With the advancement of industrialization and urbanization, the world’s energy consumption continues to increase. Every day more people are migrating to cities, where they live in a society confined to buildings. As a result, the daily energy consumed by buildings grows exponentially and increases the emissions of greenhouse gases (GHG) (Musa et al., 2024). Buildings are among the priorities for climate change mitigation strategies since they account for one-third of the world’s final energy consumption and one-fifth of its greenhouse gas (GHG) emissions (Lang et al., 2016). Approximately 74% of the worldwide energy needs are met by fossil fuels (International Energy Agency, 2020). As the main source of energy generation, fossil fuels especially natural gas, coal, and diesel pose significant problems to global warming and GHG. There is an increase in the development and integration of sustainable energy sources to fulfill energy demands in order to lessen these issues (Habib et al., 2023a; Ehsan et al., 2024; Bashir et al., 2024; Habib et al., 2023b).

Photovoltaic (PV) offers a promising technology to achieve this goal because of its significant and prominent environmental benefits as that of a low-carbon energy source and its substantial potential for economic development (Liu et al., 2022; Tamoor et al., 2022a; Nguyen et al., 2024; Bhatti et al., 2024; Wen et al., 2022). After a significant reduction in photovoltaic manufacturing costs due to large-scale deployment, photovoltaics has become economically competitive with alternative energy sources around the world (Zander et al., 2019; Tamoor et al., 2022b; Sinha and Ghosh, 2024; Tamoor et al., 2022c; Tamoor et al., 2020). The main factors behind the constant growth of this technology are its significant cost reduction and the environmental problems associated with fossil fuels. The global cumulative photovoltaic installed capacity has increased exponentially from nearly 0 GW in 1990 to 505.0 GW in 2018 (Appavou et al., 2019). Additionally, 102.4 GW of new PV systems were installed globally in 2018 (Muteri et al., 2020). In contrast to concentrated solar power (CSP) systems, photovoltaic technology can generate energy also in regions with moderate levels of solar irradiance. As a result, this technology has the potential to be utilized (i.e., at the commercial or residential level), and the idea of the solar city has captured the interest of many engineers and researchers (Bouramdane et al., 2021; Tamoor et al., 2021a; Huda et al., 2024; Alshehri et al., 2024; Miran et al., 2022; Tamoor et al., 2021b).

The energy consumption of buildings is increasing rapidly every day in both hot and cold regions (Huang and Zheng, 2018; Kang et al., 2021; Habib et al., 2023c). Office buildings contribute considerably more to this high consumption of energy, consuming 17% of all energy globally (EIA, 2016; EIA, 2006). Energy consumption in Asian countries is extremely high during the summer solstice (Ramli et al., 2017; Liu et al., 2021). The high load during the summer is a result or consequence of the energy required for cooling in both commercial and residential buildings. In the upcoming years, global warming will increase the load even more (Prieto et al., 2018; Van Ruijven et al., 2019). In Asian countries, buildings account for 80.0% of the total energy consumed (Asif, 2016; Shaahid and Elhadidy, 2008), but in European countries, this share is only 40.0% (Machete et al., 2018). In particular for office buildings, photovoltaic installations can be a suitable option to meet the high summer energy demands as the energy generation pattern of photovoltaic systems matches the load pattern of office buildings because primary loads of buildings are high during office time i.e., daytime.

Rooftop PV is an excellent option to integrate renewable energy into the national grid without changing the use of land or adding more distribution or transmission lines (Wiginton et al., 2010; Palmer-Wilson et al., 2019). Rooftops of urban buildings offer potential and suitable sites for photovoltaic (PV) installations. However, an effective approach to harvesting rooftop solar potential by identifying suitable and appropriate roofs to optimize photovoltaic (PV) installations still seems to be challenging (Mohajeri et al., 2018; Mountain and Szuster, 2015). Research on optimizing photovoltaic (PV) installations has started to progress mainly in developed countries in Europe and America, however, there is a shortage of maps showing the potential of solar energy generation for future solar urban planning (Huang et al., 2019). The size of the research area is one of the most crucial factors in assessing the potential of rooftop photovoltaic systems (Schallenberg-Rodríguez, 2013). Applying the same methodologies on a local, regional, or continental scale is often not possible because of the time-consuming procedures, the substantial cost of obtaining the information from various sources, and the lack of diversity in some sections of the data.

Studies investigating PV self-consumption have primarily examined case-specific building types, such as single-family homes (Lang et al., 2015; Chwieduk and Chwieduk, 2021), large-size office buildings (Prajapati and Fernandez, 2019), university campuses (Ali and Alomar, 2022; Tarigan, 2018), or multiple buildings (Ahsan et al., 2020). The utility-scale rooftop photovoltaic system installed in Switzerland was analyzed by Assurin et al. (Assouline et al., 2018) using random forests to determine its generation capability. They proposed a method for calculating roof areas that are available for installing photovoltaic modules and assessed the shading losses brought on by surrounding buildings and trees, without accounting for the losses brought on by mutual shade of the tilted photovoltaic modules. Fina et al. (2020) developed a method to evaluate the economic viability of roof-top photovoltaic systems depending on neighboring energy communities and expanded roof-top photovoltaic potential to analyze the renewable energy-related policy goals of Austria. Shukla et al. (2016) designed and installed a stand-alone 110-kW photovoltaic system on the flat roof of an Indian hostel. The authors thoroughly examined the technical as well as financial aspects of the proposed photovoltaic system; however, the shading losses were not taken into account. The technical performance of a 5-kW roof-top photovoltaic system was assessed by Yadav and Bajpai (2018). They examined the array efficiency, CUF, average daily energy output, and energy yield of PV systems, but they did not analyze the shading losses. A 200-kW roof-mounted photovoltaic system was studied by Kumar et al. (2019) by using PVSyst simulation software to calculate approximate output energy generation and energy loss and analyze the performance ratio, efficiency of the system, and CUF.

Satpathy et al. (2021a) designed a 19.2 kW grid-connected PV system using PVsyst software, taking into account the site’s meteorological data, available components, and numerous loss characteristics for residential buildings. The 3D modeling of the roof is performed in the Sketchup Skelion environment to ensure optimal module placement and prevent unexpected shading during operational hours. The analysis indicates that the estimated system size suggested by both software tools matches closely, with the maximum output of the proposed system estimated at 25 MWh/year. Additionally, the system and maximum array losses are determined to be 0.44 and 0.93 kWh/kWp/day, respectively. Another research examines a comprehensive examination of a 100 kW grid-connected photovoltaic system, including its location, system design, module orientation, selection of components, loss analysis, and energy yield. This research has been utilizing the most efficient PVsyst software for determining acceptable parameters for the optimum planning and designing of a 100 kWp PV system (Satpathy et al., 2021b). In order to determine the prospective benefits of rooftop PV systems, several researchers (Singh, 2020; Mohamed et al., 2024; Tamoor et al., 2023; Al-Amin et al., 2024; Monna et al., 2020; Vargas-Salgado et al., 2024; Yang et al., 2024; Thotakura et al., 2020; Abd Elsadek et al., 2024) utilized simulation software like PVSyst, HelioScope, Homer Pro, Solmetric SunEye, PVGIS, and PV*Sol.

The RETScreen software has been employed to conduct techno-economic, and environmental analyses for a 10.0 MW utility-scale grid-connected PV system across seven cities in Benin. According to the assumptions described in this research, the photovoltaic system generates approximately 13,222 MWh per year of electricity that can be exported to the grid. This results in a PR of approximately 67.3% and a capacity factor of 15.1%. The project produces an LCOE that ranges from 0.110 USD/kWh to 0.125 USD/kWh. In comparison to the utility grid, the utility-scale PV system reduces CO2 emissions by approximately 76.0% (Akpahou et al., 2024). Boruah and Chandel (2024) conducted a technical and economic feasibility study on five commercial grid-connected PV systems with battery energy storage under both net-metering and without net-metering regimes. The Solar Labs and PVSyst software have been used for system design and energy generation calculation, proceeded by HOMER grid software and Excel-based financial simulations for optimization of systems and cost-benefit analysis. The analysis indicated a 200 kWp PV system integrated with a 250 kWh energy storage under net metering as the most optimized solution, with an energy generation cost of 4.21 INR/kWh and a payback period of 6.15 years.

Another research intended to assess the technical, economic, and environmental performances of grid-connected and stand-alone hybrid systems across 21 provinces in seven regions of Turkey, taking into account variations in regional solar irradiations and wind speed. Hybrid systems have been designed and simulated utilizing the HOMER PRO to supply the daily energy demand of 13.2 kWh/day for a home. The results indicated that the most suitable configurations are PV/WT/Grid for a grid-connected hybrid system and PV/WT/DG/BESS for a stand-alone hybrid system. The NPC value ranges from $2,540 to $8,951 for grid-connected and from $23,372 to $40,858 for stand-alone systems (Ayan and Turkay, 2023). This research presents a techno-economic evaluation of grid-connected PV systems in arid regions, focusing on the aspect of peak shaving. The impact of a commissioned 102 kW PV system on peak shaving for the waste-management organization building is evaluated as a practical case. The findings confirm that the installed PV system reduces the peak demand of commercial buildings by an average of 40%–50% during summer afternoons. The results indicated that the proposed project is economically feasible, demonstrating an NPV of €43,671 and an IRR of 34.5% (Mousavi and Bakhshi-Jafarabadi, 2024).

The objective of this research is to examine the potential and assess the optimum methods for installing a grid-connected photovoltaic system on the roof of commercial buildings. This research study comprehensively investigates the constraints/challenges on commercial building rooftops in order to evaluate the utilization of rooftop areas for photovoltaic energy systems. The current research work consequently fills a gap in the scientific literature as it aims to determine the potential of photovoltaic installation on commercial buildings. Commercial buildings vary widely in terms of their sizes and purposes. The shopping plaza is the primary building type covered in this study. The range and intensity of various architectural, structural, and service characteristics that limit the usage of photovoltaics on building rooftops are examined using satellite images. Site visits were also conducted to review and understand the condition of the roof in detail and to verify the results of the assessment procedure based on satellite images. Software such as HelioScope, Aurora Solar, and some standard data are used in the design. For this system, PV modules are mounted on a fixed-mount racking system. The grid-connected photovoltaic system is designed with the HelioScope software. The 3D model is designed and shadow loss is analyzed using Aurora Solar. Building a 3D model with appropriate photovoltaic module configurations, such as azimuth angle, tilt angle and inter-row spacing is challenging when using HelioScope software. In order to optimize solar irradiation, the PV modules are installed at 180° azimuth angle and a 15° tilt angle. To maximize the output energy production of the PV system, we examined different Inter-row spacing.

Although ground-mounted photovoltaic systems are easier to operate and require less maintenance, it is difficult to install PV systems in metropolitan areas due to the cost and availability of land. In contrast, rooftop photovoltaic systems involve no land costs and block solar irradiance from making direct contact with the roof’s exterior surface. High temperatures in extremely hot regions, cause building roofs to heat up due to direct sunlight hitting the roof surfaces. In these hot climate regions, solar (PV) modules mounted on building roofs would reduce building cooling energy requirements due to their ability to shade the roof. Utilizing a grid-connected photovoltaic system reduces the electricity bill because it minimizes the need for a 100% electricity supply from the national grid. The shopping plazas will profit from reduced energy bills, the ability to meet load demand, and be friendly to the environment if the rooftop space of the commercial shopping plazas is utilized efficiently. As a result, it would be highly beneficial to assess the performance of roof-top photovoltaic systems installed on commercial shopping plazas. In summary, the contributions of this research work are as follows.

• Detailed solar resources including solar irradiance (kWh/m²), wind speed (m/s), ambient temperature (°C), and hourly PV module temperature (°C) for each month have been analyzed.

From a methodological point of view, this research uses an empirical and deductive research design to improve the energy generation performance and efficiency of rooftop photovoltaic systems. From an operational and economic perspective, the ultimate objective of this research is to investigate how different design factors affect a rooftop photovoltaic system’s ability to generate energy. These factors such as tilt and azimuth angles, GHI, ambient temperature, and shading from the surrounding obstacles as shown in Table 1.

Energy demand rises as a result of economic expansion and urbanization. Pakistan, a high-energy-demand nation, fills the shortfall in its energy supply by importing fossil fuels. Pakistan has to modify its energy policy to emphasize sustainable, clean, and renewable energy resources, like other developed nations. Pakistan has enormous solar potential with a 1691.9 kWh/m² annual global horizontal solar irradiance. Pakistan has currently made the transition to sustainable energy and developed new regulations for renewable energy systems, including the installation and commercialization of a rooftop photovoltaic system. Therefore, this requires detailed evaluation to determine the capabilities of the PV system and convince decision-makers. To achieve this goal and calculate the appropriate rooftop area for photovoltaic modules, simulations are carried out using HelioScope software.

The objective of this research is to examine the potential of a rooftop photovoltaic system for commercial buildings. This research examines the effects of different design factors on the efficiency and performance of a rooftop photovoltaic system. These factors such as tilt and azimuth angles, GHI, ambient temperature, and shading from the surrounding obstacles. The summer months experience the highest levels of global horizontal irradiance. Furthermore, the maximum hourly value of the GHI is 915 W/m² in May. The GHI is measured in May at its highest level (188.8 kWh/m²) and in December at its lowest level (82.3 kWh/m²). The wind speed fluctuates between 0.3 m/s at the lowest point to 7.8 m/s at the highest point. The daily average maximum wind speed is 3.406 m/s, while the average annual wind speed is 2.133 m/s. Ambient temperatures range from 5.1°C to 47.6°C, while average annual ambient temperature is 28.49°C. The maximum hourly operating temperature (°C) of photovoltaic module is 67.83°C in April, while the minimum hourly operating temperature is 1.22°C in January. Additionally, average daily maximum operating temperature of a photovoltaic module is 59.70°C, the average daily minimum operating temperature of a solar (PV) module is 4.47°C and the average annual operating temperature of a solar (PV) module is 34.85°C.

The commercial shopping plaza has a flat roof and two buildings. The photovoltaic module is tilted to capture the most intense solar irradiation. An optimal row-to-row distance is calculated with the aim of maximizing energy yield. By simulation analysis, it is found that a photovoltaic system installed with 5 feet Inter-row spacing is more efficient. With 5 feet inter-row spacing, the results of simulation indicate that annually energy generation of PV system is 371.6 MWh, specific yield (kWh/kWp) is 1508.0, performance ratio is 82.1%, solar access is 98.9% and TSRF is 96.3%. The maximum daily DC inverter input power is 194614.7417 W, and the average daily DC inverter input power is 158881.5110 W. The maximum daily AC inverter output power is 186698.6914 W, whereas the average daily AC inverter output power is 152231.6311 W. The output power (AC) is barely less than the input power from PV arrays, showing an inverter efficiency of approximately 95.93%.

According to the simulation results, the total irradiance (kWh/m²) on the collector is 1724.9 kWh/m². The annual nameplate energy of the system is 425017.6 kWh, the output energy at irradiance levels is 423121.8 kWh, the optimal DC output is 378460.5 kWh, the energy at inverter output is 373539.7, whereas the total amount of energy that is fed into the national power grid is 371672.1 kWh. The annual production of roof-mounted PV system installed on a commercial shopping plaza in the first year is 371672.1 kWh, in the second year, the annual production is 369760.1 kWh, while in the twenty-fifth year, the annual production is 328329.1 kWh and total annual production of PV system in 25 years is 8739615.5 kWh. This means that the installed photovoltaic system depreciates energy at a rate of 0.88% per year and falls in the standard warranty rate of 0.8% per year. In the designed system installed on a commercial shopping plaza, the system has 7.2% temperature losses, 3.3% mismatch losses, 0.40% wiring losses, 0.0% clipping losses, 0.5% AC system losses, 1.3% inverters losses, 3.1% reflection losses, 1.1% shading losses, 2.0% soiling losses and 0.41% irradiance losses.

After the Simulation study, detailed testing was performed at the site before commissioning to make sure that the equipment’s performance guarantees were met, properly installed, correctly adjusted, and suitable for commercial operations. Test results of installed photovoltaic system were taken for 30 days to evaluate and investigate the output generated energy (kWh) and performance of the photovoltaic (PV) system. We analyzed the experimental system in May because simulation results indicated that photovoltaic system produced the most energy during that month. The daily maximum output energy generation of installed PV system (1333.676 kWh) was recorded on day 23, and its average energy generation was 1091.56 kWh. Due to a faulty transformer on days 2 and 8, energy production is zero. The system is shut down for diagnostic tests from day 14 to day 16. By PV string open circuit voltage test, the maximum V_OC for inverter 1 is 835 V, inverter 2 is 834 V, inverter 3 is 835 V and inverter 4 is 698 V. Similarly, maximum V_OC for a string consisting of 18 PV modules is 835 V, V_OC for string consist of 17 PV modules is 789 V and V_OC for string consist of 15 PV modules is 698 V. It is found that voltages of all strings are within the rated range. PV String Isc Current Test shows that no reverse Polarity was detected, and each string’s earthing continuity was apparent enough to function without difficulty. The short circuit currents of the selected strings of inverters 1, 2, 3, and 4 are 9.99A, 10.0A, 9.81A, and 10.27A, respectively. The measured fill factor of inverters 1, 2 3, and 4 are 81.37%, 82.34%, 81.40%, and 81.91%, respectively.

To perform the inverter efficiency test, the input and output power was measured at the inverter terminal. The efficiency of inverter 1 is calculated to be 98.83%, inverter 2 is calculated to be 98.76%, inverter 3 is calculated to be 98.80%, and inverter 4 is calculated to be 98.81%. All inverters passed the inverter efficiency tests because their efficiency values are within the range of the rated inverter efficiency (98.7%). Megger is used for earth resistance and insulation tests of DC cables (Positive to Negative and negative to ground & positive to ground) and AC cables. The value of resistance of DC cables (positive to negative and negative to ground & positive to ground) varies between 1.6 GΩ and 1.9 GΩ for all strings. These values show that there is high resistance among each other. The insulation of DC cables is the same for all string and have a very high value (11 GΩ). The highest measured resistance of AC cables for inverter 1 is 3.9 GΩ between Red-Ground and Yellow-Neutral. The lowest measured resistance of AC cables for inverter 1 is 2.8 GΩ between Blue-Ground. The highest measured resistance of AC cables for inverter 2 is 3.8 GΩ, for inverter 3 is 3.8 GΩ and for inverter 4 is 3.9 GΩ. The insulation of AC cables for all inverters is 11 GΩ. All wire sequences have good insulation and high resistance among each other and there is not any major breakage in insulation during installation which may cause short circuit faults later on. The maximum performance ratio (80.90%) was recorded on day 6 and the average daily PR of the installed photovoltaic system was 75.70%. The installed PV system operates more efficiently because it has a high-performance ratio. The payback period of a solar (PV) system is 4.22 years and the LCOE of the photovoltaic system is 0.0229 $/kWh. The PV system saved 215569.818 metric tons of CO₂ in the first year and a total of approximately 5068976.99 metric tons in 25 years.