Environmental analysis and comparison of the conventional and fractal glass textured surface photovoltaic panels

Abstract

There are two major forms of solar energy that are typically utilized: photovoltaic and concentrated applications. The application of fractal glass texture to photovoltaic solar panels is a cutting-edge technique in the field of solar panels that generate electricity from exposure to light. When it comes to studying the environmental implications of a product during its development and commercialization, the life cycle assessment (LCA) approach is an excellent technique that can be utilized. The purpose of this study is to offer a thorough understanding of the product’s effects on the environment by taking into consideration a wide range of criteria, including environmental, economic, and other evaluations. Through the utilization of the life cycle assessment (LCA) methodology and the SimaPro software, this paper presents a comparative analysis of conventional solar panels and fractal glass texture panels. During the course of this research, 18 midpoint indicators and three endpoint indices were investigated. In addition, a sensitivity analysis has been carried out on the fractal property of the panel in order to evaluate the impact that it has on environmental impacts and damages. For the purpose of this study, three distinct levels of fractal coating were applied to the panel surface: one percent, three percent, and five percent. As a result of the data, it was determined that the “Photovoltaic cell single-Si wafer” and the “Transport, freight, sea, transoceanic tanker” had the most significant impact on the midpoint and endpoint indices for both panels, respectively. Furthermore, there is a direct association between the rise in fractal coating on panels and the reduction in environmental repercussions, approximately. This correlation exists because of several factors.

Introduction

There is a threat that fossil fuels and other non-renewable sources of energy may become extinct in the coming years (Zhu, 2023). Therefore, it is imperative that mankind obtains energy from renewable sources as soon as possible (Ejaz et al., 2021). In comparison to other types of energy sources, renewable energy has the qualities of being clean, renewable, inexhaustible, and widely distributed (Shabani et al., 2021). The use of renewable energy sources, such as solar, wind, tidal, and geothermal, is becoming increasingly important in the generation of electricity (Zhou et al., 2024). Solar energy accounts for a greater percentage of these sources, especially in the form of photovoltaic (PV) panels (Vaishak & Bhale, 2021). During the past few years, photovoltaic technology has improved in both efficiency and cost performance (Yu et al., 2021a). Based on data provided by the International Energy Agency (IEA), there were 103GW of installed photovoltaic power generation systems in 2018, and the cumulative installed capacity of photovoltaics exceeded 512.3GW in 2018 (Failed, 2023). About 29% of global power demand is derived from photovoltaics (Yu et al., 2021b). Moreover, IEA claims that the share of PVs will grow to 50% of the total renewable energy sources by 2024 (Gassar & Cha, 2021).

As a result of the progress in photovoltaic solar cell technology as well as a general assessment of the field, they can be divided into three categories as shown in Fig. 1 (Zahedi et al., 2022).

Fig. 1

PV technologies categories

In addition to the presented classification, there are other types of solar cell technologies on which many researches have been conducted. One of these technologies is the use of fractal glass texturing (Jain & Pitchumani, 2017; Kant et al., 2022). Textured glass is a possible means for reflection reduction of a photovoltaic module (Ghodusinejad et al., 2022a). By reducing reflection losses, texturing can increase the energy yield of the system as well as enhance convection and radiation losses and dissipate waste heat (Zhou et al., 2021). The use of fractal patterns in solar panels has been inspired by plants and the anatomy of leaves (Zhu et al., 2024). These patterns can enhance the optical, electrical, and thermal performance of panels as well as their esthetic appearance (Sim et al., 2020). A schematic of fractal patterns is presented in Fig. 2 (Roe et al., 2020).

Fig. 2

Fractal H-trees and bus bar patterns

The largest share of the solar cell market currently belongs to first-generation cells (refer to Fig. 1) and the rest of the technologies (including fractal glass textured surface) have not been widely commercialized. One of the main obstacles in this direction is the lack of confidence in the nature and extent of the environmental effects of these new technologies, which can be developed by conducting numerous studies.

On the other hand, one of the most critical foundations of modern societies is energy, which plays a prominent role in the advancement of nations (Bai et al., 2022). As a result of environmental and climate change, the world has faced several challenges since the end of the twentieth century, especially global warming and ozone layer erosion, air and water pollution, loss of ecological diversity, and scarcity of certain natural resources. Consequently, energy production processes are experiencing a crisis between urgent need and environmental preservation (Abdel-Basset et al., 2021; He et al., 2021).

Life cycle assessment (LCA) is considered an excellent tool to assess the environmental impact of renewable energy (Ahmad Ludin, et al., 2021). Analysis of a product or technology's life cycle helps determine its environmental impact from creation to disposal. Life cycle assessments of energy technologies are important because material and energy flows are often interwoven and emissions may vary during their life cycle (Fthenakis & Kim, 2011). During product development, LCA measures and analyzes energy consumption and environmental impact. In modern industrial environmental management, LCA means considering emissions and resources throughout the product's life cycle and production process (Ghodusinejad et al., 2022b). LCA efficiently analyzes the environmental, energy, material, and waste implications of a product, process, or economic activity (Zhu et al., 2019). Calculating material and energy flows using LCA is comprehensive and systematic. According to ISO 14040 and 14044, this flow structure can quantify emissions throughout a product or process's life cycle (ISO-14040, 2006; ISO-14044, 2006; Lima et al., 2021).

There is a piece of research conducted in the field of utilizing LCA method in the solar energy industry and PV panels. Ahmad Ludin et al. (Ahmad Ludin, et al., 2021) analyze three different types of solar photovoltaic including a rooftop on-grid, a rooftop off-grid, and a land mount on-grid solar farm from technical and economic feasibility viewpoints. They utilize some tools such as life cycle assessment (LCA) and life cycle cost assessment (LCCA) during their study. The scope of the study was cradle to grave and the locations were Malaysia, Thailand, and Indonesia since they have similar climate conditions. Constantino et al. (2018) assess the LCA of renewable power generation in the Brazilian northeast. The generation data of 10 plants totaling 1.1 MWp were reviewed over two years. Energy payback time, greenhouse gas emission rate, and emission payback time were estimated. Similar research in Brazil has been conducted by Schultz and Carvalho (2022).

Raugei et al. (2020) examine the effects of the building sector and question the energy and environmental benefits of integrating and conventionally implementing photovoltaic (PV) systems into the building compared to municipal utility supplies. Over their lifetimes, solar systems minimize a building's dependence on non-renewable resources more than grid mix systems. Based on hourly historical data for 2018, Raugei et al. (2021) present a detailed analysis of greenhouse gas emissions, cumulative demand for total and non-renewable primary energy, and energy return on investment for the domestic electricity grid mix in the U.S. state of California. The goal is to reach 80% of the renewable share in the energy basket by 2030. Yan et al. (2020) investigate the environmental and economic trade-offs of a distributed cooling, heating, and power system incorporating renewable energy and energy storage using parametric life cycle assessment. They also compare this strategy to centralized traditional energy generating. They use parametric life cycle assessment to compare the environmental and economic implications of different solar PV arrays and battery sizes. Parametric life cycle assessment produces more accurate emission consequences than conventional life cycle assessment due to hourly simulations and parametric models for system components.

Using LCA methodology and the EcoInvent database, (Faircloth et al., 2019) compare the environmental impacts of landfilling end-of-life crystalline silicon panels with those of two different recycling methods. It is possible to recover valuable metals within silicon-based solar panels through recycling rather than allowing them to be lost in landfills. When credits are applied to recycling methods for the avoided production of materials that are recovered from the panels, recycling PV panels is less environmentally harmful than landfilling. Other studies have been conducted on the topics of rooftop PV solar cells (Eskew et al., 2018; Tevis et al., 2019), floating solar power system (Cromratie Clemons et al., 2021), hybrid solar power system (Magrassi et al., 2019), and large-scale solar power plants (Phuang et al., 2022; Yang et al., 2022), which can be accessed in the references section.

Environmental assessments are a crucial requirement for the general adoption and commercialization of any new technology. The literature assessment clearly indicates that the majority of research studies have concentrated on the consistent pattern of surface texturing or a single performance quality. There is a lack of a thorough examination of the impact of multiscale asperity features on the environmental aspects during the whole lifespan of the glass panel. This article aims to compare commercialized solar panels (known as first-generation) with solar panels featuring fractal glass texture, which are a recent discovery in the area. The comparison will be made from an environmental standpoint, using the life cycle assessment (LCA) approach. A novel environmental computational model is created to calculate the 22 midway and 3 endpoint environmental impacts of the PV panel based on the fractal parameters. Furthermore, a sensitivity analysis is conducted to examine and explore the environmental impacts of the features associated with this novel glass texture.

In the following, the methods used, tools and data required to perform LCA are presented. The results of the research will then be analyzed in detail in order to provide an overview of the findings. In the conclusion section, a summary of the research conducted along with important achievements and suggestions for future research are presented in order to complete and expand the current research.

Methodology

According to ISO-14040 and ISO-14044 standards (ISO-14040, 2006; ISO-14044, 2006), as shown in Fig. 3, the LCA method is based on four main steps, which are described separately below.

Fig. 3

Stages of an LCA

Goal and scope definitions

Defining goal and scope are the first step of an LCA process. The goal contains the information about the objective of the study, the reasons, and the intended audience. The scope states some items such as the product system to be studied, the functional unit, the system boundary, assumptions and limitations, etc. (ISO-14040, 2006; ISO-14044, 2006).

The goal of current research is comparing the Environmental Impacts (EIs) of a conventional (i.e., first-generation) PV panel with a fractal glass texture one. The reasons of the study have been presented in previous section.

The scope of the study is shown in Fig. 4 (Zahedi et al., 2022). According to it, there are some types of the LCA based on the boundaries of system include cradle-to-grave, cradle-to-gate, gate-to-gate, gate-to-grave, and cradle-to-cradle. Due to the lack of data related to the disposal and recycling of fractal panels, this study is limited to LCA from cradle-to-gate. In addition, the functional unit for this study will be 1 kWh.

Fig. 4

The scope of the system with showing different types of LCA

Similar to any kind of research, there are some assumptions and limitations in the current study. The first one is neglecting the fact that the fractal glass textured PV panels are not commercial products up to now. The next one is that the manufacturer and consumers are located in China and Iran, respectively, and the sea transportation will be used (cargo ships). The last assumption is that there is no internal transportation in the origin and destination.

Inventory analysis

Life cycle inventory analysis (LCI) is the second stage of the LCA. LCI includes collecting all required data to calculate EIs such as the material data, the energy data, the transportation data, etc.

In this study, there are two products with similar manufacturing process. For the conventional PV panel, a commercial product called FU300P is considered, whose specifications are given in Tables 1 and 2 (Zahedi et al., 2022).

Table 1 The properties of the polycrystal panel (first-generation)

Table 2 The mass of each material to produce 1 kWh for conventional panel

An important property that differentiates fractal panels from conventional panels is the change in the amount of reflection of pleasant radiation. This feature, which is dependent on the fractality of the glass texture, can lead to a reduction in radiation reflection and, as a result, an improvement in panel performance parameters such as optical and electrical efficiency, production power and surface wetness (Kant & Pitchumani, 2022; Zhou et al., 2021).

Here, in order to model this feature, it is assumed that the anti-reflective process has been done on the surface of the panel, which is considered equal to 1% of the required surface of the panel in order to produce 1 kWh. Therefore, the mass of materials required for fractal panels is determined in Table 3.

Table 3 The mass of each material to produce 1 kWh for fractal panel

Impact assessment

Life cycle impact assessment (LCIA) is the next step of the LCA procedure. Among different methods, the ReCiPe 2016 is selected to utilize in this study (more details in Sect. "Computational method and software tool"). The ReCiPe 2016 approach initially converts the effects of natural resources and emissions of hazardous elements to eighteen midpoint effect classes. After that, three endpoint effect classes are exploited to aggregate the acquired results, containing (1) resource availability, (2) ecosystem diversity, and (3) human health. Ultimately, the last result is offered as a single score using a weighting method. According to different cultural perspectives, three weighting methods are utilized in the ReCiPe 2016 approach that the “average” version, as the more moderate method, is principally applied. In the mentioned version, the shares of resource availability, ecosystem diversity and human health in the final score are 20, 40 and 40%, respectively. Notably, the final score is dimensionless that anyway ‘‘point’’ (Pt) is the name used for dimension of this score (Dehghani et al., 2020).

Interpretation

The last phase of an LCA is interpretation which means to identify significant issues, evaluate the results from LCI and LCIA phases by checking completeness, sensitivity, consistency, and others, and conclude general findings (ISO-14040, 2006; ISO-14044, 2006). The outputs of this phase may affect all of the LCA process and may lead to modify somethings in previous phases.

Computational method and software tool

As the use of LCA directly requires a time-consuming, complex, and costly process, the ReCiPe 2016 method embedded in the SimaPro software tool is used here to evaluate the EIs. It is a comprehensive tool that utilizes the latest science-based databases and methods in order to extract, scrutinize, and evaluate the environmental impact of a variety of products and services in a variety of industries (Dehghani et al., 2020).

A variety of methods are available in SimaPro 9 for estimating the magnitude of potential EIs, including CML2001, EPS 2000, IMPACT 2002 + , Eco-indicator 99, and ReCiPe 2016. Among the existing approaches, the ReCiPe 2016 approach is applied here due to the following characteristics. This method has been developed on the basis of both the Eco-indicator 99 and CML2001 methods, therefore it provides both advantages. Furthermore, this method encompasses the latest advances in environmental sciences as it is one of the most current and up-to-date methods. As a third advantage, the method utilizes both mid- and end-point effects to assess EIs. Fourthly, it is an inclusive EI assessment method that adequately covers a significant portion of existing mid- and end-point effects (Dehghani et al., 2020).

Results and discussion

The subsequent sections present a summary of the outcomes derived from the LCA analysis. The first section presents the results of the midpoint indicator for both the first-generation and fractal solar panels. The second section presents the results of the endpoint indicator for both types of panels. The final portion of the study examines the perspectives of the EIs and compares conventional panels with fractal panels. Ultimately, a sensitivity analysis is conducted on fractal panels to assess the impact of an anti-reflection coating on specific midpoint and endpoint indicators.

Conventional panel results

Figure 5 presents the midpoint indices for typical solar panels, categorized into 18 unique groups. When considering the diagram as a whole, it becomes apparent that the solar cell single-Si wafer and metallization paste, back side inputs have the most significant impact. Furthermore, the impact of transportation on environmental indicators is minimal, if not completely insignificant. The a-Si photovoltaic panel has a significant effect on the measures of ionizing radiation and the potential for causing cancer in humans. In addition, the reliance on fossil fuels for energy generation in Iran means that the shortage of these resources is more greatly affected by electricity production compared to other electrical businesses. Furthermore, it is worth noting that panel glass, which should be distinguished from fractal panels, significantly contributes to the depletion of the ozone layer and the acidification of the atmosphere. Table 4 displays the greatest and least notable impacts for each EI. For more details, please refer to the table.

Fig. 5

The results of midpoint indicators for conventional panel

Table 4 The maximum and minimum effect on midpoint EIs for conventional panel

By grouping the midpoint indices into three categories, we obtain the chart of the endpoint indices, which is shown in Fig. 6 for conventional solar panels. Transport has a negligible impact relative to the other factors in all three endpoint indicators, similar to the midpoint indicators. Furthermore, it appears that the a-Si photovoltaic panel makes a significant 20% contribution to the indicators of human health, ecosystems, and resources. The single-Si wafer of the photovoltaic cell has the most significant influence on all metrics, particularly the ecosystem’s index, compared to other factors. Furthermore, metallization, panel glass, and electricity have made distinct contributions to each of the indices, with the greatest impact observed in human health, followed by human health and resources, respectively.

Fig. 6

The results of endpoint indicators for conventional panel

Fractal panel results

The midpoint indices for fractal patterned glass solar panels are provided in Fig. 7. These indices are broken down into 18 distinct groups. This chart, much to the one that was presented in the preceding section, provides information regarding the impact that each input has on EIs expressed as a percentage change. Figures 5 and 7 are distinct from one another due to the inclusion of a new entry that is referred to as anti-reflection-coating. This new entry, on the other hand, did not have any statistically significant influence on any of the midpoint indicators. It is for this reason that the single-Si wafer photovoltaic cell continues to provide a substantial contribution to all EIs. Additionally, the inputs of photovoltaic panels with a-Si and metallization had varying effects on many indicators, the majority of which were in the areas of human carcinogenic toxicity and mineral resource scarcity, respectively. On the other hand, electricity has the biggest proportion in the fossil resource scarcity index, as was said in the part before this one. This is because the methods that are used to produce electricity in Iran are frequently reliant on fossil resources. As is the case with anti-reflection coating, transport has a relatively minor portion of EIs. The results of using panel glass are extremely similar to those of using conventional glass. The most and least significant effects for each EI are shown in Table 5, which can be accessed for further information.

Fig. 7

The results of midpoint indicators for fractal panel

Table 5 The maximum and minimum effect on midpoint EIs for fractal panel

By grouping the midpoint indices into three categories, we obtain the chart of the endpoint indices, which is shown in Fig. 8 for fractal textured glass solar panels. The photovoltaic panel made of amorphous silicon (a-Si) exhibits approximately one-fifth of the efficiency in each of the endpoint indicators. Furthermore, the photovoltaic cell single-Si wafer dominates the human health, ecosystems, and resources indices, accounting for over 40% in each category. The influence of metallization and panel glass on the human health index was greater than that of other factors. In contrast, electricity had a larger proportion of resources in comparison to others. Consistent with expectations and the findings of the midway indicators, the sectors of transport and anti-reflection-coating have demonstrated the least impact on the endpoint indicators.

Fig. 8

The results of endpoint indicators for fractal panel

Comparison between conventional and fractal panels

The results of this section, which includes a comparison between midpoint and endpoint environmental indicators between two products, conventional solar panels, and fractal glass texture solar panels, is one of the main outputs of this research. The outcomes are presented in Tables 6 and 7. Based on ReCiPe 2016 method available in SimaPro software, the units are determined based on the results.

Table 6 Impact assessment comparison

Table 7 Damage assessment comparison

According to Table 6, all of the midpoint indicators in the fractal panels have improved. This is the case in the basic case with 1% anti-reflection coating. Despite the fact that the changes are quite little, several indices have undergone varying degrees of improvement. The categories of terrestrial ecotoxicity and land use effect have experienced the most and least amount of improvement, respectively.

There has been a decline in the values of the endpoint indices, and these changes are more for human health than they are for the other damage categories, as indicated by the last column in Table 7, which displays the relative difference.

Sensitivity analysis results

A sensitivity study has been carried out in this section in order to determine whether or not there is a connection between the fractalness of the panel and the increase in the number of EIs present. Among the categories of impacts, five indicators have been chosen, and the LCA process has been carried out with the assistance of SimaPro software. The findings are shown in Fig. 9, and they were obtained by adjusting the amount of anti-reflection coating from 1 to 3% and then to 5%. In addition, a process that is parallel to this one has been carried out for the various categories of damages, and the results of this process are shown in Fig. 10. In order to normalize the charts, the maximum value that is associated with the base state data (that is, 1% anti-reflection coating) is utilized.

Fig. 9

Selected impact categories sensitivity analysis

Fig. 10

Damage categories sensitivity analysis

Both types provide outcomes that are comparable to one another. There is a reduction in environmental effects and damages that occur as a result of raising the fractality of panels, which is comparable to increasing the proportion of anti-reflection coating. Moreover, it appears that there is a linear link between the rise in coating (%) and the decrease in EIs. This is something that can be observed.

Conclusion

The environmental aspect, encompassing the consequences and harms caused, is a crucial component of any energy system or new technology. This aspect can be examined from multiple viewpoints. Life cycle assessment (LCA) is a method that has attracted significant scholarly attention in recent years due to its high level of efficacy. This research aims to present a thorough environmental analysis of a novel technology called fractal glass texture panels in the photovoltaic solar panel industry. In addition, a comparison was conducted between this technology and the fully commercialized version of these panels, commonly known as first-generation or conventional panels. Furthermore, a sensitivity analysis was conducted to ascertain the impact of fractal features on EIs. The most important results are:

• Using fractal glass texture reduces all environmental impacts and damages,

• Metallization paste and photovoltaic cell single-Si wafer have the most share in the EIs,

• There is an almost linear relationship between the fractal feature of the panel and the reduction of EIs.

Similar to any other research publications, this effort likewise encounters constraints and challenges. An initial significant obstacle was the inadequate availability of ample experimental and laboratory data for the latest iteration of solar panels. As a result, it became impossible to conduct a thorough examination of panel performance metrics, such as efficiency and production power, and make comparisons with previous generations and models of solar panels. Another constraint is to the study’s exclusive focus on a certain phase of the solar panel’s life cycle.

To ensure the successful completion of this research, it is recommended that a thorough environmental analysis be conducted, taking into account the entire life cycle of the technology (from creation to disposal), in order to uncover all the practical aspects of its development. Furthermore, performing economic and sociological analyses can serve as valuable complements to the current study and facilitate the commercialization of fractal glass texture panels.