Different Scenarios for Reducing Carbon Emissions, Optimal Sizing, and Design of a Stand-Alone Hybrid Renewable Energy System for Irrigation Purposes

Resources) software. This new system consists of solar photovoltaics (PVs), batteries, an inverter, and a 100 kW DG. The results showed a clear di ﬀ erence between the baseline DG-only system and the hybrid system regarding energy cost and carbon emissions. The energy price for the HRES is $0.107/kWh, and carbon dioxide emissions are reduced to 27,378kg/yr from 184,917kg/yr for the DG-only system. In addition, simulations and comparisons for an alternative HRES with a 60 kW DG were conducted. Based on the simulation results, the energy price was $0.091 instead of $0.19, and carbon dioxide (CO 2 ) emissions were 15,847kg/yr instead of 115,090kg/yr. It was concluded that using hybrid renewable energy systems to power the irrigation of remote areas successfully reduced the energy cost, fuel consumption, emissions, and overall cost. The HOMER program makes an accurate comparison over extended periods between the four strategies (load following, cycle charging, combined dispatch, and predictive dispatch) and selects the optimal system based on the cost, emissions, fuel consumption, and percentage of renewable energy from the system.


Introduction
Due to climate change, the need for clean energy has become urgent, and serious work to reduce CO 2 emissions in the atmosphere is underway [1,2]. It is necessary to study carbon's impact and consider replacing fossil fuel energy sources with environmentally friendly renewable energy systems. In recent years, energy demand has increased significantly, growing by approximately 5% annually, with an accompanying decrease in traditional energy sources depending mainly on conventional fuel and crude oil [3,4].
HRES are flexible and use multiple renewable energy sources, providing flexibility in designing a system best suited to a local region. An HRES can combine different energy sources to provide a continuous, effective, and capable energy source, especially in remote areas not connected to the power grid. Currently, those remote areas depend directly on electric power supplied by DGs to pump water and irrigate land [5,6]. An essential feature of an HRES is its ability to preserve the environment by significantly reducing carbon dioxide emissions and reducing the cost of energy (COE). An advantage of these systems is that they can be customized to local conditions based on solar radiation, wind and water availability, and other conditions. The cost can also be tailored from a diverse range of power and storage capacities from a smaller size for home use to a larger size for industrial production. Recently in Jordan, reliance on renewable energy systems has increased due to increasing energy costs. The region's high rate of solar radiation was leveraged to build solar energy systems to supply electricity and pump water in farms and remote areas outside of the electrical grid [7,8]. This research conducted a comprehensive analysis and feasibility study of a hybrid renewable energy system for an off-grid remote area that produces electricity using PVs, batteries, and DGs. The carbon impact of the DGs is studied, and we also examine the hybrid system's effectiveness in reducing carbon emissions. In terms of cost savings, the farm currently uses a 100 kW diesel system, placing a cost burden on the farmer and the environment due to carbon emissions. Reliance on traditional energy sources is costly and has adverse effects on the environment. Moreover, this energy is being depleted. Therefore, it is necessary to consider switching to clean and inexpensive energy systems. Most major companies worldwide are attempting to rapidly switch to clean energy to save money and conserve energy for the environment.
This research is aimed at investigating a clean hybrid energy system as an alternative to using a traditional power source to pump water in a farm located in a remote area in Ma'an, Jordan. The farm currently depends on diesel as the primary fuel for producing electricity. The main objectives of this research were as follows: (i) Develop a sustainable renewable energy system in areas with little or no access to the electrical grid and provide a reliable energy source for daily activities (ii) Reduce harmful carbon dioxide emissions and energy costs (iii) Work on developing an irrigation system strategy, which depends on specific irrigation hours and specific water quantities (iv) Develop a system for storing water and energy to take advantage of the surplus electrical energy from the system

Literature Review
This section reviews and analyzes current knowledge and published reports about various hybrid renewable energy systems and their use in place of conventional energy. Conventional energy sources, such as DGs that emit carbon dioxide, are relatively expensive and damaging to the environment. The research reviewed in this section discusses the vital issue of irrigation of remote off-grid areas and the delivery of electricity to the pumps. These papers focused on topics such as dispensing with traditional energy sources that burden the environment, studying cost and economic feasibility, analyzing energy consumption, enumerating problems and finding possible solutions, and searching for the best storage systems (i.e., batteries vs. other technologies).
Regarding the literature related to hybrid system characteristics and costs, renewable energy use has increased recently due to price decreases for the components of these systems and higher energy bills. Reducing traditional energy source use led to energy rationing and merging conventional energy systems with renewable systems to create hybrid systems. These hybrid systems have been studied and applied chiefly in coastal areas.
Kasaeian et al. [9] discuss the effectiveness of using hybrid renewable energy systems, especially in areas with adequate wind speed and solar radiation conditions. Their study used the HOMER program for the design of the system, which produced 470 kW. The most important requirements for this system are the area's natural characteristics, especially for remote areas outside the electrical network. Environmental readings indicated good wind speed (3.174 m/s) and average solar radiation (5.96 h/day) conditions for their study.
Hybrid systems are often used in countries that suffer from a lack of fuel sources, such as African countries. Nyeche and Diemuodeke [10] employed hydropower storage with a hybrid system of solar and wind energy. The study was conducted in Nigeria, which suffers from poor basic services and a lack of economic resources, especially in remote areas. In Nigeria, 36% of rural regions get electric energy for only 3-4 hours per day, and the total rate of local energy production is about 4.6 GW. Because of the country's high population growth rate and urbanization, its energy demand will continue to increase, making it necessary to find alternative energy sources. The hybrid system in their study consisted of solar cells, wind turbines, and a hydroelectric storage system to compensate for when other sources are unavailable. The study indicated that the energy cost of the hybrid system ($0.27/kWh) is much less than the current diesel energy source ($0.65/kWh).
Solar energy systems are one of the most widely used renewable systems and can be used at the home level and in more significant projects. Their widespread use has led to increased usage in off-grid areas, as shown by Ali and Jang [11]. They investigated hybrid systems' effectiveness in remote areas, where solar energy output grew by 50 GW in 2015 to reach a total capacity of 227 GW. Solar power output continues to increase, and many hybrid combinations have been researched and proven. Studies in recent years show that the cost of a hybrid energy system is good compared to a system that uses fossil fuels and is also clean and environmentally friendly. The competency index for the inverter reached 95% for a 3.5 kWh solar system in a remote area in India. They also found a decrease in the system's efficiency in some European regions where the solar radiation is often low due to cloudy weather, so more wind energy has been utilized. Studies in Fiji and Bangladesh showed high satisfaction levels with these hybrid systems.
Regarding hybrid systems' performance and impact on carbon emissions, most countries are looking for effective ways to develop their irrigation and agricultural systems in line with technology, energy savings, and emission reduction. In the case of the East Asian countries, India, and other countries with high population density, Ghasemi-Mobtaker et al. [12] considered solar energy systems to reduce environmental impacts and overdemand on electricity by irrigation stations. Two types of irrigation systems were simulated using the TRNSYS program for a farm in Iran: surface irrigation and sprinkler irrigation. These systems consume 49.89% of the farm's electricity and 40.40% of its diesel fuel for the generators, and the surface irrigation system consumes 35.7% as much water as sprinkler irrigation. As for carbon dioxide emissions using a solar energy system, surface irrigation releases 424.54 kg/ ha, while sprinkler irrigation releases at a high rate of 1183.86 kg/ha.
Powell et al. [13] studied renewable energy use in sugarcane agriculture to reduce costs and carbon emissions. In the Queensland region of Australia, where sugarcane cultivation accounts for 90% of electricity usage, off-grid systems are needed to provide energy due to significant expansion in remote areas. In these areas, installing a solar cell system up to 40 kW is permitted, reducing carbon dioxide emissions to 1245 tCO 2 -eq (tons of CO 2 -equivalent) from 1314 tCO 2eq per installation over 25 years. The study also indicates that battery systems are considered ineffective and very expensive and should be avoided in irrigation networks, as 60% of the battery value is deducted.
According to Santra [14], who assessed a photovoltaic system for a 1 hp irrigation pump in India, a solar energy system is better for the environment than a grid-connected system. It was also found that a pump system operating on direct current (DC) is less expensive than one that uses alternating current (AC). In terms of environmental impact, the solar system supplying the pump had lower carbon emissions (0.009 kg CO 2 -eq ha-mm -1 ) than the system connected to the grid (1.124 kg CO 2 -eq ha-mm -1 ) or a diesel system (0.381 kg CO 2 -eq ha-mm -1 ). Therefore, solar is considered the best and most appropriate for the environment.
Abhilash et al. [15] studied a solar energy-tracking system for irrigation using a silicone material. The system optimizes the use of the sun's rays by tracking its movement to increase energy efficiency. They also installed a sun sensor on the solar panels and a weather sensor in the station. Batteries were used to store energy if the solar cell produces 0.6 V, and the current can be direct or alternating depending on the presence of a control or inverter device.
Hybrid renewable technology has helped solve energy problems in Mozambique, where Chilundo et al. [16] utilized solar energy for horticulture and irrigation. This paper discussed the possibility of providing agricultural areas in Mozambique with the energy needed to pump water, where 70% of the citizens do not receive electricity services, and only 5% of the agricultural areas are equipped with an irrigation system. In addition, the area's weather conditions were studied, and it was found that the site has good solar radiation resources. As a result, the government has adopted a photovoltaic water pumping system (PVWPS) program, which saves money and promotes clean energy for remote regions and farms. This study concluded that this system reduces carbon dioxide emissions significantly by eliminating the burning of diesel fuels used in generators.
Kazem et al. [17] studied Annaliese in the Sohar region of Oman, where a solar irrigation water pumping system was designed. The system to be installed reduces energy bills with an energy cost of $0.309, a 21% reduction compared to the previous system. The size of the system was 2.22 kWh and reduced CO 2 emissions from diesel combustion by 924 kg/yr of CO 2 .
Balamurugan et al. [18] presented the best operation to the hybrid system from wind and solar energy in a rural area. The study focuses on the use of a hybrid energy system consisting of the solar system, wind, biomass, and battery. The solar energy system used provides the initial demand for energy, and the wind is used when conditions or the climate overlaps; the system works together to reduce wasted energy and utilize the energy in the best way. The study site in India also shows the amount of energy used and the cost of all the components of the renewable energy system in addition to the biomass: the annual energy loss is 1% and the cost is $0.1095/kWh. The conversion process for the hybrid system using the HOMER program is considered effective, as a year-long simulation was done on three villages to see the performance of these systems, and a hybrid system consisting of more than two systems was made for the process of maximum energy utilization and ensuring that the energy is not lost. And the research results are considered satisfactory. Table 1 shows a summary of each study, the components of the hybrid system, and several variables arranged in an abbreviated manner.
The studies in Table 1 generated an idea for a case study in Jordan's off-grid system since the data and results of those earlier studies proved the success of hybrid systems in those countries. In fact, Jordan has higher solar radiation and a more moderate climate than most countries studied previously, which encouraged the research and analysis of renewable systems. The HOMER simulation software will determine the optimal hybrid renewable design. In most countries located in Asia and Africa, solar energy systems are effective because of the many daylight hours due to their geographic location. Table 1 shows that the most commonly used designs consist of a solar energy system, batteries, and a DG. This hybrid configuration significantly exploits the availability of solar energy and stores its power to maximize its use as a continuous energy supply system.  Sen and Bhattacharyya [31] India (Palari)

International Journal of Energy Research
PV-WT-DG-hydropower --A hybrid system consisting of PV, DG, and WT was installed in Palari. Based on HOMER program results, hydroelectric power was later added to this system, which indicated a decrease in energy and emissions.
Odou et al. [32] Benin, Africa PV-DG-battery 200 kWh/day -A renewable system consisting of PV, DG, and batteries saves more than 70% of energy, 97% of carbon emissions, and more than 97.3% of DG energy. In addition, the invested capital is returned after 3.45 years 5 International Journal of Energy Research Diverse renewable energy sources give the best results in remote areas because each source has specific geographic and weather requirements. For example, solar energy was used to pump water in rice farms in Australia because it enjoys high solar radiation and is efficient for irrigation. The same is true for India, where most studies conducted for remote areas are aimed at providing a permanent energy source that serves farmers for irrigation and other purposes. The studies carried out in the regions near Jordan gave good results, especially in Saudi Arabia, where the desert climate is similar to Jordan's Al-Jafr region and the rate of solar radiation is excellent. Thus, a preliminary indication of the current study results is provided by the results of neighboring countries. For example, Haffaf et al. [28] investigated a similar region and duration of the hybrid system components, showing reductions in the energy cost and carbon dioxide emitted. Thus, most of these studies showed satisfactory and promising results concerning energy conservation and the environment.

Methodology and Experimentation
This section presents what has been studied and measured in the field on the farm. The appropriate area for the study, its characteristics and the method of providing it with energy, and identifying the optimal renewable system to be used have been determined. Many studies have pursued the transition to clean energy and the reduction or elimination of conventional sources. At the end of the study, some signifi-cant improvements will be identified that utilize the total power capacity without waste.
The area to be studied is in the Ma'an city region in the southern desert of the Hashemite Kingdom of Jordan. The territory is devoid of mountain and valley terrain, with high temperatures in summer (about 42°C) and relatively cold temperatures in winter. The region does not contain any industrial activity. However, recently, cultivation of crops adapted to the desert climate has begun in the area.
The case study is a farm consisting of 100 hectares, located 47 km east of the Ma'an Governorate at the coordinates 30°14 ′ 09 ″ , 36°09 ′ 36 ″ and an elevation of 853 meters in southern Jordan, as shown in Figure 1. The area is remote, and the electrical network does not serve the farm. This farm cultivates alfalfa to produce fodder. These crops consume large quantities of water per day, and the farm contains an artesian well at a depth of approximately 250 meters that supplies the farm's water needs. The farm depends on a 100 kW EMSA diesel-powered generator costing $18,000 to cover its energy needs, including powering pumps to irrigate crops. It consumes 20 L/hr of diesel fuel, operating on average 6 hr/day. This generator releases many harmful gases, most importantly CO 2 , the primary contributor to global warming [33].

Emission Measurements and Costs for the Current
System. The diesel combustion process releases toxic and other greenhouse gases such as carbon dioxide. Burning one liter of diesel fuel produces 2.67 kg of CO 2 [21]. The farm's 100 kW DG currently uses an average of 20 L/hr of and the CO 2 emission can be calculated using the following equation [33]: where the T CO2 is the total quantity of CO 2 (kg), m f is the fuel quantity (L), HV f (MJ/L) is the heating value of the fuel, CEF f is the carbon emission factor (ton carbon/TJ), and X c is the oxidation factor (3.667 g of CO 2 includes 1 g of carbon). Through a visit to the Royal Scientific Society (RSS), the CO 2 emission factor values were obtained for most energy sources. As shown in Table 2, the CO 2 emission factor for diesel is 0.267 tCO 2 /MWh.
A Testo 320 flue gas analyzer was used in field measurements to measure carbon dioxide rates and toxic gas ratios emitted to the atmosphere, as shown in Figure 2. The device provided information on the CO 2 emissions from the DG by measuring the proportions of gases emitted due to the combustion process. The Testo 320 analyzer is characterized by its accuracy and is widely used in oil refineries and factories. It measures the emission rates and the temperatures of the toxic gases and the surrounding medium to provide the best results. Table 3 presents the results obtained.
The most important data from Table 3 is the percentage of CO 2 emission, considered the most responsible for global warming. The rate of 11.43% CO 2 is considered high compared to that of other gases in the table, such as the toxic NOx and SOx not addressed in this study. This indicates that CO 2 emissions from the DG have a substantial impact and cannot be neglected as their concentrations are high and directly impact the atmosphere. The cost of one liter of diesel in Jordan is equal to $0.7, which is approximately 0.5 JD (Jordanian Dinar). Since the farm is located in a remote area, additional costs for transporting the fuel are equivalent to approximately 0.51 JD. The amount of diesel consumption per day is equal to 120 L/day or 43,800 L/yr, so the annual cost of diesel is 22,338 JD ($31,461). In addition, the generator requires regular maintenance and lubricant and filter changes, which are relatively expensive in addition to the annual diesel bill. An additional factor is the generator noise, which disturbs the farm animals and other creatures in the area.
The diesel generator's negative influences, such as the environmental effects and high operational cost, make it desirable to consider an alternative renewable and clean energy system. Since the region is located in the Jafer desert with high solar irradiance, a system incorporating solar energy sources offers an affordable and sustainable energy source without harming the environment.

PV System
Specifications. The farm is located at the coordinates 30°14′09″, 36°09′36″ and has an elevation of 853 meters. From Global Solar Atlas (GSA) data, this area has solar irradiance that is among the highest in the world, with a direct normal irradiance of 2646 kWh/m 2 /yr, equivalent to 7.3 kWh/m 2 /day, indicating that a solar installation is expected to be effective, efficient, and highly reliable. Figure 3 shows the global solar radiation values used as input to the HOMER program. In the summer months of June and July, the solar radiation rises to 8.3 kWh/m 2 /day and decreases in the winter months. The resulting average solar radiation is about 6 kWh/m 2 /day annually. A renewable energy system must provide the equivalent of 100 kW for 6 hours/day to the farm to replace the power supplied by the current DG. The wind energy density at the height of 10 m was estimated at 187 W/m 2 , so it is better to use a solar energy system. Allowance must also be made for weather conditions, clouds, dust, and capacity reduction due to seasonal solar incidence variations.
The study was done in steps and in an orderly arrangement, as shown in Figure 4. The necessary input data were collected to define the area's characteristics, the nature of the loads, components of the hybrid system, and energy costs. The HOMER program performed the simulations, choosing the optimal design with the best combination of low economic cost and emission reductions for the specified region and providing results for parameters such as energy, capital costs, and the total project cost. The HOMER program was used as it is considered one of the bestdeveloped programs in renewable energy. The HOMER program relies on simulation on several important factors in order to give the best result and high accuracy, as the basis for the differentiation in results depends mainly on the value of the system and its longevity as well as studies of the nature of the region And with regard to harmful emissions, payback period, capital recovery, and the annual net present cost (NPC) of the system, it integrates these characteristics with the parts of the system that are entered, as it performs the simulation process to produce optimal and accurate realistic results.

Hybrid System
Components. The hybrid system under consideration consists of various components, as it includes solar energy, a diesel-electric generator, a storage battery, and a converter. A solar energy system was chosen because of the abundant solar irradiance available in the region, and the DG has been included to supply power when it is not available from renewable sources or the battery. The function of the inverter is to convert different forms of electrical energy, whether AC or DC, to the form required by the pump. The parameters used to find economic costs for the design can be calculated mathematically. For example, the following equation computes the renewable energy fraction (RF), defined as the ratio of renewable energy to the total energy served [36]: where E nonren is the electrical energy produced from nonrenewable energy (kWh/yr) and E served is the total energy supplied.
The cost of energy can be calculated using the following equation [26]: where the C an,to is the total annual cost of energy ($) and E is the total electricity consumption for the year (kWh/yr). The capacity recovery factor (CRF) is an important quantity needed to compute net present cost (NPC). The CRF can be calculated using the following relationship [32]: The annual real interest rate i (%) can be calculated by the following equation: where i′ is the nominal interest rate (%); f is the annual inflation rate (%), equal to 1.77% in Jordan according to the Department of Statistics [37]; and Tp is the project life (25 years). After evaluating the CRF, the NPC can be calculated from the following equation [38]: where the C tot is the annual cost of energy and CRF ði,TpÞ is the capital recovery factor of the investment. An inflation rate of 1.77% (from the year 2021 data) and an interest discount rate of 7.67% were used as inputs appropriate for the Hashemite Kingdom of Jordan. These inputs have been used to compute the COE and NPC [39]. The data     Table 4, based on their prices from companies in the Jordanian market.
3.3.1. Solar PV System. A solar energy system was used because it can effectively and efficiently convert solar energy into electrical energy in Jordan's Ma'an region. Three solar panel types were considered for use: JINKO Tiger LM 72HC-BDVP 455 W, Kyocera KU325-8BCA, and SunPower E20-327. These solar panels have high efficiency and capacity and high output power per plate and can withstand high temperatures, harsh weather conditions, and winds. They are installed at an angle of inclination of 27-31°. The installation costs for areas outside the grid are $350, $340, and $400 per kW, and the cost of operation and maintenance is $13/kW/yr for all types. In our case, a system with a maximum expected capacity of 120 kilowatts will be used, which is somewhat more than the energy produced by the current DG. The capacity cannot be increased further because the additional area of the system would need to be taken from the agricultural land   International Journal of Energy Research area. The power output from the PV system can be calculated using the following equation [40]: where P N−PV is the power under ideal conditions, G is the solar radiation, G ref is 1 kW/m 2 , K t = −3:7 × 10 −3 ð1/°CÞ is a constant, T amb is the ambient temperature, and T ref is the standard temperature (25°C).

Diesel
Generator. The 100 kW EMSA-110 kVA-50 Hz-1 DG is the current system that supplies the farm with energy at the cost of $180/kW. The life cycle of the generator is 22,000 operating hours, and the maintenance cost is $0.05/ hr. A minimum load ratio of 25% is assumed because the generator in the hybrid system will operate only during specific periods of renewable energy source interruption as determined by the HOMER Pro program. A 60 kW DG (EMSA [33]) will also be simulated to examine the potential savings for a hybrid system built as new.
The fuel consumption of DG qðtÞ can be calculated from [41] where PðtÞ is the energy produced (kWh), a = 0:246 and b = 0:08415 are the fuel consumption coefficients, and P rated is the rated power (kWh). The efficiency of the DG is calculated from [38] where ρ D is the fuel density (kg/L), P g is the diesel power (kW), F D is the fuel consumption (L/h), and LHV D is the lower heating value of diesel (kJ/kg).

Converter
Model. The ABB inverter system used in this case study has a $170/kW cost and $3/yr operating and

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International Journal of Energy Research where P in is the DC power input (kW), P out is the AC power output (kW), and η inver is the inverter efficiency (%).  Figure 9: Relationship between dispatch strategies and excess energy for the optimal system using 100 kW DG.  for use when needed. The equations related to energy storage in batteries can be used to find the maximum energy that can be stored [43]:

Energy Storage (Battery
where the ƞ Batt,C is the storage efficiency and where k is the storage constant (hr -1 ), Q 1 is the available energy in the battery (kWh), Δt is the time between periods (hr), Q is the first available energy (kWh), C is the battery capacity ratio, Q max is the total storage of the battery, N Batt is the number of batteries, I max is the highest current in the battery (A), and V nom is the battery voltage (V). The state of charge for a battery can be calculated using the following relationship [44]: where the SOCðtÞ is the amount of energy stored in the battery on the last day, P i BatteryðtÞ is the amount of power stored in the battery on the same day, η Battery is the battery efficiency, and Δt is the time interval for net charging.
The battery storage can be discharged according to the following formula [44]: where the DoD is the depth of discharge, SOC min is the minimum limit of charge state, and SOC max is the maximum limit of charge state. The economic parameters' return on investment (ROI), internal rate of return (IRR), and payback period can be calculated by the equations of the HOMER Pro 3.14 software for ROI: and IRR: where C is the cash flow at time t, IRR is the discount rate/ internal rate of return expressed as a decimal, and T is the time period (years). As these parameters can show the economical assessment for each case scenario and for ROI relative to the investment's cost and IRR, the higher the value of an internal rate of return, the more desirable the scenario.  Figure 12: Gas emissions from the optimal 100 kW DG hybrid system.   Figure 11: Monthly electricity production from the PV and DG systems for the optimal design with a 100 kW DG. 15 International Journal of Energy Research operation of the DG is coordinated with the battery storage system if the renewable energy source is interrupted or if it is not sufficient to meet the energy demand to guarantee energy continuity. Four types of dispatch, namely, load following (LF), cycle charging (CC), combined dispatch (CD), and predictive dispatch (PS), are used to find the most suitable performance for the hybrid system.

Load Following (LF).
This strategy operates the DG to support the system if the renewable energy sources are unable to meet the energy demand. The energy is not stored in the battery as it is considered a deferred load and has a lower priority, and the loads are left to the renewable energy sources. The generator can sell the energy to the network if that is economically feasible.

Cycle Charging (CC).
The cycle-charging strategy uses the full power of the generator to cover the required primary load. It directs the surplus electrical production towards the parts of less importance, such as charging the storage system and the power supply service according to priority.

Combined Dispatch (CD)
. This strategy uses either load following or cycle charging to ensure that generator use is highly efficient. The DG may charge the storage system batteries using cycle charging, and the DG is turned off during subsequent low load periods. Alternatively, load following may be used to avoid charging the batteries and rely on the DG at lower loads in the future.

Predictive Dispatch (PS).
Predictive dispatch is a strategy of the HOMER program based on forecasting the upcoming demand for the system and estimating the available renewable energy sources. This strategy often results in lower energy costs and is based on charging batteries and economically operating the generator.

Results and Discussion
Information about the region and the costs of power generation were input into the HOMER Pro program. The price of diesel was $0.7 per liter, and solar radiation in the region was about 2664 kWh/m 2 /yr, equivalent to A comparison is made between the results of using a hybrid system with a 100 kW DG and one using a 60 kW DG in terms of energy cost and harmful carbon emissions, the amount of energy produced, and the actual cost of the systems. Accordingly, recommendations are made for the most suitable hybrid system design for the farm.

Hybrid System Results
Using Current DG (PV, Batteries, 100 kW DG, and Converter). About 2565 simulated solutions were performed to determine the (optimal) winning scenario, which combines the lowest energy price and the lowest annual cost. Three solar PV and three battery types were used with the existing 100 kW DG to obtain the results listed in Table 5. This table compares the systems and shows the optimal system having the lowest NPC. Figure 5 also presents the various systems' results for renewable energy fraction (RF) and COE.
The hybrid system consisting of a solar PV system (Kyocera KU325-8BCA), DG (EMSA-110 kVA-50 Hz-1) system, and batteries (Discover 12VRE-3000TF) is optimal, having the lowest NPC and energy cost. These results show the COE and the renewable energy fraction (RF) in the different systems. Figure 6 shows the economic parameters between each system, comparing the maintenance costs (O&M), capital costs, and total project cost (NPC).
Dispatch strategies were applied to each hybrid system, and Table 5 lists the best one for each configuration. Figure 7 shows the relationship between the dispatch strategy, the COE, and the renewable energy fraction (RF) for the winning hybrid system (100 kW DG, Kyocera PVs, and Discover batteries). This figure shows that the predictive strategy (PS) has the lowest power price ($0.107).
The choice of dispatch strategy for the optimal system makes a clear difference in the solar PV capacity. Figure 8 shows that the PS dispatch strategy has the lowest capacity solar system (127 kW) and COE ($0.107/kWh) in addition to the lowest cost. The solar capacity value is highest for the load-following (LF) strategy, and the cycle-charging (CC) strategy has the highest COE. The CD strategy was to find the medium PV solar system capacity with 133 kW and COE of $0.108/kWh.
The dispatch control strategies also affect other factors of the optimal system, such as the annual energy surplus. The strategy with the highest energy surplus is CC, accompanied by a rise in energy cost. The CD strategy has the lowest surplus energy, as indicated in Figure 9 and Table 6. Table 7 compares the three types of batteries, their capacities, productivity, and renewable energy fraction, indicating why the Discover battery is the best for the optimal system with 100 kW DG. Note the difference between energy prices and strategies between different types of batteries. The Discover battery achieved the lowest energy price. The simulation has chosen 62 Discover 12VRE-3000TF (12 V)

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International Journal of Energy Research batteries with a 53.6 kW converter. The batteries store the surplus energy for future needs, and the average energy stored is 29,483 kWh/yr. Storage is depleted by 188 kWh/ yr, as the batteries lose their storage capacity gradually over time. The losses from the storage process are 5704 kWh/yr.
The four dispatch strategies (PS, CC, CD, and LF) were applied to the optimal system to examine their impact on the number of batteries. This comparison also includes the differences in energy costs, as shown in Figure 10.
The effect of dispatch strategies on the optimum hybrid system is summarized in Table 8, which shows the differences in energy cost, number of batteries, solar PV capacity, and other parameters. For the optimal system, it is observed that the PS strategy obtained the best results.
In summary, the optimal hybrid system design consists of a solar energy PV system (Kyocera KU325-8BCA), DG (EMSA-110 kVA-50 Hz-1), batteries (Discover 12VRE-3000TF), and a 53.6 kW converter (ABB MGS100). The renewable energy fraction (RF) for this system is 77.5%. The capacities of the solar and DG systems are 127 kW and 100 kW, respectively. The overall power output of the system is 652 kW/day, and the capacity factor is 21.3%, with an energy excess of 83,097 kWh/yr. The total solar power generated was 238,042 kW/yr, accounting for 85.3% of the total energy output. Electricity is produced from solar energy throughout the year, rising in the summer months (when solar radiation increases) and decreasing near the beginning and end of each year during the winter season.
As for the specifications and characteristics of the optimal system, the DG operates primarily in the winter months due to the weak solar radiation and fewer hours of sunlight. The months in which the need for the DG rises are January-April, November, and December. The DG operates little or none of the time during the summer months when the solar radiation is high, as shown in Figure 11. The fuel consumption of the DG increases with its power. The DG produces 41,026 kWh/yr, has a capacity factor of 4.68%, consumes 10,463 L/yr, and has an electrical efficiency of 39.8%. It requires 0.255 L/kWh of diesel fuel at an average cost of $0.22/h, and the average fuel consumption is 28.7 L/day.
Using a hybrid renewable system also significantly decreased carbon dioxide emissions, reaching 27,378 kg/yr compared to 184,917 kg/yr for the DG-only system. The proportions and quantities of other harmful gases also   Figure 16: Effect of dispatch strategies for the optimal hybrid system using a 60 kW DG. 18 International Journal of Energy Research decreased. Figure 12 shows that carbon dioxide constitutes the largest proportion of emissions relative to other harmful gases.
The total final cost of the entire system is the net present cost (NPC) of $253,111, and the levelized cost of energy (LCOE) is $0.107/kWh. Important economic parameters, such as simple payback, internal rate of return (IRR), discounted payback, and return on investment (ROI), were also calculated. Simple payback is the number of years expected to recover invested capital. It is compared to the baseline system using diesel as the only fuel source. The simple and discounted paybacks for the hybrid system were 2.03 years and 2.22 years, respectively. ROI is the annual savings in relation to the initial capital investment, which is around 45% for the hybrid system, and the IRR is 49.6%.
The main factors used to assess the viability of a system are that it has the lowest NPC and the lowest emissions and operating costs. Figure 13 presents the change in cash flow over 25 years for the baseline and optimal hybrid systems.
A breakdown of costs by system component is shown in Figure 14.
The HOMER Pro program chose the PS strategy, which involves predicting future loads and the availability of renewable energy sources. This strategy relies on a balance between operating the generator and charging the batteries economically and efficiently, as predicted by the PS algorithm. Table 9 shows the difference between the baseline system and the (proposed) optimal hybrid system in terms of fuel consumption, COE, and carbon emissions, in addition to the difference in energy prices.

Hybrid System Results
Using New DG (PV, Batteries, 60 kW DG, and Converter). Simulations of hybrid systems with a lower-capacity 60 kW DG were conducted using the same approach as the previous hybrid system. A total of 2512 simulations processes were performed to determine the optimal hybrid design. Table 10 shows that a system consisting of Kyocera PVs, Discover batteries, a 60 kW DG,

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International Journal of Energy Research and a converter has the lowest COE and system cost over the project's life. Figure 15 shows the extent to which the energy price is affected by each hybrid system. This difference in energy prices between the systems is accompanied by a difference in its renewable energy fraction. The figure also shows the appropriate dispatch strategy for each system.
The four dispatch strategies were applied to the optimal system to examine their effect on the hybrid system's performance, COE, and other important information, as seen in Figure 16. In general, different dispatch strategies affect the system's behavior since each has its method for operating the system. Some depend on charging the batteries as an auxiliary system, while others depend on operating the DG as a primary solution when the renewable energy source is depleted. The choice of dispatch strategy also affects the amounts of fuel used and gases emitted.
The load-following (LF) strategy was used with this system since it is based on using diesel fuel during an energy shortage or renewable energy source depletion. In this case, the system does not store energy in batteries as it is considered one of the least important priorities. The choice of the LF strategy for the system depends on several factors, most importantly maintaining continuity in the system's power supply. Other considerations include the system's NPC, RF, and the emissions emitted by the system. Therefore, the system works to balance these factors using the appropriate strategy.
Each dispatch strategy can be evaluated according to the data in Table 11. This table shows that the HOMER program chose the LF strategy because it has the lowest COE. However, some strategies have similar results to those using the 100 kW DG. For example, the PS strategy has lower annual fuel consumption than LF, decreasing carbon emissions. Table 11 shows differences in the number of batteries and solar system capabilities for different dispatch strategies. The table also shows the energy surplus, emissions issued, and fuel quantities per year consumed for each configuration. Figure 17 compares the dispatch strategies separately for different performance parameters that can be used in the decision-making for the optimal configuration. It is observed that there is only a small difference in the COE between the strategies. However, more significant differences are seen for other results, such as fuel consumption, which directly reflects the difference in emissions and the number of batteries. Differences in the size of the solar system are also noted, where HOMER chooses the most appropriate and optimal strategy over the project lifetime of 25 years. It is impossible to judge the systems' preference from these results only because shorter time periods must also be considered, which can be accomplished using HOMER Pro.
Comparing the strategies using the power surplus (excess electricity) plot, note that the power surplus is high for the PS strategy. In addition, the PS strategy is lowest for other quantities such as fuel consumption and CO 2  Figure 18: System components for the optimal hybrid system using a 60 kW DG. emissions. Therefore, the best dispatch strategy can only be judged from a complete knowledge of the long-run system behavior.
The change in battery type used is accompanied by a change in the dispatch control strategy. After applying the three types of batteries to the hybrid system with Kyocera PVs and a 60 kW DG, the Discover 12VRE battery type with 60 batteries and 25,845 kWh/yr energy output was found to be optimal. Comparing the Discover battery to the other types shows that it has a lower price, the highest annual throughput, and a high RF, as seen in Table 12. The optimal system configuration was determined to consist of a 60 kW 62GGPC-6128A Cummins DG, a 113 kW Kyocera KU325-8BCA solar PV system, 60 Discover 12VRE-3000TF batteries, and a 52.7 kW ABB converter, as shown in Figure 18.
Energy production by the solar PV system varies throughout the year. It is noted that solar energy production rises in the summer months due to the high radiation rate and is available only during daylight hours. Figure 19 shows this variation in the daily production rate according to the day of the year.
If the monthly solar energy production rates are compared to the battery discharge rates, it is clear that the stored energy from the batteries is consumed at night. The DG is also used, with varying capacities, primarily at night. We also note that the energy produced by the system more than covers the daily load, resulting in excess energy storage in the batteries. There is no solar energy produced from sunset until sunrise, and the system relies on energy stored in the batteries and from the DG during this time.
It is also seen that part of the battery power is used during daylight hours in some winter months to support the work of the solar energy system if it is not sufficient to meet energy needs. The batteries also provide stability and continuity in the power supplied by the system.
The hybrid system has an operating system that provides effectiveness and efficiency with the best performance by coordinating the operation of the system's components to ensure sustainability and reduce energy costs. It is possible to select a specific day of the year (3 rd July, for example) to study how the system works in detail. Figure 20 shows the relationships and behavior of the hybrid system components during a selected sample day. The solar system outputs energy starting at 04:48 am (sunrise) until 19:12 pm (sunset). During this period, the batteries recharge.
During the day, the hybrid system more than covers the electrical load. After sunset, the DG begins working to sup-ply the electrical load, and the batteries start to discharge. In the July image of Figure 19, battery discharge occurs continuously all night after 18:00 pm.
The renewable energy fraction (RF) for this system is 77.9%. The energy produced annually from the solar energy system is 211,260 kWh. Figure 21 shows the percentage of energy produced annually by the solar PV system compared to the DG.    Figure 21: Percentages of energy production via the optimal hybrid system using a 60 kW DG.  The excess energy production for this hybrid system is 55.263 kWh/yr, and the generator produces 40,420 kWh/yr. The diesel fuel consumption is about 7012 L/yr, implying an average of 19.2 L/day. Carbon dioxide emissions amounted to 18,547 kg/yr compared to 115,090 kg/yr for a DG-only baseline system (see Table 13). Table 14 shows the difference in energy costs between the conventional (baseline) and hybrid renewable systems. The COE of the hybrid configuration is $0.0918/kWh, and the NPC is $216,543, while the simple and discounted payback periods are 2.8 years and 3.14 years, respectively. The hybrid design has a 29% ROI and a 35% IRR.

Result Comparison between Optimal Hybrid Designs
Using Baseline (100 kW) and New (60 kW) DGs. This section compares results for the optimal hybrid designs using 100 kW and 60 kW DGs and discusses the most efficient configuration. The comparisons will include energy prices, carbon emissions, and the NPC, with recommendations for the best system. Comparisons of the price per kilowatt for each system with the corresponding baseline (DG-only) systems are provided in Figure 22. There are clear differences in the LCOE and NPC values, as shown in Table 15. The hybrid system that uses a 60 kW DG has the lowest energy cost ($0.0918). Also, as detailed in Figure 22, energy cost and NPC are much lower for the hybrid renewable systems than for the current systems.
The simple payback for the 100 kW hybrid system is 2.03 years compared to 2.8 years for the 60 kW hybrid system. The discounted paybacks are 2.22 and 3.14 years for the 100 and 60 kW configurations, respectively. The ROI and IRR for the 100 kW hybrid system were 45% and 49.6%, respectively, while they were 29% and 35% for the 60 kW hybrid system, respectively. The difference in the simple payback between the two hybrid systems is about 0.8 years in favor of the 100 kW system, which recovers the capital more quickly. This shorter recovery time results in a higher ROI for the 100 kW system because the ROI is the average yearly difference in cash flows over the project lifetime divided by the difference in capital cost. The clear difference in the output of harmful gases and CO 2 by the proposed systems appears in Table 15. The hybrid systems emit significantly lower quantities of harmful gases, and the 60 kW hybrid system recorded the lowest amount of emitted gases compared to all others. Figure 23 shows the comparison between emissions.  The summary of the results of the HOMER program in terms of COE, emissions, NPC, and the other outputs in Table 16 indicates that the overall best system is the 60 kW hybrid system. This system has the lowest energy cost of $0.0918, in addition to the lowest fuel consumption and CO 2 emissions.
The winning design's COE was also compared to costs from previous studies located in neighboring countries or regions. It was found that the price per kilowatt is close to local energy prices and is also the lowest due to the high solar irradiance in the Ma'an region. These results are presented in Table 17, and Figure 24 shows the comparisons graphically.

Conclusions
This study concerns a farm located in a remote area outside the electrical grid that relies on a DG to generate the electrical power needed to operate the irrigation pumps. We have shown that the transition to a hybrid renewable energy system has strong feasibility and benefit, especially in such remote and isolated areas. This study is aimed at managing energy sources, obtaining energy efficiently, sustainably, and at a lower cost, in addition to reducing harmful carbon and toxic emissions. Therefore, a study was conducted to add renewable energy sources to reduce the price of energy and emissions. Relying on the HOMER Pro program, we identified an optimal hybrid renewable system with the best results at the lowest costs. A hybrid system consisting of a 100 kW DG, 127 kW Kyocera solar PV system, 62 Discover batteries, and an ABB converter reduced the energy cost from $0.291/kWh for the baseline system (100 kW DG-only) to $0.107/kWh (hybrid with 100 kW DG) and also reduced carbon emissions from 184,917 kg/yr to 27,378 kg/yr.
A simulation was made for another hybrid system with a 60 kW DG and a 113 kW solar PV, 60 batteries, and a converter as a new system design. This new hybrid configuration was compared to the previous (100 kW DG) hybrid system. The new design had lower COE and emissions, and the energy price was $0.0918/kWh compared to $0.107/kWh for the 100 kW DG hybrid system. Annual carbon emissions were reduced to about 18,547 kg/yr (60 kW DG design) from 27,378 kg/yr (100 kW DG design), while the corresponding net present costs were $216,543 and $253,111, respectively. The new design also reduced diesel fuel consumption from 10,463 L to 7,012 L. Excess energy for the 60 DG hybrid system was 55,263 kWh/yr compared to 83,097 kWh/yr for the 100 kW DG hybrid system. Therefore, the best and most economically feasible solution for the farm is the new 60 kW hybrid system. Comparing dispatch strategies used by the system in determining the winning scenario, differences between each dispatch strategy were noted. Some of them depend on storing excess energy in batteries, while others depend on a DG to supply the system when the renewable energy source is depleted. The HOMER program makes an accurate comparison over extended periods between the four strategies (load following, cycle charging, combined dispatch, and predictive dispatch) and selects the optimal system based on cost, emissions, fuel consumption, and the percentage of renewable energy from the system.

Data Availability
The data is available under request.

Conflicts of Interest
The authors declare that they have no conflicts of interest.