Comparative Analysis of SAM and RETScreen Tools for the Case Study of 600 kW Solar PV System Installation in Riyadh, Saudi Arabia

Abstract

In this study, we discussed the main recent studies on PV systems worldwide and specifically in the Gulf Cooperation Council (GCC) region. We focused on different PV cells and their characteristics in terms of efficiency, importance, and negative impacts, and examined the classification of PV systems and their comparison. In addition, the adoption of PV technologies in GCC countries is considered, focusing on the future aspects. In addition, technical and economic evaluations were carried out for a 600-kW commercial PV solar project at one of the selected sites in the Riyadh region, and the PV energy generation performance was assessed. The monthly energy production, module orientation and tracking system, peak voltage, net power consumption, rated output power, cash flow and capacity factor were calculated. In addition, the direct, normal and diffuse solar radiation are calculated to determine the cost-effective and efficient PV system. Two simulation programs, namely system advisor model (SAM) and RETScreen, are used in this study. In addition, a comparison between annual energy production, cash flow, and electricity loads was performed to evaluate the accuracy of the simulation results. The study suggests that a low-cost PV system could be developed in the Riyadh region.

1. Introduction

In an effort to move away from fossil fuels and create a more sustainable and environmentally friendly energy system, photovoltaics (PV) has a key role to play [1]. PV is a clean and sustainable energy source that can contribute to the fight against climate change by generating electricity without emitting greenhouse gases or other harmful pollutants. Distributed power generation and distribution is enabled by solar PV systems on individual homes and buildings, which helps reduce electricity losses during transmission and distribution and provides people and communities with more control over their energy sources [2,3,4]. Reducing dependence on imported fossil fuels is an important step toward energy independence, and solar photovoltaics can be especially helpful for countries that do not have their own fossil fuels. The inclusion of solar photovoltaics (PV) in the global energy mix has the potential to contribute to a more sustainable and equitable energy system as PV technology continues to advance and become more cost-effective.

The demand for solar power generation is growing worldwide as many countries pursue pollution reduction goals and strive for sustainable power generation [5]. PV technology is expected to play a critical role in the future global renewable energy grid. Commercial solar cells can be classified into two main types: crystalline silicon (c-Si) and thin film, depending on the underlying manufacturing technology. Despite the devastating impact of the COVID-19 epidemic around the world, 138.2 GW of solar energy was installed in 2020, an 18% increase over the previous year and another record for annual solar installations. This brings global solar capacity to 773.2 GW, a 22% increase, and marks a new milestone for the solar industry as it crosses the three-quarter terawatt mark. Global solar power generation could increase to 2147 GW by the end of 2025 under optimal conditions [2]. Given the current market situation, the medium scenario forecasts the most likely development. The low scenario assumes that policymakers will stop promoting solar power and that other problems such as interest rate hikes and severe financial crises will occur. The high scenario, on the other hand, forecasts the best case scenario in which political support, financial circumstances, and other factors improve.

PV power generation is expected to reduce CO₂ emissions by approximately 69–100 million tons, NOx emissions by 68,000–99,000 tons, and SO₂ emissions by 126,000–184,000 tons by 2030. In 2020, China remains the leader in the solar energy industry, adding more than twice as much capacity as the second largest market (USA) [2]. Installed capacity in Europe also increased; however, the insignificant increase of 0.3 GW or 1 percentage point volume increase to 23.7 GW represents a decrease in global share to 17%, down from 20% in 2019. Liu et al. [3] conducted a systematic evaluation of PV technologies in Europe, China, and the U.S. using the concepts of “energy return on energy invested “(EROI) and “net energy return on carbon invested” (EROC). Regional success in EROI was achieved in Europe, followed by China. Due to high energy consumption by electricity and labor, the U.S. achieved the lowest average net energy return. Due to significant differences in the carbon intensity of the production cycle, Europe also achieved the highest EROC, while China was the worst performer.

The Gulf Cooperation Council (GCC) countries, including Saudi Arabia, Oman, and the United Arab Emirates, have significant potential for solar energy generation [4]. According to the International Energy Outlook 2019, global energy consumption is expected to increase by nearly 50% between 2018 and 2050, with Asia leading the growth [6]. All GCC countries have now implemented significant solar and wind power projects. In 2020, Saudi Arabia produced 3.45 GW of renewable energy, which is approximately 4% of the country’s total energy production [7]. In non-Organization for Economic Cooperation and Development (OECD) countries (including GCC countries), gross energy consumption has increased by 84%, compared to only 14% in OECD countries. In the last two years, the development of solar PV systems in GCC countries has increased significantly. Oman, for example, has set a target of generating 11% of its electricity from renewable sources by 2023 and 30% by 2030, and the United Arab Emirates aims to generate 75% of its electricity from carbon-free sources, mainly PV, by 2050 [8]. Saudi Arabia has set a goal of generating 50% of its energy from renewable sources by 2030 [9,10]. These efforts demonstrate the commitment of the GCC countries to shift to renewable energy sources and reduce their dependence on fossil fuels.

Alnaser et al. [11] published a thorough study on the impact of increasing solar energy consumption in the GCC countries. The main impacts were the following: (1) a significant regional decrease in solar energy prices; (2) the participation of investors in the sustainable energy business; (3) the promotion of innovative house architecture aimed at using buildings for the installation of renewable energy systems; (4) the improvement of facilities and maintenance used by many solar technology companies; (5) the establishment of new academic institutions and courses in educational institutions for solar and renewable energy technologies; (6) a greater emphasis on outstanding grid intermittency through solar connections; (7) a significant reduction in per capita carbon emissions in GCC countries; (8) more efficient use of household and industrial appliances; (9) a boost to the battery sector through solar energy storage. Saudi Arabia has emerged as one of the largest markets with the largest number of PV projects among the six GCC countries and is expected to become a center for solar energy development. Jeddah, Riyadh, and Dammam are the three largest cities in Saudi Arabia and have an average irradiation of 5.78 kWh/m²/day, which is significantly higher than the global value of 1.36 kWh/m²/day [12]. The availability of raw materials in Saudi Arabia also contributes to it being considered an ideal location for the use of solar energy [13].

Recently, Ghaleb and Asif [14] conducted a study to evaluate the potential of photovoltaics for commercial buildings in Saudi Arabia, considering factors such as the availability of sunlight, the size and orientation of the building roof, and the building’s electricity consumption. The authors concluded that solar PV has significant potential for commercial buildings and could be a viable option for reducing carbon emissions and saving on energy costs. In another study, Mohammed et al. [15] investigated the performance and feasibility of a 10 kWp residential PV system in Saudi Arabia. They conducted a study to evaluate the performance of the PV system over a period of one year, considering factors such as the availability of sunlight, the electricity consumption of the building, and the impact of weather conditions. They also conducted a financial feasibility analysis to evaluate the potential economic benefits of the PV system to the building owners. The authors concluded that the PV system works well and provides significant economic benefits, including a reduction in electricity bills and an increase in building value. The authors also discussed the challenges and limitations of deploying a residential PV system, including initial installation costs, the need for sufficient roof space, and potential shading from neighboring buildings or trees.

Several studies addressed the difficulties and obstacles that must be overcome for Saudi companies to compete in the solar energy market [16,17,18,19,20,21]. Al-Jarboua [16] suggested that Saudi Arabia increase energy prices to enable real competition by taking advantage of the existing conditions for solar and wind energy in different ways. In some countries, such as the Kingdom of Saudi Arabia (KSA) and the UAE, special agencies for renewable energy and improved energy efficiency have been established to support the energy transition [22]. In the UAE, for example, renewable energy investments increased 29-fold in 2017. Recently, several PV projects have been announced, offering highly competitive costs [21]. By 2023, KSA plans to build renewable energy sources with a total capacity of 27.3 GW, the majority of which will be solar energy with a capacity of 20 GW. The rest (7.3 GW) will be wind power and concentrated solar power (CSP). The numbers for PV, wind, and CSP solar are expected to reach 40 GW, 16 GW, and 2.7 GW, respectively, by 2030 [21]. This represents approximately 32% of the KSA’s absolute peak power generation (as estimated in 2018) of 61.743 GW [23]. Saudi Arabia has planned to complete 11 GW of PV and wind power projects by 2022 [24]. KSA has also made significant investments, totaling USD 384 billion (USD) to diversify energy sources to meet the electricity demand of each industry, with the possibility of producing more than 123 GW by 2032, with a production potential of approximately 52 GW, 46 GW, 5 GW, 2 GW for PV, nuclear, CSP, and wind, respectively [25]. In 2018, the KSA and Softbank announced an ambitious 12-year program to build 200 GW of solar power to be implemented by 2032 [26]. Recently, Al-Amri et al. [27] discussed a method to improve the efficiency of solar panels in the harsh climate of Saudi Arabia. They proposed the used heat pipes and liquid cooling to achieve a uniform temperatures in the modules, which could improve their performance and extend their lifetime. They conducted experiments to test the effectiveness of this approach and found that it significantly lowered the temperature of the solar modules and increased their efficiency. The authors also discussed the potential benefits of this technique, including the ability to reduce the cost of solar energy and improve the reliability and stability of the solar module system. Overall, the use of heat pipes and liquid immersion cooling appears to be a promising approach to improve the performance and efficiency of solar modules in hot and harsh climates. Alami and his co-authors [28] recently published a comprehensive review on the potential challenges in PV technology deployment. They highlighted several challenges, including the high initial cost of PV systems, the need for sufficient roof area, and potential shading from nearby buildings or trees. Overall, they concluded that careful planning and management of PV technology deployment could help overcome these challenges and accelerate the transition to a more sustainable and renewable energy system.

From the above discussion, there is a lack of studies that specifically address the development and application of techno-economic assessment models for PV solar technologies in the region. Potential research issues in this area include identifying the key factors that influence the economic feasibility and viability of solar PV projects in the Middle East region, developing and applying appropriate approaches and methodologies for developing and applying techno-economic assessment models, evaluating the accuracy and reliability of such models in predicting actual project outcomes, and identifying effective strategies for engaging and persuading stakeholders in the region to adopt solar PV technology based on the results of techno-economic assessment models. Overall, there is a need for further research focusing on the development and application of techno-economic assessment models for solar PV technologies in the Middle East region, with particular attention devoted to Saudi Arabia as a special case, to better understand the economic feasibility and viability of solar PV projects in this region and to support the development of effective strategies to promote solar PV adoption. Some studies [29,30,31] in the Kingdom of Saudi Arabia recommend the installation of PV systems on building roofs in commercial and residential areas and the calculation of the power generation capacity of the proposed system. However, all these studies lack the current and future PV installation capacities in the GCC and KSA, as well as the technical and economic values. We chose a commercially available PV system as a cost-effective model. All aspects were studied in detail, and a case study of the installation of a 600 kW PV system in the Riyadh region was provided to support the analysis.

In a study by Kumar [32], several simulation tools, including PV Watts, PVGIS, PV-Online, PVSOL, PVsyst, and the system advisor model (SAM), were compared in terms of their ability to analyze solar PV systems. While some of these tools, such as PV Watts, PVGIS, and PV-Online, provide basic technical and economic analysis, others, such as PVSOL, PVsyst, RETScreen, and SAM, provide a more comprehensive technical analysis. According to Kumar, SAM and PVsyst are the most detailed programs for studying PV solar systems, although PVsyst is not available for free use [32]. In a separate study, González-Peña et al. [33] evaluated the performance of five commercial and freely available software tools (RETScreen, SAM, PVGIS, PVSyst, and PV * SOL) in predicting solar energy generation. They found that both SAM and RETScreen performed exceptionally well, with deviations of less than 10% from actual data. Simulation results obtained with paid tools were not significantly better than those obtained with free software.

The aim of this study is to investigate the structure, composition, classification, technologies, and current and future characteristics of PV systems in the GCC region, focusing on the city of Riyadh. While there are several studies on PV systems in general, there is not yet a comprehensive technical and economic study on the impact of PV in Riyadh. Therefore, this study focuses on analyzing the cells, area, module efficiency, current status, and structural characteristics of PV cells, as well as studying the advantages and disadvantages of different PV technologies. The study also classifies different types of PV systems, including off-grid, grid-connected, and hybrid systems, and discusses the limitations associated with each system. Considering the high intensity of solar radiation in the GCC region, solar cells are likely to be the most effective form of PV technology in the area. A comprehensive overview of PV solar technologies in the GCC region is provided, with particular attention devoted to Saudi Arabia in terms of environment, health, economics, geography, meteorology, and power load forecasts. Based on all available technical and scientific information, a comprehensive technical and economic analysis of a 600 kW PV system was conducted, leading to the optimization of the best possible PV system for the Kingdom. Based on the results of the feasibility study and the lessons learned, the study proposes a plan for the development of a working prototype in Riyadh.

2. Solar PV Technologies and Their Implementations

It is possible to make PV cells from a variety of semiconductors. Silicon is the most common semiconductor material used to make these cells [34]. A cell, module, and array are schematically shown in Figure 1. In order to increase cell efficiency and minimize cost, various semiconductors have been explored. Other semiconductors that could be used are:

• Monocrystalline silicon;

• Polycrystalline (multi-crystalline) silicon;

• Amorphous silicon;

• Cadmium-telluride (CdTe);

• Gallium-arsenide, gallium-antimony, and others;

• Copper indium gallium selenide.

Almost 90% of today’s PV technologies are based on silicon, and the main differences between the various PV technologies are in the materials (semiconductors) used to manufacture PV cells. The material properties determine the efficiency, cost, and durability of PV solar cells. Each material has its own properties. Depending on the semiconductor material and design, the efficiency of the cell can range from 6 to 18% in most cases [35]. The silicon cell sensor was found to be a viable device for long-term outdoor measurements after considering the size and performance of the PV system and its specifications. However, the study did not address additional structural characteristics of the PV system [36]. Therefore, we studied the module efficiency of all other cell types (Table 1) and the hybrid cell HIT seems to have the highest efficiency. Ibrik conducted a similar study in the Palestinian region of Nablus, where a system with 128 PV solar modules achieved an average annual energy yield of 1684 kWh. However, the study did not address the overall performance and importance of PV technology in this region [37]. As shown in Table 1 and Table 2, the efficiency of different types of solar cells can vary significantly.

Over time, the use of solar energy will increase as the cost of generating solar energy decreases and the demand for green energy increases. In addition, the government is in favor of renewable energy sources. It is expected that more combinations of semiconductors will be used in the production of PV cells to increase efficiency. Solar energy is abundant and is considered the cleanest source of renewable energy. Solar energy can be used to generate electricity for commercial, domestic and industrial use.

Classification and Comparison of the Solar PV Technologies

PV systems come in different shapes and sizes. In terms of dimensions and covered areas, they can be large or small. There are also PV plants with power ranging from a few kW to several hundred MW or more. Recently, PV systems have evolved from a mere backup power supply to a primary source of electricity generation [40]. Apart from being a positive development in the technological field, the improvement and increase in the diversity of PV systems have helped to reduce the associated costs. In this paper, we consider different types of PV systems and compare them in terms of various aspects such as production scale, functionality, installation methods, and operation, as shown in Figure 2.

In general, three main types of PV systems are distinguished: grid-connected PV systems, off-grid PV systems, and hybrid PV systems [41]. Several parameters are considered when distinguishing between the three systems, including the configuration of the PV systems. These components form a system, the extent of use, and the different applications of these systems. Table 3 explains the individual characteristics of each type.

Although hybrid systems generate cheap power, they often require other power generation devices to deliver maximum power. Typically, a battery is used as an option to power diesel generators, which may prove inefficient in certain cases [42]. Research has shown that a hybrid PV system is the most economical, as it offers the possibility of combining isolated grids and mini grids. However, maintaining power grids powered by diesel generators is costly because diesel is a relatively expensive fuel.

Grid-connected PV systems store electricity using the anti-islanding solution, which means that the system continues to operate when the grid is shut down. In contrast, off-grid PV systems use integrated batteries [40]. A solar thermal storage system, such as solar towers or parabolic troughs, is used in hybrid systems for energy storage.

Based on the abovementioned information, PV systems are considered as a critical source of power generation and complement the typical power sources. The three main PV systems have several common characteristics; therefore, they can complement each other when selecting a suitable PV system. As different customers focus on different parts of the systems, the slight differences promote diversity in their use. PV systems are very versatile in practice due to their wide range of applications.

3. Solar PV Technologies in the GCC Region

Growth in electricity generation in the GCC countries is critical to meeting the expected increase in energy consumption. In Saudi Arabia, this has increased significantly in recent years, resulting in a high peak load. As a result, the Kingdom is experiencing a rapid increase in power generation, and we should use the most efficient renewable power generation facilities to achieve the Vision 2030 targets.

At the end of 2018, there were 79 power plants in the Kingdom with a total installed capacity of 22.5 GW. In 2019, renewable energy capacity in the country increased dramatically due to the increasing attention toward environmental issues. In 2018, the total installed renewable energy capacity was 87 MW; however, in 2019, it increased to 397 MW [45]. Compared to the other GCC countries, Saudi Arabia has the largest installed generation capacity. The UAE has the second largest installed capacity of approximately 29 GW, with Abu-Dhabi accounting for almost half of this capacity at 15.5 GW. The other GCC countries have smaller capacities compared to Saudi Arabia and the UAE. Kuwait has an installed capacity of 18.3 GW, Qatar 8.6 GW, Oman 7.8 GW, and Bahrain has the smallest installed capacity with only 2.8 GW [11].

In all GCC countries, current power generation relies mainly on petroleum, which accounts for a large share of carbon dioxide emissions. Recently, however, many countries have announced an ambitious target for the introduction of renewable energy sources. The Saudi Arabian government has announced plans to build approximately 30 solar and wind power projects over the next decade as part of a USD 50 billion program to increase electricity generation while reducing oil consumption under Vision 2030 [46]. The GCC region is expected to become one of the most important locations for future renewable energy growth. The Arabian Peninsula appears to be a blank spot on the world’s solar resource map. One reason is that the GCC countries are somewhat isolated from the rest of the world. The GCC is characterized by regions with a high potential for solar radiation. KSA ranks 6th among countries with the highest potential for solar energy generation, as shown in Figure 3 [47].

The Sakaka solar project, with a solar capacity of 300 MW, is now operational. The Renewable Energy Project Development Office (REPDO) of Saudi Arabia’s Ministry of Energy, Industry and Mineral Resources (MEIM) awarded the solar capacity to this one facility. This tender also received global recognition because it contained the lowest-priced bid for solar power to date. French energy giant EDF committed to an electricity price of 0.06697 SAR/kWh. However, Saudi energy company ACWA Power won the bid with an offer of SAR 0.08872/kWh. In addition, in line with Saudi Arabia’s Vision 2030, KSA has announced an ambitious renewable energy target of 27 GW by 2024 and 58 GW by 2030. Accordingly, wind energy is expected to provide 16 GW by 2030, making it the second largest green energy source after solar energy.

Solar PV Technologies Installation in Saudi Arabia

The growing demand for electricity in Saudi Arabia necessitates the expansion of power generation capacity. Due to greenhouse gas emissions, conventional power generation is a major cause of environmental pollution and has negative impacts on human health. To protect the environment and human health, it is important to provide alternative methods of electricity generation. Saudi Arabia is an ideal location as it is located in a sun belt. Therefore, it has the potential to become one of the largest solar energy producers in the world [48]. “The cumulative installed capacity for solar PV in Saudi Arabia increased from 2.35 MW in 2010 to 455.8 MW in 2020, with a combined annual growth rate of 69.3%”, according to GlobalData analyst Ankit Mathur [49].

In Saudi Arabia, low-grade fuels and conventional power generation methods release several pollutants that cause human health problems. Conventional power generation releases CO₂, SO₂, and NO_x, which contribute the most to global warming. Green power plants, such as solar energy, can therefore make an important contribution to reducing these emissions through alternative power generation.

In December 2020, the residential price of electricity for households in the UAE was USD 0.081/kWh, and USD 0.048/kWh in Saudi Arabia. The cost of electricity generation from conventional energy sources, including indirect costs, will increase compared to that of solar energy. According to the World Energy Outlook 2020 [50], the world’s most exemplary solar energy projects today provide the “cheapest electricity in history”, with the technology being cheaper than coal and gas in most major countries.

The sun belt is located between latitudes 40-N and 40-S, with Saudi Arabia being located between latitudes 31-N and 17.5-N. Due to its geographic location, Saudi Arabia is well-suited to harness the sun’s energy. In Saudi Arabia, the average solar radiation varies from 7.004 kWh/m² in Bisha to 4.479 kWh/m² in Tabuk [51]. Most parts of the southern region of the country, including Bisha, Najran, and Soleil, have high solar radiation values (up to 7.004 kWh/m²).

Future electricity demand is an important factor in determining solar energy demand. The highest load demands occur on sunny days in Saudi Arabia [50]. This is considered the climax time. Therefore, the total energy demand from conventional sources in Saudi Arabia may decrease during the current peak period, resulting in a pronounced peak pattern. On weekdays, the demand for electrical energy increases around 7:00 AM and decreases around 6:00 PM. However, solar radiation is available from approximately 6:00 AM to 6:00 PM. Saudi Arabia has its peak loads from May to September, when the monthly cycle of solar radiation coincides with the peak of electrical load.

The study of the first year of broadband solar power measurements in King Abdullah City for atomic and renewable energy, corresponding to a new Saudi Arabian monitoring network, was presented by Zell et al. [52]. The study was conducted over twelve months (October 2013–September 2014) and used data from 30 sites in the region based on measurements from GHI, DNI, DHI, and related meteorological variables. It was found that PV technologies work well in any environment; however, extremely high temperatures can affect their efficiency (annual averages above 30 °C in some areas). Although most regions have sufficient solar energy for the deployment of solar technologies, the western inland sites, with an average total daily output of more than 6474 Wh/m² (an average total annual output of 2400 kWh/m²/year), outperform the eastern sites, which have an average total daily output of nearly 5510 Wh/m² (an average total annual output of 2000 kWh/m²/year). In another study [53], the techno-economic aspects of rooftop PV systems were investigated in Al Majmaah district in Riyadh province, Saudi Arabia. The annual PV energy yield and payback period were used to verify the profitability of a PV system; however, variations in the seasonal load profile were not considered in the feasibility analysis.

Temperature, DNI, and GHI data from 41 geographically distributed tracking and monitoring sites were made publicly available by the Solar Atlas of Saudi Arabia [54]. In the summer, GeoModel solar maps showed a DNI of 9000 Wh/m²/day in the northern parts and 6000–6500 Wh/m²/day in the central and eastern regions. In the winter, a DNI of 8000 Wh/m²/day was observed in the northern and southern zones, while DNI of 7000–7500 Wh/m²/day was reported in the central belt. The DNI in the northeastern Arar and southwestern Jeddah areas was 4500–5000 W h/m²/day. Another study [55] investigated the wind and solar power generation capacity in five locations in KSA (Dhahran, Riyadh, Jeddah, Abha, and Yanbu). LCOE in the Yanbu region was USD 0.609/kWh when hybrid renewables were used, i.e., a combination of solar, wind and wind turbines.

Awan et al. [56] presented a one-year study of a PV project with a PV capacity of 100 kW based on radiation data collected from 44 sites in Saudi Arabia. They compared the production in terms of GHI and PV energy (Figure 4) with the load profile, taking into account the main factor (temperature) that resulted in high loads in KSA even in summer. Most sites in KSA had high GHI, making them ideal for PV generation. However, some sites experienced unusually high temperatures that could reduce the effectiveness of PV technology. During the high-load summer season, most locations experienced high annual PV production and output. It was also reported that Tabuk and Riyadh provinces were the two areas with the highest PV output.

4. Computational Analysis

Two well-known calculation programs were used for the study. These programs are named as follows:

• SAM;

• RETScreen.

Depending on the plant description, working language, location and financial aspects, the simulation methods of the two programs differ slightly. In SAM, the working language was created using C, C++, Python, Java, and MATLAB, while RETScreen uses Visual Basic language. However, both simulation programs can be easily operated in MS Excel, as shown in Figure 5. Figure 6a,b shows the generalized orientation of the PV system, including its routines and subroutines.

SAM is a well-known simulation program developed by the National Renewable Energy Laboratory, USA. SAM helps design various renewable energy systems, including PV, CSP, wind, geothermal, biomass combustion, parabolic troughs, marine energy, wave, and tidal systems. PV systems for commercial and residential projects can be installed with or without energy storage. The program calculates technical and economic parameters of the proposed system, including performance and financial metrics. SAM has numerous databases for calculating system components, including PV modules, inverters, batteries, parabolic trough collectors and receivers. SAM has been used in many studies, e.g., for a 1.2 MW PV solar system [57], a 50 kW CSP system [58], and others [59].

RETScreen is a clean energy management tool developed by Energy Resources Canada for evaluating energy efficiency, cogeneration projects, renewable energy projects, and feasibility and energy performance studies. Its application has been widely used to help professionals and decision makers evaluate and optimize energy systems, including photovoltaic, thermal solar, wind, tidal, biomass, and geothermal. Several studies have been carried out with this program, including feasibility studies for solar PV systems in Egypt [60,61], feasibility and development studies for wind farms in Algeria [62], and the idea of a smart building powered by a PV system [63].

The proposed model includes the site selection (for the PV) and the simulation model consists of generic model linked to the Monte Carlo method and performance model. The initial parameters were calculated and used in the MC model based on the MATLAB language which was then exported to an Excel spreadsheet as presented in Figure 6. Both programs use a different program language for simulation and their operation is different. Since both SAM and RETScreen have high accuracy in performing renewable energy feasibility analysis, we performed the comparative studies shown in Section 6 to confirm V&V (verification and validation) analysis. It can be found that the percentage error in both analyzes is not more than 1.20, which shows the accuracy of the simulation results and confirm the feasibility analysis of the PV system.

According to KSA’s plans to install PV systems throughout the country, feasibility studies and determining the optimal region for PV system installation are critical. Therefore, a technical and economic evaluation of a 600 kW PV system was conducted as a feasibility report for the proposed system, based on the extensive research and literature study in the previous sections. The study was conducted at a selected site in one of the largest cities in the Kingdom, the central region of Riyadh. The analysis addresses the financial viability of implementing a particular PV system and the technical components that contribute to the optimization of the system. The theoretical and computational modeling and validation of the study was carried out in this area. Equations (1)–(5) were used to determine some of the parameters, and the results were used in calculation programs to calculate the technical and economic aspects of the PV system.

The main objective of this part of the study is to conduct a feasibility study for solar PV systems in KSA while conducting preliminary studies throughout the GCC region. Many researchers performed different analyses by considering the same analysis methods and using different calculation programs such as PVSyst, SAM, HOMER, RETScreen etc. However, in our case, we used the methodology of SAM and RETScreen. There are recent works published by many researchers using the same analysis methods (theoretical and computational). In one study [64], the software tool HOMER was used to investigate the optimal PV, inverter and PV/inverter sizes for the grid-connected PV system in Makkah, Saudi Arabia. A theoretical and computational approach was used to study a residential rooftop PV system in Yanbu city, Saudi Arabia [65]. A study on the potential of CSP power plants in KSA was carried out using the same computational methods and provided results that can explain the potential viability of CSP plant [66]. A very recent study was conducted for the development of PV system in residential buildings with a computational approach using computations [15].

5. Technical and Economic Assessment of a 600 kW PV Plant in Riyadh, Saudi Arabia

Current solar energy generation systems in Saudi Arabia rely on outdated and limited solar irradiance data and rely primarily on data from satellite observations of the atmosphere. Saudi Arabia has identified an initial renewable energy demand of 9.5 GW. As envisioned in Vision 2030 [50], this large-scale development of renewable technologies requires reliable and long-term measurements. To obtain accurate long-term field data, KSA has established a renewable resource monitoring and mapping network [67]. Global horizontal irradiance (GHI), diffuse horizontal irradiance (DHI), direct normal irradiance (DNI), capacity utilization factor (CUF), levelized cost of energy (LCOE), and PV energy production are some of the most important characteristics that affect PV performance

GHI, DHI, and DNI are essential solar components that are related to a solar zenith angle (SZA) through the following expression [52]:

(1)$GHI=DNI\times \cos \left(SZA\right)+DHI$

GHI refers to the total amount of solar radiation received per unit area on a horizontal surface. DHI refers to the fraction of GHI that is diffuse, or scattered, rather than direct. DNI indicates the amount of solar radiation received per unit area on a surface that is perpendicular to the sun’s rays. The SZA is the angle between the sun’s position in the sky and the local vertical and is a key factor determining the intensity and distribution of solar radiation at a given location. As SZA increases, the contribution of DNI to GHI decreases, while the contribution of DHI increases. Understanding this relationship is important for accurately predicting and modeling solar irradiance at a given location.

Annual CUF is used to calculate the percentage of usability of a proposed PV system over a one-year period [68]:

(2)$CUF=Energy measured \left(kwh\right)/(365\times 24\times plant installed capacity)$

where “Energy measured” represents the total amount of electricity generated by the PV system over a one-year period, expressed in kilowatt-hours (kWh). The installed power of the system is the total rated power of the PV system, also expressed in kW. The term “365 × 24” represents the total number of hours in a year. Knowing the annual CUF of a PV system is important for evaluating its economic feasibility and profitability, and for optimizing the design and configuration of a PV system.

The power output of a PV array is a measure of the amount of electricity that the array is able to generate and can be obtained using the following relation [56]:

(3)$P_{PV}=D_{PV}{X}_{PV}\left(\frac{S_T}{S_{T,STC}}\right)\left[1-{\alpha }_P\left(T_C-T_{C,STC}\right)\right]$

where P_PV is the output power of PV; D_PV is the derating factor of PV (%); X_PV is the output power of a PV array under standard test conditions (kW); S_T is the incident solar radiation at the current time (kW/m²); S_T,STC is a set of conditions used as radiation incident at standard conditions (kW/m²) and is used to normalize the intensity of solar radiation at other locations and times. STC is a set of conditions that is used as a reference for testing and comparing PV devices. ${\alpha }_P$ is the temperature coefficient of power (%/°C). This is a measure of the change in the power output of the PV cells as the temperature changes. T_C is the cell temperature of the PV at the current time step (°C). This is the actual temperature of the PV cells at a specific location and time, and it can affect the performance of the PV cells by changing their electrical resistance and reducing their efficiency. T_C,STC is the cell temperature of the PV under standard test conditions (°C). This is the temperature of the PV cells at STC, and it is used as a reference for comparing the temperature of the PV cells at other locations and times. When the temperature effect on PV power output is neglected, the above equation can be written as follows [56]:

(4)$P_{PV}=D_{PV}{X}_{PV}\left(\frac{S_T}{S_{T,STC}}\right)$

The above equation takes into account the intensity and availability of solar radiation as well as the efficiency of the PV cells, but not the effect of temperature on the power output of the PV system.

LCOE can be obtained using the following relation [53]:

(5)$LCOE=\frac{NPC\times CRF}{{\sum }_{t=1}^{8760}{P}_L\left(t\right)∆t}$

where LCOE represents the levelized cost of electricity; NPC is the net total present value of the actual cost of all components; CRF is the capital recovery factor; P_L is the load demand at the corresponding hour; t is time and ∆t represents the time step. This equation calculates the LCOE of a power generation project by dividing the net present cost of the project by the total power produced over a one-year period. The net present cost of the project includes all costs associated with the project, including capital costs, operating costs, and financing costs. The capital recovery factor is used to convert the initial capital cost of the project into a series of annual payments over the life of the project.

A specific site with coordinates (24.674 N, 46.719 E) in the center of Riyadh was selected for the study. Since solar radiation and meteorological conditions are important, the peak profile of each month (Table 4) was used in both simulation programs to calculate energy production and cash flow. The selected site is the building of the engineering college of King Saud University in Riyadh.

Table 4 shows the monthly energy consumption in the engineering building of King Saud University and the peak electricity demand. According to the statistics, the second quarter of the year has the highest energy consumption with peak values (274.24 kW) at the end of May and beginning of June, and the lowest values (162.55 kW) in November [69]. It was found that the annual net electricity consumption cost is reduced to 50% by installing PV panels with an annual energy production of 809.09 MWh. These are net savings in the first and third quarters of the year as demand decreases due to temperature weather conditions.

Both simulation algorithms used the monthly values for global solar radiation and temperature on the horizontal surface of the proposed site (24.674 N and 46.719 E), as shown in Table 4. As shown in Figure 6a, the proposed PV system is a fixed array system with tilt and azimuth angles of 20° and 180°, respectively. Through this arrangement, the efficiency of the PV panels is up to 19% with a capacity factor of approximately 46%, as shown in Table 5. Schematic diagrams of the PV panels can also be seen in Figure 6b.

The efficiency of the module and the characteristics listed in Table 6 were simulated based on the mentioned position and orientation of the panels, as shown in Figure 6a.

As shown in Table 6, the calculated area of PV panels was calculated as 1.631 m² with 96 cells, and the material used was mono silicon carbide. The total land area was calculated to be 0.9 acres including the module area of 1135.2 m², and the physical characteristics of the module and the system were calculated based on the monthly temperature and radiation patterns.

6. Results and Discussion

Some of the operating parameters of the PV system are listed in Table 7. The AC and DC power determined using the two analysis methods (SAM and RETScreen) provides a deviation of approximately 1%. Since there is a difference between the operating scenarios of power consumption at night and during the day, we have calculated the operational power consumption and the stored power consumption during off time (night). The calculation shows that the efficiency during day time (operational) reaches 97% in SAM and 95% from RETScreen, while the off time analysis predicts a maximum efficiency of 17%. Moreover, the AC/DC voltage corresponds to a maximum of 800 V with minimum MPPT value is 570 V and maximum as 800 V. It is noted that the errors of the two simulation programs are less than 2%, indicating that the designed PV system is well-optimized for the prototype system.

To determine the most cost-effective and efficient PV system, an economic analysis was performed using the SAM and RETScreen programs, as shown in Table 8. Since a total of 969 modules were divided into three units and both the modules and inverters contributed a direct cost difference of USD 574,860 and USD 179,667, respectively, with a percentage error of 11% and 10%, respectively. This shows that the reported capital costs support the longevity and cost effectiveness of the proposed PV system.

Figure 7 shows that the output voltage increases rapidly and reaches higher values of approximately 100 volts, which corresponds to the MPPT of the optimal PV solar system. The MPPT converts the higher voltage DC of the solar modules to a lower voltage suitable for the batteries. The C-rate, the temperature profile with higher and lower temperatures, and the depth of charge are other factors to consider. These variables are interrelated via MPPT, which is in turn related to the cycling efficiency of the system.

The cumulative electricity load increases from January to March (the beginning of summer) with an estimated value ranging from 60 kWh to 62.5 kWh as illustrated in Figure 8. A significant increase in load is observed until August with a peak value of 87 kWh, which then decreases by a factor of 30% until November and finally decreases until the end of the year. Almost the same pattern was observed in RETScreen, with a slight variation in the electrical load profile as the start of the program is at 50 kWh. The load was estimated using both SAM and RETScreen, and there were no significant variations in the results, indicating that the simulations were consistent. In contrast, the scenario of electricity generation shows different patterns throughout the year. From January to February, electricity generation increases slightly to 30 kWh and follows the same pattern in the following months, peaking in June and August. This is because solar radiation in Riyadh is the highest during this period and electricity generation should therefore be maximized. The downward trend continues until the last months of the year. Both simulation programs confirm each other’s data, as almost the same trends were obtained.

The cash flow scenario generated using both modeling programs for the proposed PV system shows a downward trend in Figure 9, as the associated tax decreases over time with an increase in monthly expenses, obeying the concept of FOAK (First of a Kind) > NOAK (Nth of a Kind). It is found that the observation follows the principle, and it can be seen that the decrease from 6.5 years maintains constant values for 25 years. A comprehensive result for some of the main parameters of the PV system can be found in Table 9. It can be seen that the electricity cost is cheaper with the PV system and the payback period is higher, with an efficiency of 77%, which is acceptable for the installation in the Riyadh region. The analysis was then validated against the published work and it was found that the benchmark results are in agreement with the simulation results, which confirms the accuracy of the simulation results.

7. Conclusions

In this study, we investigated different elements of solar PV systems and their deployment, focusing on the GCC region and Saudi Arabia. We studied different types and characteristics of PV cells and found that a module made of monocrystalline silicon was the most efficient. This result was also confirmed by studying a type of cell with the required surface area for a power of 1 kW. The results of the geographical, meteorological, prognostic, and economic evaluations of the current study presented an efficient approach for installing a PV system in Saudi Arabia. In addition, we evaluated the performance of a 600-kilowatt PV. The CAPEX of PV modules and inverter is calculated as USD 210 k and USD 60 k, respectively. All these results were validated using SAM and RETScreen. The final PV system design layout increases the capacity factor to 17.6%. We found that with a performance ratio of 77%, the normalized LCOE was calculated as USD 0.061/kWh, while the real cost is calculated as USD 0.053/kWh. The system runs with an actual value of USD 10,242 having payback period of 16.8 years. The net CAPEX of the entire system was calculated as USD 3,982,655. As a result of the current study, we concluded that building this type of PV system is an efficient and cost-effective approach to introduce PV technology, especially in Riyadh, Saudi Arabia.

Author Contributions

Conceptualization, S.U.-D.K.; methodology, S.U.-D.K. and I.W.; software, S.U.-D.K.; validation, S.U.-D.K.; formal analysis, S.U.-D.K. and I.W.; investigation, S.U.-D.K. and Z.A.; resources, S.U.-D.K., I.W. and Z.A.; data curation, S.U.-D.K. and I.W.; writing—original draft preparation, S.U.-D.K. and I.W.; writing—review and editing, S.U.-D.K. and I.W.; visualization, S.U.-D.K., I.W. and Z.A.; supervision, S.U.-D.K. and Z.A.; project administration, S.U.-D.K.; funding acquisition, S.U.-D.K. All authors have read and agreed to the published version of the manuscript.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors declare no conflict of interest.

Abbreviations

AC	Alternating current
CC	Combined cycle
CSP	Concentrated solar power
CUF	Capacity utilization factor
DC	Direct current
DHI	Diffuse horizontal irradiance
DNI	Direct normal irradiance
EROC	Energy return on carbon invested
EROI	Energy return on energy invested
GCC	Gulf Cooperation Council
GHI	Global horizontal irradiance
HIT	Heterojunction with Intrinsic Thin layer
K.A.CARE	King Abdullah City for Atomic and Renewable Energy
LCOE	Levelized cost of energy
MPPT	Maximum power point tracking
OECD	Organization for Economic Cooperation and Development
PV	Photovoltaic
REPDO	Renewable Energy Project Development Office
SAM	System advisor model
SC	Simple cycle
ST	Steam thermal
SZA	Solar Zenith Angle
UAE	United Arab Emirates
$	USD
C-rate	Charging/discharging rate of batteries

Footnotes

Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Figures and Tables

Figure 1. PV cell, module, and an array (not to scale).

Figure 2. Types of PV system installation.

Figure 3. Top 10 countries in terms of solar energy production (PV on land). Data are taken from [47].

Figure 4. Performance comparison of different regions of KSA based on the annual PV energy output. Data are taken from [56].

Figure 5. Working mechanism of SAM and RETScreen.

Figure 6. (a) Orientation and tracking of PV modules, (b) Schematic of PV modules.

Figure 7. Trend of rated output power.

Figure 8. Comparative analysis of energy production by SAM and RETScreen.

Figure 9. Comparative analysis of cash flow trend by SAM and RETScreen.

Table 1

Types of PV cells and their characteristics [1,38].

Type of PV Cell	Construction	PV Cell Efficiency	Module Efficiency	Stage of Development
Monocrystalline silicon	Uniform crystalline structure	24%	14–20%	Industrial application
Polycrystalline (multi-crystalline) silicon	Multi-crystalline structure—different crystals visible	18%	13–15%	Industrial application
Hybrid HIT solar cell	Combination of crystalline and thin-film cells	>20%	17.3–19.5%	Industrial application
Amorphous silicon	Atoms irregularly arranged. Thin film technology	11–12%	5–9%	Industrial production
Gallium-arsenide	Crystalline cells	25.0%		Produced exclusively for special applications (e.g., spacecraft)
Gallium-arsenide, gallium-antimony & others.	Tandem (multijunction) cells, different layers sensitive to different light wavelengths	25.0–31.0%		Research and development stage
Copper indium selenide	Thin film, various deposition methods	18.0%	10.0–12.0%	Industrial production
Cadmium-telluride & others	Thin film technology	17%	9–11%	Ready to go into production
Organic solar cells	Electrochemical principle-based	5–8%		Research and development stage—not commercially available

Table 2

Surface area required to produce 1 kW according to a cell type [39].

Cell Material	Module Efficiency	Surface Area Need for 1 kW
Monocrystalline silicon	11.0–16.0%	7–9 m2
Polycrystalline silicon	10.0–14.0%	8–9 m2
Thin film copper–indium–diselenide	6.0–8.0%	11–13 m2
Amorphous silicon	4.0–7.0%	16–20 m2

Table 3

Characteristics of types of PV systems.

	PV System	Characteristics
1.	Perovskite solar cell	Perovskite solar cells are a relatively new form of photovoltaic technology that has attracted considerable interest in recent years because they have a very high efficiency and a low production cost. The term “perovskite” refers to its crystal structure, which is a mixture of organic and inorganic components. Despite all their advantages, perovskite solar cells still have certain drawbacks, such as stability problems and the use of hazardous compounds in manufacturing. However, ongoing research aims to overcome these difficulties and make perovskite solar cells a more realistic choice for wider application in the future.
2.	Grid-connected PV system	Grid-connected photovoltaic (PV) systems are electricity generation systems that are connected to the power grid and can range in size from small residential houses to huge industrial plants [42]. They cost extra because their batteries are not installed. An electricity meter measures the amount delivered to other consumers and calculates how much extra electricity is fed into the grid for other consumers to use [40]. The inverter converts the power from DC power to AC, monitors and controls the grid voltage and waveform, and detects grid faults to prevent power outages.
3.	Off-grid PV system	An off-grid system is a power generation system that employs a charge controller to regulate the amount of electricity flowing to and from the batteries of a power system [40]. PV modules power an off-grid solar system. The choice of an appropriate PV module is critical to the success of an off-grid system. The most important component is the charge controller, which can be of two main types: a PWM (pulse width modulation) charge controller and an MPPT (maximum power point tracking) charge controller. The MPPT solar charge controller delivers 30% more charged volts than the PWM charge controller, which makes it more efficient and cost-effective [43]. Due to its high output voltage, the MPPT solar charge controller is prone to overheating and requires regular temperature adjustment to keep it functional.
4.	Hybrid photovoltaic system	A photovoltaic hybrid system is a power system that combines either a grid-connected or an off-grid PV system with an external power generation source. Two common forms of PV hybrid systems are photovoltaic hybrid diesel and photovoltaic wind systems [44]. In the first case, one of the two photovoltaic systems mentioned above is combined with a diesel generator. In the second case, one of the two photovoltaic systems is combined with wind generators [44]. The main purpose of these two types of hybrid systems is to bridge the gap between the energy generated by a system and the transmitted electricity loads.

Table 4

Monthly energy consumption in the Riyadh region (King Saud University).

Month	Energy (kWh)	Peak (kW)
January	58,276.87	171.04
February	53,225.90	183.59
March	60,010.00	189.56
April	61,632.89	235.94
May	82,652.49	274.24
June	85,352.66	262.46
July	86,439.30	263.98
August	72,097.05	249.14
September	65,319.20	222.34
October	56,319.20	202.14
November	56,363.05	162.55
December	57,827.35	185.17
Avg. Annual	66,292.97	216.84

Table 5

Module characteristics.

Parameter	Values
Total irradiance (W/m2)	1000
Cell temperature (°C)	25
Nominal efficiency	19.029%
Maximum power	310.15 Wdc
Maximum power voltage	54.7 Vdc
Maximum power current (Amp)	5.7 Adc
Open circuit voltage (Voc)	64.4 Vdc
Short circuit voltage (Isc)	6.1 Adc

Table 6

Physical characteristics of module and system.

Parameter	Values
Area	1.631 m2
Number of cells	96
Material	Mono-c-Si
Module width	1.0 m
Module length	1.63 m
Space between back and roof surface	0.05 m
Modules per string in a subarray	12
Strings in parallel in subarray	58
Number of modules in subarray	696
Total module area	1135.2 m2
Total land area	0.9 acres
Number of modules alongside of row	2
Number of modules along bottom of row	7
Number of rows	49
Length of one side	3.330 m
Estimated row spacing	11.101 m
Aspect ratio of module	1.7

Table 7

Efficiency curves and characteristics.

Parameter	Values
	SAM	RETScreen	Error (%)
AC power (max)	59,860 Wac	52,860 Wac	1.13
DC power (max)	61,130.8 Wdc	60,130.01 Wdc	1.02
Power consumption (in operation)	97.21 Wdc	95.33 Wdc	1.02
Power consumption (night)	17.96 Wac	15.01 Wac	1.20
AC voltage (nominal)	400 Vac	380 Vac	1.05
DC voltage (max)	800 Vdc	760 Vdc	1.05
DC current (max)	97.03 Adc	94.01 Adc	1.03
MPPT voltage (min)	570 Vdc	548 Vdc	1.04
DC voltage (nominal)	630 Vdc	612 Vdc	1.03
MPPT DC voltage (max)	800 Vdc	771 Vdc	1.04

Table 8

Economics parameters.

Parameter	Values
	SAM	RETScreen
For modules:
Units	696	696
DC power per unit	0.3 kWdc/unit	0.3 kWdc/unit
Total power	600 kWdc	600 kWdc
Cost per watt	USD 0.35	USD 0.35
Direct capital cost	USD 210 k	USD 210 k
For inverter:
Units	03	03
AC power per unit	59.9 kWac/unit	57.01 kWac/unit
Total power	600 kWac	600 kWac
Cost per watt	USD 0.10	USD 0.10
Direct capital cost	USD 60 k	USD 60 k

Table 9

Comprehensive results for the PV system with SAM and RETScreen.

Metric	SAM	RETScreen	Ref. [70]
Annual energy (kWh)	332,019	332,000	334,099
Capacity factor (%)	17.6	17	17.70
Energy yield (kWh/kW)	1538	1601	1548
Performance ratio	0.77	0.75	0.77
Nominal Levelized cost of electricity (USD/kWh)	0.0661	0.0660	0.0657
Real levelized cost of electricity (USD/kWh)	0.0528	0.0502	0.0525
Electricity cost without a system (USD)	111,909	111,012	58,520
Electricity cost with a system (USD)	88,752	80,875	36,908
Savings with a system (USD)	23,157	21,140	21,612
Present value (USD)	10,242	10,011	23,612
Payback period (years)	16.8	16.8	6
Net capital cost (USD)	392,655	309,251	392,655
Equity (USD)	157,062	156,242	157,062
Debt (USD)	235,593	230,521	235,593

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