There is a growing trend towards developing and using renewable energy sources like solar, wind, and hydropower. Solar energy, in particular, has seen a steady increase in global installations and demand over the past two decades. However, large-scale solar farms on land can occupy significant areas, potentially impacting biodiversity. Additionally, geographical factors like sunlight intensity can affect solar energy utilization. Despite these challenges, advancements in technology are opening doors for alternative solar applications beyond traditional land-based installations.

This paper primarily focuses on (i) Analyzing the solar PV potential in forests, lakes, and buildings at the UMPSA Pekan campus. (ii) Conducting an economic analysis based on payback period and annual savings. (iii) Performing an environmental analysis in terms of annual carbon dioxide (CO₂) generation and net CO₂ reduction from solar PV installations. These data are calculated based on the simulation results of PV GIS and a Helioscope.

To analyze the solar PV potential on the rooftops of UMPSA Pekan buildings, including energy generation, annual savings, carbon dioxide emissions, and net CO₂ emission reductions.

The primary scope of this study is to compare and calculate the potential installation of solar PV systems in forest zones, lakes, and buildings through an extensive literature review. Based on the collected data, the study will evaluate the advantages and disadvantages of various solar technologies from technical, economic, and environmental perspectives. The case study focuses on specific areas at the University Malaysia Pahang Al Sultan Abdullah (UMPSA) Pekan campus, including its forests, Tasik Lake, and the Canseleri Tun Abdul Razak building. Additionally, the study assesses solar technologies for different scenarios of area utilization (40%, 60%, and 80%). These evaluations will consider improvements based on current trends in PV technology growth.

Forest photovoltaic system as shown in Fig. 1 is a synergy between carbon sequestration and renewable energy production [16]. Installation of PV systems over land faces significant challenges like deforestation, soil erosion, and loss of biodiversity [17]. The forest has large expanses of underutilized land beneath the canopy that can be utilized to deploy the PV system [18]. Also, resizing the canopy branches can provide space for the installation of solar PV modules. They provide ecosystem services beyond electricity generation. The presence of PV panels can help regulate microclimate, reduce soil erosion, and enhance biodiversity by creating new habitats for certain species. Integrating PV into forest management methods can help improve sustainability by diversifying revenue streams and lowering reliance on logging and other extractive activities. This can help prevent forests from deforestation and degradation while also supporting renewable energy ambitions. These challenges generated a new concept for the installation of renewable energy systems on forested land. This also allows more direct solar irradiation; albedo loss will be less.

The basic components of a Forestvoltaic system include:

Solar Panels: Solar panels, also known as photovoltaic (PV) panels, are devices designed to capture sunlight and convert it into electricity through a process called the photovoltaic effect [19–21]. These panels consist of multiple solar cells made from semiconductor materials, typically silicon. When exposed to sunlight, these cells generate an electric current by harnessing the energy from photons, which are particles of light.

A floating solar system, also known as a floating solar farm or floating photovoltaic (FPV) system, is a type of solar power installation where solar panels are mounted on floating structures on bodies of water, such as lakes, reservoirs, ponds, or even the open sea [26]. This innovative approach to solar energy generation as shown in Fig. 2 offers several advantages and has gained attention as a sustainable and efficient solution. Here are the key features of floating solar systems:

Floating Platforms: The solar panels in a floating system are typically mounted on buoyant structures that keep them afloat on the water surface [27]. These platforms can be anchored to the bottom of the water body, tethered in place, or allowed to drift within a designated area.

A Building Applied Photovoltaics (BAPV) system as shown in Fig. 3 refers to the installation of solar photovoltaic (PV) panels on the walls and roofs of a building by mounting structures and moving rails. Instead of being added on as an afterthought, the solar panels are designed to be an integral part of the building’s architecture. This integration serves both functional and aesthetic purposes, providing the dual benefit of generating renewable energy while seamlessly blending with the building’s design.

Solar Panel: BAPV systems involve the incorporation of solar modules directly into various building elements, such as polycrystalline, monocrystalline, and amorphous thin-film solar panels.

Forestvoltaics, Floatovoltaics, and BAPV represent innovative approaches to harnessing solar energy in diverse environments. Each method offers unique advantages and challenges, catering to specific geographical, infrastructural, and environmental conditions. Table 1 discusses the differences in innovative technology as per location, environmental impact, efficiency, and scalability.

Universiti Malaysia Pahang Al-Sultan Abdullah (UMPSA) is located in the east coast state of Pahang, which is the biggest among other states in Peninsular Malaysia. UMPSA has its base campus located in the Pekan and another campus in the Gambang. However, in this case study, the Pekan campus was chosen because of the variety of places that have buildings, agriculture, and water bodies. The rural campus of UMP is known as the Pekan campus. With 2000 staff members, 15,000 students (5000 in Gambang and 10,000 in Pekan), 18 departments or units, and ten faculties, Universiti Malaysia Pahang Al-Sultan Abdullah (UMPSA) is a QS-ranked educational institution that contributes to the engineering, technology, and creativity fields. The campuses are made up of dependable infrastructure and facilities. Apart from this, UMPSA has a special interest in practicing energy and environmentally efficient practices to promote renewable and sustainable energy usage on campus. Geographically, UMPSA Pekan is situated at Latitude 3.544°N and Longitude 103.429°E. The UMPSA Pekan campus is about 12 m above sea level. The UMPSA has a total area of 658.06 acres, which is the result of two campuses, including the 642-acre Pekan campus, which is located on the rural side as marked in Table 2. As shown in Fig. 5, the lake, forest, and rooftops of buildings The lakes and forest area are marked in Fig. 5a, while the other rooftop areas of the building are respectively shown in Fig. 5b, c. Given that UMPSA has 658.06 acres of land, many of the open spaces—more than 20%—can be used. In addition, roof space could be utilized. In the below Google Earth terrain image, the red line shows the Universiti Malaysia Pahang Al-Sultan Abdullah (UMPSA) Pekan campus, while the forest and lakes have been marked for the study of the potential of solar PV installation.

A photovoltaic geographic information system, or PVGIS for short, is one of the most well-known tools for evaluating the efficiency of solar PV power plants on most of the continents of Europe, Asia, and Africa. This tool is packaged with estimates for economic parameters, such as the cost of electricity, a performance assessment method, and a database of solar radiation [34]. The parameters needed for PV plant sizing can be entered into PVGIS based on the load or any hypothetical plants. The slope, tilt, and azimuth angles of the PV module can also be optimized by the user. Simulated results are displayed in a variety of ways depending on the user’s preferences, including as graphical representations, tabular columns, excel sheets, and PDF files. Using PVGIS, the user can perform the following analysis:

Consummation of grid-connected PV

The leading software platform for designing and evaluating the performance of a solar plant for medium-sized to large solar PV plants are called a Helioscope. The initial input for the Helioscope software is the area’s longitude and latitude; alternatively, as shown in Fig. 6, if the area’s name is correctly entered in the designated window, the area map of the relevant land is automatically downloaded. Once the area’s location has been determined in the software, the primary feature of the Helioscope is to put the field segments. The field segments consist of heights, azimuths, tilts, and module layouts. Further electrical segments consist of inverters and a range of maximum power point tracking (MPPT) strings. Also, it can select the appropriate kind of panels and inverting, and the entire plant’s layout is automatically generated with all the necessary information, including power output, system loss, energy to the grid, the number of modules and inverters, and the arrangement of the panel.

Methodology of Helioscope for designing Forestvoltaics, Floatovoltaics, and Building Applied Photovoltaic (BAPV) is shown in Fig. 7. In Helioscope, create a login and project name. Enter the Global Positioning System (GPS) coordinates for your forest, lake, and building areas. This allows you to design separate projects utilizing solar panels for each application (forest, lake, Building). Within a new project, navigate to the “Mechanical” layout section. Here, you will define the placement of your solar panels. “Field Segments” represent areas like forests, lakes, and building roofs suitable for panels.

Conversely, “Keep Outs” defines areas excluded due to shading from surrounding obstacles. Optimize your design by setting the maximum system size at the periphery and specifying the canopy area for solar coverage. Choose a suitable solar module for your project. Next, define the height, azimuth (orientation), tilt, layout, setbacks, and alignment of your panels, considering the specific conditions of forests, lakes, and building areas. Inverter placement also varies by location. In forests, position the inverter below the tree canopy for shade. For lakes and buildings, prioritize shaded areas to enhance inverter cooling. Finally, plan the string layout for connecting the solar panels in series. In the forest zone, route the strings internally to connect all panels. Due to limited combiner box inputs, combine these series strings from the solar panels as needed.

The solar panel forms the main part of the entire PV system, which accounts for the conversion from solar irradiance to DC electricity. On the types of various technologies, polycrystalline, monocrystalline, and amorphous solar PV have an efficiency of 15%, 20%, and 10%, respectively. Solar power capacity is given by the formula: (1)Pc=Ap.Pd

In the Eq. (1), Pc is the capacity of Forestvoltaic, Floatovoltaic, and BAPV system in MW, while Ap is the area coverage of the solar plant in meter square with a Pd as a power density, in general, the power density is taken as FPV power density = kW/10 m². (2)Eg=Pc.Uc.Thwhere Eg is the annual energy generated by the Forestvoltaics, Floatovoltaics, and BAPV measured in Megawatt hour (MWh) MWh/year shown in Eq. (2). Pc is the nameplate capacity of the solar plant installed, i.e., forestvoltaics, floatovoltaics, and BAPV. Capacity Utilization factor Uc measures a plant’s energy production over a time Th, i.e., 21 years in Malaysia. It is typically calculated by dividing the total energy produced over a given period. It calculates the amount of energy the plant would have produced if it ran at full load [36].

Eqs. (1) and (2) are used to conduct an economic analysis of the planned PV project. The annual savings and payback durations were determined. (3)Cs=Eg.FiT where annual savings Cs are in Malaysian ringgit (RM)/year, energy generation is in MWh/year, and FiT rate is the tariff rate for solar power purchased as shown in Eq. (3). The proposed solar power plant’s carbon mitigation is done by Eq. (4) takes the following approach: (4)eco2=Eg.GEF

The CO₂ emission is measured in tCO₂, which is the yearly energy generation measured in MWh or kWh, and its grid emission factor. The grid emission factor (GEF) is defined as the CO₂ emission factor (tCO₂/MWh) that is connected to every unit of electricity produced by a power system and is calculated per kWh or MWh. However, solar power facilities are not fully emission-free. Estimating CO₂ emissions per kWh generated by solar plants is minimal. The emission from the PV facility is calculated using Eq. (5). (5)epv=Eg.eco2where CO₂ emissions from a PV plant are measured in tCO₂, annual energy generation in MWh or kWh. Eq. (6) calculates the net reduction in CO₂ emissions from the solar PV plant. Net CO₂ reduction is the overall reduction in carbon dioxide (CO₂) emissions achieved by transitioning from traditional power plants to photovoltaic (PV) power plants. This reduction represents a significant environmental benefit as it helps mitigate climate change by reducing greenhouse gas emissions and minimizing the carbon footprint associated with electricity generation. (6)enet=eco2−epv

Based on Helioscope software, the forest voltaic potential of the UMPSA Pekan campus is estimated. Table 3 shows the solar PV site capacity to be installed over forest zones 1, 2, 3, and 4. The red line shows the area demarcated, the green line shows the periphery area where solar trees are planted, and the light blue shaded part shows the solar panels in the canopy area. Based on the percentage of land covered, there are three different cases discussed: the optimistic case (60%).

The Potential of Forestvoltaics Capacity (MW) with Different Solar Technologies

Total Area = 127,728 m²

The solar PV potential in the forests of UMPSA Pekan on the basis of scenarios as depicted in Fig. 8 used different solar PV technologies. Table 4 compares three scenarios (Case I, Case II, and Case III) with varying coverage percentages (60%, 40%, and 80%) and three types of solar panels (polycrystalline, monocrystalline, and amorphous thin film). The capacity ranges from 5.11 to 12.77 MW, indicating the amount of solar energy that can be generated based on the specific scenario and solar panel type. Case III with monocrystalline solar panels consistently shows the highest potential capacity of 12.77 MW, while Case II with amorphous thin film solar panels has the lowest capacity at 4.26 MW. The optimum scenario among the three cases is Case I, with 60% coverage using polycrystalline panels, resulting in a capacity of 7.66 MW. Potential energy generation for these scenarios ranges from 6713.38 to 8954.48 MW. Again, Case III with monocrystalline solar panels shows the highest potential energy generation, while Case II with amorphous thin film panels shows the lowest. The optimal scenario, Case I with 60% polycrystalline panels, yields an energy generation of 7.66 MW.

Based on Helioscope software, the floatovoltaic potential of the UMPSA Pekan campus is estimated. Table 5 showcases the viable opportunity for solar PV systems to be installed on the lakes of UMPSA Pekan. At the same time, the total potential capacity can be optimized based on the various parameters.

Potential Floatovoltaics Capacity with Different Generations of Solar Panels

The quantity of solar energy that can be produced in a given location, including the base area, is referred to as the prospective solar capacity related to that base area. Solar capacity is calculated using data on solar irradiation, installed capacity, and available area. In this instance, the base area can be used to determine the potential solar capacity. Specifically:

10 m² of polycrystalline material can yield 1 kilowatt (kW) of power.

Total Area = 323,064.2 m²

Fig. 9 and Table 6 illustrate the potential of floating solar installations at UMPSA Pekan’s Lake. The total available surface area is 3,230,64.2 square meters. The tables analyze potential solar capacity (in MW) across three scenarios (Case I, Case II, and Case III) with varying land use percentages (60%, 40%, and 80%) and three solar panel types (polycrystalline, monocrystalline, and amorphous thin film). The potential ranges from 12.9 to 32.3 MW. As expected, potential capacity increases with higher scenario percentages (more land use) for all panel types. Both polycrystalline and monocrystalline panels consistently outperform amorphous thin film in terms of potential capacity across all scenarios. Considering the objective of maximizing solar generation, Case III (80% land use) with monocrystalline panels emerges as the most suitable option. This scenario boasts the highest potential capacity at 32.3 MW. Overall, the analysis suggests that maximizing land use (Case III) with monocrystalline panels offers the most promising approach for floatovoltaics at UMPSA Pekan’s lake. Table 7 presents the potential energy generation for the three scenarios (Case I, Case II, and Case III) with different coverage percentages (60%, 40%, and 80%) and the three types of solar panels. The annual energy yield ranges from 11,321.42 to 45,271.68 MWh. Case III with monocrystalline panels consistently shows the highest energy generation of 45,271 MWh, while Case II with amorphous thin film panels consistently has the lowest energy generation.

Based on the Helioscope simulation, the potential for Building Applied Photovoltaics (BAPV) is estimated since the side view of the buildings is not available in Google Earth. The solar potential of the buildings is studied from the top view, excluding the façades and windows. Table 8 highlights the viable opportunities for installing solar PV systems on various buildings, including the chancery, Faculty of Mechanical and Automotive Engineering Technology (FTKMA), Faculty of Manufacturing and Mechanical Engineering Technology (FTKPM), Faculty of Electrical and Electronics Engineering Technology (FTKEE), Faculty of Computing (FC), the student activities center, and the male and female residential colleges. The total potential capacity can be optimized based on various parameters.

Potential of Buildings Solar Capacity (MW)

Total Area = 85,359.2 m²

Case III consistently shows the highest potential capacity across all panel types, as shown in Table 9. The potential of solar pv capacity on buildings using different PV panels is illustrated in Fig. 10. Among the solar panel options, monocrystalline panels consistently exhibit the highest potential capacity, followed by polycrystalline and amorphous thin film panels. Therefore, considering the highest possible capacity and the performance of different solar panel types, Case III with monocrystalline panels appears to be the most suitable choice for maximizing solar energy generation in forested areas. The potential energy generation in Building Applied Photovoltaics (BAPV) is presented in Table 10 for three scenarios (Case I, Case II, and Case III) with different coverage percentages (60%, 40%, and 80%) and three types of solar panels (polycrystalline, monocrystalline, and amorphous thin film). The energy generation figures range from 2990.97 to 11,963.91 MWh. Comparing the scenarios, Case III with monocrystalline solar panels consistently shows the highest energy generation of 11,963.91 MWh. In contrast, Case II with amorphous thin film solar panels consistently has the lowest energy generation.

The annual savings provide information on the FiT rate (RM/kWh) for different installed capacities of renewable energy installations in Malaysia, along with the effective and yearly period rates. The FiT rate in Table 11 represents the tariff rate at which the utility company purchases electricity generated from renewable energy sources. By multiplying the annual energy generation by the FiT rate, the formula calculates the amount of money that can be saved annually by selling renewable energy to the grid.

The effective period mentioned in a table related to solar PV installations typically refers to the duration over which the savings or benefits from the installation are calculated or realized. The effective period determines the time it takes to recover the initial investment in the renewable energy installation through savings on energy costs. A longer effective period allows for more time to recoup the upfront investment, potentially resulting in greater overall savings. The effective period impacts financial metrics such as the payback period, return on investment (ROI), and net present value (NPV). A longer effective period may result in a shorter payback period and a higher ROI, indicating a more financially attractive investment. The effective period should align with the expected lifespan of the installed renewable energy technology. For example, solar panels typically have a lifespan of 25 years or more. Extending the effective period beyond the technology’s lifespan may overstate potential savings. Changes in policies, regulations, incentives, and tariffs can impact the financial viability of renewable energy installations. The effective period should account for potential changes in the regulatory environment and their effects on savings over time.

CO₂ Emission from PV Plant:

Unlike fossil fuel-based power plants, PV plants do not directly emit carbon dioxide (CO₂) during their operation. In trials, PV systems emitting 30–317 g/kWh of CO₂ yielded associated energy [37]. This is because they utilize a clean and renewable energy source, the sun, to produce electricity. However, it’s essential to consider the entire life cycle of a PV plant, including the production of solar panels, their installation, maintenance, and eventual decommissioning. CO₂ emissions associated with a PV plant mainly arise from the energy-intensive manufacturing processes of solar panels, transportation, and construction activities. Based on the Tables 15–17 below, it is evident that CO₂ emissions generally increase with higher scenario percentages. In terms of panel types, both polycrystalline and monocrystalline panels have higher emissions compared to amorphous thin film panels across all scenarios. Considering the goal of minimizing CO₂ emissions in the case of forest photovoltaics, Case II with a 40% scenario for amorphous thin film appears to be the most suitable choice with 179.01 tCO₂ emissions. Similarly, CO₂ emissions generally increase as the scenario percentage increases. Among panel types, both polycrystalline and monocrystalline panels exhibit higher emissions than amorphous thin film panels across all scenarios. Considering the objective of minimizing CO₂ emissions, Case II with a 40% scenario for Amorphous Thin Film stands out as the most suitable choice, with the lowest emissions for all panel types totaling 452.85 tCO₂. Upon comparing the data, it is observed that CO₂ emissions generally increase as the scenario percentage rises. Considering the goal of minimizing CO₂ emissions, Case II with a 40% scenario for amorphous thin film appears to be the most suitable choice, as it has relatively lower emissions for all panel types, totaling 119.63 tCO₂.

Net CO₂ Reduction:

It is noticeable that the reduction of CO₂ emissions generally increases as the scenario percentage rises for all panel types. Among the panel technologies as indicated in Tables 18–20 both polycrystalline and monocrystalline panels exhibit higher CO₂ emissions reductions than amorphous thin film panels across all scenarios. For instance, in terms of floating solar capacity, the highest value of CO₂ emission reduction is 29,834.04 tCO₂ from Case III (80%) for monocrystalline solar panels. Similarly, for forest photovoltaics, the highest value for net CO₂ emission reduction is observed in monocrystalline panels. Considering the goal of minimizing CO₂ emissions, the Case II (40%) scenario of amorphous thin film (7460.816 tCO₂) appears to be the most suitable choice as it demonstrates relatively lower emissions for all panel types. To summarize, among the panel types, both polycrystalline and monocrystalline panels exhibit higher CO₂ emissions reductions compared to amorphous thin film panels across all scenarios. Considering the goal of minimizing CO₂ emissions, the Amorphous Thin Film Case II (40%) scenario appears to be the most suitable choice, as it demonstrates relatively lower emissions for all panel types. Moreover, in the case of floating solar capacity, the highest net CO₂ emission reduction value is 29,834.04 tCO₂ from Case III (80%) with monocrystalline solar panels.

The theoretical potential of solar capacity is depicted in Tables 21 and 22, showcasing solar capacity in megawatts (MW) for different scenarios. These scenarios include floating (323.06 MW), forests (12.77 MW), and buildings (8.54 MW), all utilizing monocrystalline solar panels in Case III (80%). Moving on to annual savings, the highest value is attributed to monocrystalline solar panels in Case III (80%). For the floating scenario, annual savings amount to RM 18,842.07 * 10³, while for the forest and building scenarios, the values are RM 37,268.55 * 10³ and RM 7418.82 * 10³, respectively. However, CO₂ emissions from PV plants are at their lowest for all scenarios, specifically with amorphous thin-film solar panels in Case II (40%). The floating scenario emits 452.86 tCO₂, while forest and building scenarios emit 179.01 tCO₂ and 119.64 tCO₂, respectively. Similarly, net CO₂ emissions reductions follow the same pattern. For the floating, forest, and building scenarios, net CO₂ emissions reductions are 7460.82 tCO₂, 2950.61 tCO₂, and 119.64 tCO₂, respectively, with the use of amorphous thin film solar panels. In Table 23, a polycrystalline solar panel with a scenario of Case I (60%) is utilized across all three scenarios. Here is a breakdown of the results:

Floating Scenario: This scenario exhibits the highest potential solar capacity of 19.38 MW and the highest annual savings of RM 10,600.76 * 10³. However, it also records the highest CO₂ emissions from the floating PV plant, totalling 1018.81 tCO₂. Despite this, it achieves the highest net CO₂ emissions reduction of 16,784.97 tCO₂.

Forest Scenario: With a potential solar capacity of 7.66 MW, this scenario has the lowest among the three. Its annual savings amount to RM 4191.16 * 10³. However, it registers the highest CO₂ emissions from the forests, totalling 402.80 tCO₂. Interestingly, it also shows the lowest net CO₂ emissions reduction at 6636.18 tCO₂.

Building Scenario: Here, the potential solar capacity is the lowest at 5.12 MW, with annual savings of RM 4173.08 * 10³. CO₂ emissions from the PV plant in this scenario amount to 269.19 tCO₂, and the net CO₂ emissions also stand at 269.19 tCO₂.

These results highlight the varying outcomes across different scenarios, with the floating scenario demonstrating both the highest potential solar capacity and annual savings but also the highest CO₂ emissions. On the other hand, the forest scenario exhibits the lowest potential solar capacity but also the highest CO₂ emissions from the forests. The building scenario, while having the lowest potential solar capacity, presents relatively lower CO₂ emissions compared to the other scenarios.