Design and Optimization of a Backup Renewable Energy Station for Photovoltaic Hybrid System in the New Jeddah Industrial City

Abstract

This study aims to design and optimize a backup renewable energy station and possibility of the grid-connected hybrid photovoltaic (PV) power system for firms in 2nd Jeddah industrial city workshops. Wind and solar energy potentials were examined, and data from a variety of sources were obtained as part of the study process. It is important to utilize the application hybrid optimization model for electric renewables (HOMER) to evaluate relevant data as well as the suggested hybrid power system’s economic feasibility. The system’s payback is solely based on monthly grid bill savings and increased profits due to the absence of a power shortage. The most cost-effective system design is measured in terms of the original cost, ongoing cost, cost per unit, and total system net present value. As a result, fulfilling the load demand with 220 kW wind turbines and 500 kW solar PV is both cost-effective and efficient. The simulation results for the second scenario with a wind turbine show that a combination of a 500 kW PV, 300 kWh battery capacity, 22 kW wind turbine, and 315 kW converter is the most feasible solution for this case study, with SAR 4,433,658 net present cost (NPC) and SAR 0.1741 LCOE.

1. Introduction

The development of various forms of energy consumption is currently being driven by electricity use worldwide. Fossil fuels have met most of this electricity demand. However, it was discovered that producing power using conventional fossil fuels pollutes the environment. Furthermore, geopolitical issues have a high impact on the global economy, leading to a rise in fossil fuel prices.

Saudi Arabia’s government set a plan to develop the nation named “2030 Vision”. A part of the plans is using renewable energy to provide alternative resources for the power to run the factories and the establishments to decrease the dependency on crude oil natural gas. Moreover, the most famous project in this field is the Neom project, located in Tabuk Province of northwestern Saudi Arabia. Saudi Arabia has revealed that 50% of its energy will be from renewables by 2030. Renewable energy, often called clean energy, originates from constantly replenished natural sources or processes even if time and weather are the prime motivations for sunlight or wind. Many researchers have studied the potential of renewable energy in Saudi Arabia’s different areas.

For instance, Baseer et al. [1] used observed hourly mean wind speed data at various heights to explain the wind characteristics and resource appraisal in Jubail industrial city. They found that the wind was very variable. Shaahid and colleagues [2] studied the economic feasibility of establishing a 15 MW wind farm near Taif, Saudi Arabia, by evaluating long-term wind speed data. HOMER software was used to conduct the techno-economic analysis. Eltamaly et al. [3] proposed a computer algorithm for matching sites with wind turbines to maximize the system’s size. As input data, they used data from various sites, including Yanbu. Eltamaly proposed a technique for selecting the optimal site for a wind energy system from several feasible locations and wind turbines appropriate for various locations based on the lowest cost per kWh generated by a wind energy system. [4]. Salah et al. [5] studied and examined the characteristics of wind energy in a number of prospective Saudi Arabian locations. They estimated electricity generation and identified possible wind energy project locations. During the last decade, Allhibi et al. [6] studied wind data from Saudi Arabia. They suggested suitable locations as well as wind turbine specifications for wind data obtained in Qassim, Saudi Arabia. Rehman and Khan [7] proposed a two-level decision turbine selection approach based on fuzzy arithmetic mean operator logic and a multi-criteria decision-making (MCDM) methodology. They proved that the proposed method may be used to select the most efficient turbines from a collection of machines of varied capacities in selected locations of the Kingdom of Saudi Arabia.

Al-Ghamdi [8] analyzed wind data in annual, seasonal, and diurnal variations at Al-Aqiq, a region in KSA. The analyzed wind data employed to estimate wind energy production indicate that Al-Aqiq is suitable for wind farm development. Gaydaa et al. [9] presented a statistical analysis for seven years of recorded wind data for four sites (Dhahran, Jeddah, Al-Hofuf, and Rafah) in KSA using the Weibull distribution function. The results showed that at 10 m height, the four falls under poor class, as the highest reached amounts of mean annual wind speed and mean annual power density were 4.35 m/s and 68 W/m², individually, registered in Dhahran city.

Krishnamoorthy et al. [10] studied optimal sizing, selection, and techno-economic analysis of battery storage for a PV/BG-based hybrid rural electrification system. The result showed that the hybrid rural electrification system with LI battery is the most feasible choice of the electrification system to the village considering that its economic factor includes the total net present cost, and the cost of energy was found to be lowest.

Sharma et al. [11] performed an economic evaluation of a hybrid renewable energy system (HRES) using HOMER software. Their study shows HOMER software provides optimal solution for a commercial biogas plant for catering cooking gas demand. It has been showed that the computed cost of energy and total net present cost are USD 0.032/KWh and USD 76,837 individually by parametric assessment of proposed HRES system. Vendoti et al. [12] conducted a techno-economic analysis of off-grid solar/wind/biogas/biomass/fuel cell/battery system for electrification in a cluster of villages using HOMER software. Their study decreased total system net present cost and least cost of energy (COE) by multi-objective HOMER software. Sanjay et al. [13] performed a techno-commercial analysis of hybrid systems for the agriculture farm by HOMER software. Design, sizing, and optimizing based on the area and demand are very critical factors in HRES and were carried out in their study.

Nguyen et al. [14] studied discrete ordinates thermal radiation. Sheikholeslami et al. [15] reviewed novel progress on flat-plate solar collectors and photovoltaic systems. Their review study shows that hybrid nanofluid is useful to increase the exergy efficiency of solar water heaters. In addition, the hybrid PV/T solar system produces higher overall efficiency. Alphan [16] modelled the potential visibility of wind turbines. Target offsets that represent turbine heights ranged from 20 to 140 m. Potential wind turbine visibility was conceptualized in a “combined visibility” map, and the areas of lower potential visibility scores were proposed for wind power siting.

Solar energy may be transformed to electricity using photovoltaics. The semiconductor-based electrical devices known as PV cells may directly generate an electric current from sunshine. Renewable energy sources such as wind power rely on the aerodynamics of moving air to power their generators. This is one of the most rapidly expanding renewable energy sources in the world today. A hybrid energy system utilizes components from different power generation systems to produce electricity. This study uses solar panels and wind turbines to generate electricity in a hybrid renewable energy system. Adding an energy storage system stabilizes the output of the hybrid energy system because the power output of diverse renewable energy sources is finally governed by climatic parameters such as wind speed, solar irradiance, temperature, and so on. Power autonomy necessitates a delicate balance between the demand for and supply of electricity. Greater reliability benefits from renewable energy sources such as hybrid solar wind turbine systems because they use more than one power-generating source. Saudi Arabia has substantial wind energy potential, with average wind speeds of 7.5–8 m/s on the east coast and 7–7.5 m/s on the western coast near the Red Sea [6,17]. The Red Sea shoreline in the Kingdom of Saudi Arabia stretches for around 2000 km. According to previous research, the northwestern coastal lines may be appropriate for establishing commercially viable offshore wind farms. Offshore wind turbines are more effective than onshore turbines since the wind is more consistent offshore.

More than 50 plants are currently operating in the 2nd industrial city in Jeddah. The vast majority of these plants do not have a backup power supply in case of a power cut-off. Since the power cuts result in considerable setbacks in these plants, and if this situation continues, some factories might shut down. Since these factories work all week, 24 h a day, power cuts mean that the whole process will stop and re-begin again, which results in both material losses and time losses.

This study aims to design and optimize a backup renewable energy station for the 2nd Jeddah industrial city workshops. According to the Global Wind Atlas, Jeddah has enormous open land and an excellent average wind speed (up to 4.3 m/s), making it well-suited to use wind energy as an alternative energy source. Alternative and clean wind energy could gradually become an alternative to the electricity supplied by the national grid, which now relies on fossil fuels for its production. The backup power plant will mainly use wind energy. If the energy produced from the wind turbines is insufficient, it will be supplemented by the energy produced from solar energy. Furthermore, the design and evaluation of technical and financial requirements will be performed using HOMER software.

The primary importance of the research is to provide an urgent solution for the workshops to overcome the power shortage. Power shortage in the industrial city causes great financial losses, which affect the financial affairs of these workshops.

In the second section, the methodology, we will discuss the reason for choosing HOMER software and the simulation conditions. In the third section, results will be discussed concerning the optimization data obtained from HOMER. In the fourth section, the conclusion will add the final discussion of this paper.

2. Methodology

The chosen research area/site is the second Jeddah industrial city, located south of Jeddah near the Red Sea on the west side of the Coast Road. The city is located at latitude: N 21°5′ and longitude: E 39°24′, at 21 m above mean sea level. Jeddah 2nd industrial city contains 50 operational industries that are powered by grid electricity; however, as a result of energy shortage in the 2nd industrial city, it is estimated that almost every day, the industries have one hour of energy shortage between (18:00–6:00), which affects the production plans for industries that aim to work 24 h.

By evaluating the consumption of electricity at each industry (Considering that there are 50 various industries in the area, and each industry has varied electricity consumption), the collection was accomplished through field surveys. (Factories surveys include but not limited to the following: the factory name; factory location; and contact info; Is there a power outage in the factory? What is the time of the power outage? Is there a main power generator? Does the factory work 24/7? Does power outage affect production? Does the factory need a clean power generator? What is the consumption rate per day for the factory? Are there any capacity increases or new investments?) Figure 1 shows the daily load for Abdullah Hashim Industrial Gases & Equipment Co., Ltd. As represented in this figure, 80% of energy consumption is accrued during working hours (8:00–16:00) and 20% during the rest of the day.

2.1. Hybrid System

Solar and wind energies produce electricity in a solar–wind hybrid power plant. Since solar irradiation and wind speed fluctuate during the year, neither a solar nor a wind-powered system can offer consistent electricity. As a result, combining solar and wind energy can provide a year-round source of electricity. This hybrid system, supported by storage elements, may provide consistent and reliable electricity. Before the energy is stored in the battery banks, wind-PV charge controllers manage the charging of the energy. A converter transforms a storage system’s DC energy into AC at the appropriate power system. Installation space, installation investment, and maintenance of the hybrid systems will be discussed.

2.2. Data and Analysis of Solar and Wind Potential

Solar and wind data from Jeddah’s second industrial city region were collected. Average wind speed data were collected online from HOMER software downloaded from the NASA Prediction of Worldwide Energy Resource (POWER) database measured at 50 m height over a 30-year period. These data were assimilated into HOMER. Figure 2 presents the monthly wind speed for the Jeddah region over the 30-year period. This figure was obtained from the HOMER database.

As shown in Figure 2, the maximum estimated average monthly wind speed is 5.94 m/s in the Jeddah region. Monthly solar radiation (from HOMER) downloaded from POWER database over a 22-years period is depicted in Figure 3. The estimated solar radiation has a value ranging between 4.15 and 7.17 kWh/m²/day, with an annual averaged daily global solar radiation of 5.94 kWh/m²/day on a horizontal surface.

2.2.1. Solar PV Modules

A generic flat-plate PV system, the SunPower x21-335-BLK solar module (cell type: monocrystalline; dimensions: 2108 × 1048 × 35 mm; weight: 24.5 kg; glass thickness: 3.2 mm; maximum power (PMAX): 335 Wp; voltage at maximum power (VMPP): 57.3 V; current at maximum power (IMPP): 5.85 A), was selected for the design and has a lifetime of 25 years with a 21% efficiency. The price per unit from the HOMER grid components library has a rated capacity of 0.335 kW. The capital PV cost is SAR 1500/0.335 kWp; the replacement cost is SAR 1500/module. Although some maintenance charges are necessary to clean the dust that accumulates on the PV module’s surface, the PV system has no significant operational costs. The operation and maintenance (O&M) cost is predicted to be USD 16 (≈60 SAR) per kW per year [18]. The solar panels are mounted at a tilt angle of 22.7 degrees [19]. HOMER simulations are used to determine the total capacity of the solar panels.

2.2.2. Wind Turbines

Using HOMER analysis for daily load profile, the total system’s AC peak demands are around 219 kW. Horizontal generic wind turbines with rated capacities of 10 kW (maximum power: 20 kW; no. of blades: 3; blade length: 4.5 m; swept area: 75.4 m²; nominal rotor speed: 120 rpm; turbine design class: IEC 61400-2 Class I) were chosen to complement the solar PV system’s functioning. The capital cost is SAR 18760, the replacement cost is SAR 18760, the O&M cost is SAR1876/module/year operating addition, and its lifetime is also 20 years. The hub height of a generic wind turbine model is 24 m above sea level. Other charges, such as transportation, applicable duties, and installation, were added to those rates, totaling 30% of the initial cost.

2.2.3. Battery System

The battery storage system for this study comprises a 100 kWh Li-Ion battery manufactured by Generic, which costs SAR 3000 per unit, including cost and insurance. HOMER simulations determined the number of batteries necessary to match the storage need.

2.2.4. Converter

The HOMER program for the intended system considered several sizes of converters. The installation, operation, and maintenance expenses for both batteries and converters were calculated in the same way for solar modules.

2.3. HOMER Cost Calculation Technique

2.3.1. Present Net Cost

The NPC is the sum of the system’s installation and running costs during its lifespan, as estimated by the calculations below:

$$NPC=\frac{TAC}{CRF \left(i,L\right)}$$

(1)

where TAC is the total annualized cost in terms of SAR, CRF stands for capital recovery factor, i stands for interest rate in percent, and L stands for project duration in years.

2.3.2. Total Annualized Cost

The total annualized cost (TAC) includes all equipment utilized in the power system, containing fuel, replacement, maintenance, operation, and capital costs, all of which are computed annually [20].

2.3.3. Capital Recovery Factor

The capital recovery factor, i.e., CRF, is a ratio that analyzes a sequence of cash flows annually in relation to the present value [20].

$$CRF=\frac{i{\left(1+i\right)}^n}{{\left(1+i\right)}^{n-i}}$$

(2)

where n represents the project lifetime.

2.3.4. Annual Real Interest Rate

The annual real interest rate can be determined as follows [20]:

$$i=\frac{i^{\prime }-f}{1+f}$$

(3)

where i indicate the real interest rate, i′ indicates the nominal interest rate, and f denotes the annual inflation rate.

2.3.5. Cost of Energy

The COE is the average cost per kWh of a system that generates practical electrical energy. The COE calculation formula is as follows [20]:

$$COE=\frac{TAC}{L_{pr. AC}+L_{pr. DC}}$$

(4)

Here, L_{pr. AC} and L_pr.DC represent the prime AC load and the prime DC load, respectively.

2.3.6. Internal Rate of Return

The discount rate at which the base case and current system have the same net present cost is known as the internal rate of return (IRR). The IRR is calculated by HOMER by calculating the discount rate that equalizes the present value of difference middle from two cash flow sequences.

3. Results and Discussion

3.1. Hybrid Energy System Configuration

Figure 4 shows the intended system’s overall component arrangement and its HOMER model among the several works concerning solar (renewable) energy and performance [21,22,23,24,25,26,27]. The monthly load profile as shown in HOMER is presented in Figure 5. Furthermore, cooling system should be modified since it is inevitable that there will be a serious decrease in efficiency due to the high ambient temperature.

3.2. Simulation Results

To establish the optimal renewable energy configuration, numerous component configurations were simulated. As stated in

Table 1. HOMER simulation categorized results.

Architecture					Cost
PV Module (kW)	Wind Turbine	Battery System	Simple	Converter (kW)	NPC (SAR)	COE (SAR)	Operating Cost (SAR/y)	Initial Capital (SAR)
500	1	5	1	294	4.32	0.175	213.024	1.57
500	1	4	1	327	4.32	0.175	212.430	1.58
500	2	5	1	303	4.33	0.175	211.545	1.59
500	2	5	1	309	4.33	0.175	211.434	1.59
500	1	6	1	320	4.33	0.175	212.492	1.58
500	1	6	1	323	4.33	0.175	212.474	1.58
500	1	7	1	311	4.33	0.175	212.594	1.58
500	2	4	1	310	4.33	0.175	211.623	1.59
500	1	4	1	296	4.33	0.175	213.505	1.57
500	1	5	1	339	4.33	0.175	212.371	1.58
500	1	8	1	254	4.33	0.175	213.941	1.56
500	3	6	1	294	4.33	0.175	210.450	1.61

, the various scaling choices of the various components for making a simulation were displayed in search space. As a result, HOMER generated a total of 2000 different systems to consider. In Appendix (5), the overall results are summarized entirely.

Figure 6 shows that the HOMER analyzer evaluated the winning (optimal) system configuration for the initial instance of 5.21 m/s average wind speed and mean solar radiation levels of 5.94 kWh/m²/d with a 22.7o slope containing no wind turbine. This is due to the poor wind energy resources in comparison to the high solar energy potential.

As represented in Table 1, HOMER showed a list of configurations categorized by the NPC, i.e., lifespan cost, that could be used to evaluate alternative system design possibilities. The NPC of every component in the system and COE are calculated using HOMER. However, besides NPC and COE, choosing the best configuration depends on using all system components (grid, PV, wind turbine, and batteries). Based on the previous considerations, we selected two configurations for this study; these configurations will be discussed in detail in the following two subsections.

3.3. The First Configuration

Figure 6 shows that the best solution is a grid-connected 500 kW PV system with a 303 kW converter and five strings of 100 kWh batteries. The total annual power generation from this configuration is 2,017,268 kWh/y. The energy requirement is satisfied by a combination of grid purchases and solar energy, as shown in

Table 2. Monthly electric production and consumption for the first configuration.

Production	kWh/y	%
PV	937,282	46.5
Grid Purchases	1,079,986	53.5
Total	2,017,268	100
Consumption
AC Primary Load	1,916,250	100
Grid Sales	0	0
Total	1,916,250	100

, with a proportion of 53.5% and 46.5%, respectively. Figure 7 shows the monthly electric power generation obtained from the plant and from the proposed system (solar PV modulus).

The cheapest NPC and COE were found in this arrangement. Therefore, the NPC of this configuration is calculated to be SAR 4,318,917, whereas the COE is SAR 0.1743. The proposed system’s cost summary is shown in Figure 8, and the detailed cost is presented in

Table 3. The cost summary for first planned system.

Component	Capital (SAR)	Replacement (SAR)	O&M (SAR)	Salvage (SAR)	Total (SAR)
Generic 100 kWh Li-Ion	15,000.00	6364.11	0.00	−1197.79	2,016,632.00
Generic 100 kWh Li-Ion Bonus Depreciation	−137,025.00	0.00	0.00	0.00	−137,025.00
Generic 100 kWh Li-Ion ITC	−3900.00	0.00	0.00	0.00	−3900.00
Generic 100 kWh Li-Ion MACRS	0.00	0.00	−117,179.00	0.00	−117,179.00
Simple Tariff	0.00	0.00	2,517,333.81	0.00	2,517,333.81
SunPower X21-335-BLK	2,240,000.00	0.00	387,825.50	0.00	2,627,825.50
SunPower X21-335-BLK Bonus Depreciation	204,624.00	0.00	0.00	0.00	204,624.00
SunPower X21-335-BLK ITC	582,400.00	0.00	0.00	0.00	582,400.00
SunPower X21-335-BLK MACRS	0.00	0.00	−174,987.65	0.00	−174,987.65
System Converter	90,778.13	38,514.78	0.00	−7248.87	122,044.04
System	1,553,483.88	44,878.89	2,729,000.87	−8446.66	4,318,916.98

.

As previously stated, this layout does not include a wind turbine; hence, all renewable energy is generated solely by PV arrays. Moreover, the supplied power has three main components: grid purchase, PV arrays, and storage batteries.

3.3.1. PV Arrays: SunPower X21-335-BLK

The details of annual PV generation are shown in

Table 4. Annual PV generation details in the first configuration.

Quantity	Value
Rated Capacity (kW)	500
Minimum Output (kW)	0
Maximum Output (kW)	497
Mean Output (kW)	107
Mean Output (kWh/d)	2568
PV Penetration (%)	48.9
Capacity Factor (%)	21.4
Levelized Cost (SAR/kWh)	0.217
Hours of Operation (h/year)	4406
Total Production (kWh/year)	937,282

and Figure 9.

3.3.2. Storage: Generic 100 kWh Li-Ion

The Generic storage system’s nominal capacity is 500 kWh. The characteristics of storage batteries are listed in

Table 5. Batteries characteristic.

Quantity	Value	Units
Batteries	5	qty.
String Size	1	batteries
Nominal Capacity	500	kWh
Usable Nominal Capacity	400	kWh
Annual Throughput	62,342	hWh/year
Expected Life	15	year
Capital Cost	15,000	SAR

. Figure 10 shows the annual usage of batteries with respect to today’s hours.

3.4. The Second Configuration

The monthly power production for the 500 kW PV module with 351 kW converter, 220 kW wind turbine, and three strings of 100 kWh Li-Ion batteries is shown in

Table 6. Monthly electric production and consumption for the second configuration.

Production	kWh/yr.	%
PV	937,282	45
Wind Turbine	401,924	19.3
Grid Purchases	742,481	35.7
Total	2,081,688	100
Consumption
AC Primary Load	1,916,250	100
Grid Sales	0	0
Total	1,916,250	100

and Figure 11. It provides the best system confidence in terms of utilizing all system components and economic considerations. Furthermore, the previous table and figure show that the suggested hybrid model’s total annual production is 2,081,688 kWh/yr. The load consumes 1,916,250 kWh/yr, and the remaining produced energy (165,438 kWh/yr) is sold to the grid. The hybrid system generated 1.339 GWh of total annual power, with solar accounting for 0.937 GWh (45%) and wind contributing for 0.402 GWh, according to the same figure (19%).

The suggested model has an NPC of SAR 4,433,658 and a COE of SAR 0.1741. The proposed system’s cost summary is shown in Figure 12, and the detailed cost is presented in

Table 7. The cost summary for the second proposed system.

Component	Capital (SAR)	Replacement (SAR)	O&M (SAR)	Salvage (SAR)	Total (SAR)
Generic 10 kW	412,720.00	131,578.17	533,544.46	−74,152.74	1,003,689.90
Generic 100kWh Li-Ion	9000.00	8009.21	0.00	−1025.96	15,982.25
Generic 100 kWh Li-Ion Bonus Depreciation	−945.00	0.00	0.00	0.00	−945.00
Generic 100kWh Li-Ion MACRS	0.00	0.00	−808.13	0.00	−808.13
Simple Tariff	0.00	0.00	1,608,195.45	0.00	1,608,195.45
SunPower X21-335-BLK	2,240,000.00	0.00	387,825.50	0.00	2,627,825.50
SunPower X21-335-BLK Bonus Depreciation	−204,724.00	0.00	0.00	0.00	−204,624.00
SunPower X21-335-BLK ITC	−582,400.00	0.00	0.00	0.00	−582,400.00
SunPower X21-335-BLK MACRS	0.00	0.00	−174,986.65	0.00	−174,986.65
System Converter	105,420.19	44,727.03	0.00	−8418.08	141,729.14
System	1,979,171.19	184,314.4	2,353,770.63	−83,597.77	4,433,658.45

.

Renewable energy is generated solely by PV arrays and wind turbines in this configuration. Furthermore, the demand-supplied power has four components: grid purchase, PV arrays, wind turbine, and storage batteries.

3.4.1. PV Arrays: SunPower X21-335-BLK

The annual PV generation details are provided in

Table 8. Annual PV generation details in the second configuration.

Quantity	Value
Rated Capacity (kW)	500
Minimum Output (kW)	0
Maximum Output (kW)	497
Mean Output (kW)	107
Mean Output (kWh/d)	2568
PV Penetration (%)	48.9
Capacity Factor (%)	21.4
Levelized Cost (SAR/kWh)	0.217
Hours of Operation (h/year)	4406
Total Production (kWh/year)	937,282

and Figure 13.

3.4.2. Wind Turbine: Generic 10 kW

Table 9. Annual wind turbine generation details.

Quantity	Value
Rated Capacity (kW)	220
Minimum Output (kW)	0
Maximum Output (kW)	220
Mean Output (kW)	45.9
Wind Penetration (%)	21
Capacity Factor (%)	20.9
Levelized Cost (SAR/kWh)	0.193
Hours of Operation (h/year)	7092
Total Production (kWh/year)	401,924

and Figure 14 give detailed the annual wind turbine generation data.

3.4.3. Storage: Generic 100 kWh Li-Ion

The Generic storage system’s nominal capacity is 300 kWh.

Table 10. The features of storage batteries.

Quantity	Value	Units
Batteries	3	qty.
String Size	1	batteries
Nominal Capacity	300	kWh
Usable Nominal Capacity	240	kWh
Annual Throughput	90,852	hWh/year
Expected Life	9.91	year
Capital Cost	9000	SAR

shows the features of storage batteries. Moreover, Figure 15 depicts the annual battery use in terms of day hours

3.5. Financial Sustainability

The financial sustainability of this study was determined by employing ordinary payback technique, which defines payback period as the time it takes to return the investment to equal initial investment. All costs relative to the purchase and installation of a wind-solar hybrid system were included in the total cost of this configuration. The return came from the money saved by lowering the annual utility bill. The proposed configurations summary is as follows:

3.5.1. The First Configuration

The proposed model contains 500 kW of PV and 500 kWh of battery capacity. This configuration would reduce the industry annual utility bill to SAR 194,727, and the investment has a payback of 11.18 years and an internal rate of return (IRR) of 6.93%. Figure 16 shows the annual savings values in terms of energy, O&M, replacements, other costs, and the proposed configuration’s total savings. Furthermore, Figure 17 represents the monthly utility bill savings by month.

3.5.2. The Second Configuration

The proposed system consists of 500 kW of PV, 300 kWh of battery capacity, and 22 kW of wind-generation capacity. This system would reduce the industry annual utility bill to SAR 124,401. The investment has a payback of 11.91 years and an IRR of 6.05%. The annual savings values in terms of energy, O&M, replacements, other costs, and the total savings for the proposed system are shown in Figure 18. In contrast, the monthly utility bill savings are represented in Figure 19.

4. Conclusions

The lack of comprehensive data on total and detailed electricity consumption for all factories in Jeddah’s second industrial city as well as factory owners’ reluctance to provide us with information necessitated this study, which investigated and designed an optimal hybrid system for Abdullah Hashim Industrial Gases & Equipment Co., Ltd., Jeddah, Saudi Arabia. The HOMER grid was used to create and simulate the system, which has a 25-year life cycle.

A PV array with a storage battery as an auxiliary connected to the grid was suggested in the first configuration. The second design includes the same components as the first but also includes a wind turbine. The simulation results for the second scenario with a wind turbine show that a combination of 500 kW PV, 300 kWh battery capacity, 22 kW wind turbine, and 315 kW converter is the most feasible solution for this case study, with SAR 4,433,658 NPC and SAR 0.1741 LCOE.

Furthermore, the cost of a grid-connected solar-battery energy system is low and has a higher yearly saving value according to the HOMER simulations. Still, solar power is only available during the day, and the grid and battery are the principal sources of electricity at night. As a result, if the grid goes down, the battery will provide temporary backup; however, if the industry load is too high, or the grid outage is too long, the battery alone will not be enough, and the entire industry will be rendered powerless.

In the case of a grid-connected wind, solar, and battery system, however, the wind turbine and battery will provide additional interim backup in the event of a grid outage. Grid-connected wind, solar, and storage systems are therefore in high demand.

Furthermore, because alternative energy is not common in Saudi Arabia because of the abundance of fossil fuels, country’s total reliance on electricity generation has been based on the use of fossil fuels until now. Therefore, the system’s payback is solely based on monthly grid bill savings and increased profits due to the absence of a power shortage.

Comparison between the cost summary for first planned system and the second proposed system showed that the maximum of “Total (SAR)” for the first system is 2,627,825.5 (SunPower X21-335-BLK), while for the second system, it is 2,627,825.50 (SunPower X21-335-BLK). Results also showed that the minimum of “Total (SAR)” for the first system is −174,987.65 (SunPower X21-335-BLK MACRS), while for the second system, it is −582,400.00 (SunPower X21-335-BLK ITC). Moreover, the maximum of “Replacement (SAR)” for the first system is 38,514.78 (system converter), while for the second system, it is 131,578.17 (Generic 10 kW).

At the 70% end-of-life of products in the installation, all of them should be re-checked and replaced it is needed. Additionally, at the 90% end-of-life of products in the installation, all of them should be replaced despite their condition. For future improvement of this study, it is recommended that:

• To improve the study, more load data from more industries in Jeddah’s second industrial city are needed as well as a feasibility study of a hybrid system as a backup system for high load demand;
• Sustainable development goals (DSGs), goal 7, i.e., affordable and clean energy, and goal 11, i.e., sustainable cities and communities, should be discussed in future study;
• It is recommended that the effects of dust on the photovoltaic system and dust cleaning procedures be studied and included. On the other hand, environmental issues should be considered for the case study;
• Consider studying and evaluating an off-grid hybrid system for the chosen industry to see whether it is feasible to supply the load without using the grid;
• Consider solar modules and compare with the current results to find the best choice for economics [21].