely some standard parameters should be considered from the literature and use them as such to get the best possible results. The ENERGIES SOL unit consists of different components which includes.

1.
Transparent glass
2.
Ethylene vinyl acetate encapsulating film
3.
Monocrystalline PVC module
4.
Heat is converted from radiating by absorber exchanger who is further sent to the collector fluid
5.
At bottom there is an insulating material layer

Insulation is also present on the front side, back side and it bears the heat losses also considering the structural strength. The absorber exchanger consists of tubes and sheets for the exchange of heat where the water flows through the parallel pipes from top side to the bottom side while exchanging heat with the fluid so that the warm fluid is collected from the fluid. The transparent cover is just like the glass sheet of minimum thickness of almost 3.2 mm to cover the whole system.

2.3. Power Pinch analysis for load shifting (PoPA)

Load shift is basically the shifting demand of electricity from maximum period when demand is more to that load peak periods when demand is minimum. Different management techniques have been made including demand side management, control strategies and electric system cascade approach to shift the loads to low peak values. To determine the distribution of power in each time interval, it is verified using different graphical concepts known as Outsource and curve of electricity storage. These OSEC curves shows the valuable help that how load is shifted to off peak load by looking at the time interval and energy generation at each interval.

One of the methods to shift the load is to do descriptive case study, while considering three loads at a time such that biomass, solar and wind system. If it is assisting that the system consists of only five appliances and load can adjusted at any interval of time. This is not as easier as it is seen. In real system, load shifting method is considered only for the flexible and non-flexible loads. The energy sources can have short-term, mid-term and long-term effects on flexibility of HES (Fig. 4). In order to shift the loads two things, which need to be considered are expense of electricity and savings. The given results below show the sources of power and demands to show OSEC system to shift the load to new time interval as shown in Table 3.

Table 3. OSEC system to shift the load to new time interval.

Sr. #	Type of power	Explanation	Start	End	Empty Cell
Sr. #	Type of power	Explanation	Time	Rating of power (kW)	Empty Cell
S1	Source	Energy from sun	8 a.m.	6pm	500
S2	Source	Energy from wind	0	12pm	400
S3	Source	Energy from biomass	12pm	12am	600
D1	Demand	Device 1	6am	12pm	300
D2	Demand	Device 2	8am	6pm	350
D3	Demand	Device 3	8am	12pm	500
D4	Demand	Device 4	0	12pm	350
D5	Demand	Device 5	12pm	12am	500

2.4. Wind energy and photovoltaic cells hybrid systems

In this system, analysis of grid connected system including lead acid batteries, photovoltaic cells and small wind turbines are done. To measure the accurate results, data for household applications including wind, electricity and PV expenditures were performed already. Different results and data have been collected already because when you are performing experiments, there is need of every single detail. So, in photovoltaic and PV hybrid system, condition of photovoltaic and wind power is established.

If PVs and wind energy are combined and the effect of wind energy at various heights is considered, different curves are obtained without the energy storage. After considering the new steps, new peaks are obtained for power to heat curves. In this way, excessive heat of both systems will transform into heat. In this system, losses of electricity are very small and maximum peak is possible.

Wind and photovoltaic system if individually used will result in the increase of expenditure. But hybrid system results in the optimization of cost. Results shows that the independence of this system can be increased up to 90% with the positive value of gain. Different researches have been made to make the system most efficient with minimum electricity cost and minimum investment to provide maximum consumption of energy. Different calculations and simulations have been made which includes the capacity of battery, plant size and also includes the energy management system.

To make the hybrid system more efficient and self-consumption, there is need of reducing energy management system. It consists of short and medium hybrid energy system. Energy management system is preferable to increase the utilization of system. Batteries used nowadays are for the adjustment of minute to time scale. Fig. 5 shows complete schematic of grid system connected to PV and wind turbine system with a battery system (Moghaddam et al., 2019). Different types of batteries are used for different purpose, Li-ion battery is used as storage for small duration and lead acid batteries are used for fast load transient. With the ageing, lead acid batteries are reduced. Nowadays instead of batteries, to control the maximum value of photovoltaic system, hot water heating system is preferable.

2.5. Grey Wolf Optimization

The flowchart of Grey Wolf Optimization is shown in Fig. 6. By using this method control of reactive power in diesel and wind hybrid system can be done. Two generators are present in this hybrid system. Induction generators produce power from the wind and synchronous generator generates from diesel. All the data related to reactive power is already present. Static VAR compensation is used to produce reactive power in an isolated system (Wang and Li, 2019).

SVC also used for load variation to supply reactive power. Grey wolf organization is used to reduce the proportional integral gain. Integral time error is checked and then compared with the previous work.

The advantages of using synchronous generator are that it does not need separate dc source. It does not require any maintenance. Provide protection against overload itself and less cost. But to maintain the value of flux, reactive power is needed continuously. To meet that demand capacitor banks are required.

As most of the loads are reactive so its demand results in the large variation in voltage. Different strategies have been made to keep the voltage variation within the specific limit so Grey code optimizer has been used for that purpose.

There are three different types of errors which can be minimized by Grey wolf organization.

1.
Integral time square error
2.
Integral time absolute error
3.
Integral square error

Different values of PID constants are compared with other error minimizing criteria. These errors are minimized efficiently with GWO, as shown in Table 4.

Table 4. Variations of parameters in GWO.

Objective Function	Search Agents	Max. Iterations	KP	KI
ITAE	30	40	2738.0048	4250.3266	1.5500 × 10−6
	30	50	1118.1940	4274.2174	1.5468 × 10−6
ISE	30	40	18857.5660	14.2543	5.001962 × 10−5
	30	50	18137.9764	194.8630	5.001870 × 10−5
ITSE	30	40	1668.1496	4185.2400	9.607745 × 10−8
	30	50	1771.2759	4183.1733	9.607721 × 10−8
ITSE & PSO	30	50	4261.2345	4993.8140	9.613193 × 10−8

It is concluded that the greater iterations, more improvement in convergence. PSO is also reduced. ITSE criteria is also preferred because of low undershoot with the designed value of controller. To get the better performance and stability in the future, parameters should be upgrade according to the performance and stability of hybrid wind energy.

2.5.1. Maximum power point tracker (MPPT)

In hybrid system, all the MPPTs are attached with the controllers so that each controller will be specified for specific substation. If separate code and algorithm and also the MPPT controller are used, then it will decrease the accuracy of the hybrid system and it complicates the whole system. It also results in increase in cost. So main objective is to find an accurate and fast MPPT for hybrid fuel cell or photovoltaic generation system. This s called the universal tracker because it tracks wind energy, photo voltaic system and other cells simultaneously.

A comparison of universal MPPT and other MPPT techniques is provided in Table 5. There is no need of sensors in MPPT such as tachometer and anemometer, only current and voltage from PV module is utilized and from different subsystem in a power system. Only the utilization of current and voltages of FC stack, WEC system of power system is being done in universal MPP tracker. This treacle's not only measures the output of wind turbine but also tracks the WEC subsystem to get the maximum value of output. Application is found in power system because it tracks in MPPT. It is concluded that the point of operation of wind turbine to its maximum power point is tracked by the MPPT techniques.

Table 5. Comparison of universal MPPT and other MPPT techniques.

Power point tracking techniques	Sensors	Response time (ms)	MPPT efficiency	Data Type
OC voltage	1 Voltmeter	82	86	Simulated results
Temperature measurement	1 Voltmeter 1 Thermometer	80	83	Simulated results
SC current	2 A m	300	89	Simulated results
Fuzzy logic	1 Voltmeter 1 A m	60	96	Simulated results
Adaptive fuzzy	1 Voltmeter 1 A m	120	Not reported	Simulated results
Artificial neutral network	1 Voltmeter 1 A m	820	Not reported	Simulated results
Fixed Perturb and observe	1 Voltmeter 1 A m	76	88	Simulated results
Variable Perturb and observe	1 Voltmeter 1 A m	15	96	Simulated results
Three point weight	1 Voltmeter 1 A m	47	96	Simulated results
PSO-ANFIS	1 Voltmeter 1 A m	10000-17000	97–98	Simulated results
P&O-ANFIS	1 Voltmeter 1 A m	12000-19000	85–97	Simulated results
Incremental conductance	1 Voltmeter 1 A m	81	95	Simulated results
Modified IC	1 Voltmeter 1 A m	≥200	Not reported	Simulated results
Extremum seeking control	1 Voltmeter 1 A m	33	97	Simulated results
Ripple based	1 Voltmeter	520	99.6–99.8	Simulated results
PM-MPPT with scanning	1 Voltmeter 1 A m	Not reported	99.2	Simulated results
MPPT with scanning	1 Voltmeter 1 A m	2000	Not reported	Experimental results
MPPT with irradiance sensor	1 Voltmeter 1 A m Some sensors	Not reported	98.62	Simulated results
Hybrid MPPT method	1 Voltmeter 1 A m	≥3000	Not reported	Experimental results
MPPT-Cuckoo	1 Voltmeter	100–250	Not reported	Simulated result
Genetic algorithm	1 Voltmeter 1 A m	≥600	96–99	Simulated and experimental
MPPT method	1 Voltmeter 1 A m	245	95.8	Simulated results
Universal MPP tracker	1 Voltmeter 1 A m	12	≥99.6	Experimental results

2.6. HOMER software for system implementation

This software has its most effectiveness in 20th century. It helps to determine and optimize designing of HES. The necessity is to make the system cost optimal. To optimize the cost, electrical grid should be used instead of storage system (Suresh et al., 2020). For renewable energy plant expenditure's calculations different system are selected. These systems are used for best sizing to minimize the cost of the system to smaller unit and it is stimulated by HOMER software. Different type of systems such PV, PV-wind, PV wind fuel cell should be evaluated to reduce the expenditures. If PV only system is considered, then it is used to provide power during daytime while grid will provide power at night. So the whole system is stimulated on HOMER software including running and expenditures. Another system is wind and grid connected hybrid system. Apart from providing 17% energy from gird, wind and PV energy share 37 and 49% of overall energy, respectively. This PV wind system consists of wind, PV system, fuel cells, hydrogen tanks and electrolyser. Electrolyser produces hydrogen gas and it is stored in hydrogen tank. Hydrogen is supplier of fuel cell to produce electricity. All the simulations are given in the HOMER simulations. It is concluded that the standalone PV system has least cost of energy because of high irradiation of sunlight. Inverter plays major role in affecting the cost of system. Instead of using inverter to reduce the cost, DC supply should be used in remote areas to meet the demand.

2.7. Hybrid algorithms

To ensure environmental optimal power flow (EOPF) and new algorithm has been proposed which is hybrid algorithm. This system is designed for nonlinear controlled system. Cost analysis including thermal and wind energy is done other than considering the output obtained from wind. This algorithm ensures the cost of its installation, its running cost, real power output, losses of FACTS devices to maintain a stable and reliable hybrid energy system. To verify the efficiency of HES particle swarm optimization algorithm (PSOA) evaluation is done. PSOA algorithmic is performed in order to obtain the most optimal solution over several iterations. PSOA is very much related to environmental concerns and can be motivated by different activities. This algorithm includes position and velocity of particle, and also the change in velocity as a result of change in position.

2.8. Hybrid system fuzzy controller

In this control system, system power is controlled by using logic. This fuzzy logic controller has a feature of stability and reliability along with optimized cost and low power dissipation. The fuzzy logic controller depends on nonlinear control method and is known as fuzzy set theory. Fuzzy logic controller manages the power in the system, and they employ constant knowledge. The steps involved in this controller are fuzzification, fuzzy interference and defuzzification.

2.9. Multilevel inverter

Multilevel inverters are the most advanced inverters. These are used where high power is required. The quantity of power will improve if number of levels is increased. The voltage obtained as output by multilevel inverter is harmonic free. This is the biggest advantage of multilevel inverter. The harmonics that are produced in output voltage increases the current so the flow of current in the neural path increases. The connection configuration is such that the firstly source connected to DC-DC converter. After that this inverter is used to provide AC signal with minimum harmonics. There are different configurations in which they can be arranged such that voltage source converter and H-bridge converter.

2.10. Neural network

Renewable energy system utilizing the solar energy used. Artificial neutral networks to improve efficiency. These networks help in prediction of solar energy at different time zones. These networks can be used for forecasting the irradiance of sun and it can also be used for different sizing applications. Fig. 7 shows a hybrid power system with neural network controller (Zarrad et al., 2019). In MPPT and photovoltaic power systems, these networks ANN can be used. For wind energy conversions ANN are used by controlling the angle of pitch in case of wind turbines. The purpose of using it in wind turbine is to obtain the maximum efficiency. Also, wind directions and speeds can also be determined by using ANN. Briefing about its architecture, it comprises of four layers which are input, outer, context and hidden layers.