Economics of Snow Accumulation on Photovoltaic Modules

Abstract

The growth in photovoltaic (PV) module installations over the past decade has prompted a critical need to examine the economic implications of snow accumulation on solar energy production. The aim of this study is to quantify the economic impact of snow accumulation on PV modules in different regions and environmental conditions and to identify effective mitigation strategies for enhancing power generation efficiency and reliability of PV systems. It was found that snow accumulation on PV modules can lead to annual losses of 1% to 12% depending on the environmental conditions and geographic location. A financial analysis related to maintenance costs associated with snow accumulation on PV modules is also presented. A two-fold methodology of quantitative data analysis and interviews conducted with PV system operators is used for this purpose. In addition, the extent of snow accumulation financial losses in the U.S. is categorized based on the snowfall amount and solar market segment, suggesting an annual loss of at least USD 313M in utility and residential solar sectors. Furthermore, various currently employed active and passive snow mitigation strategies are presented in detail, describing their shortcomings and advantages. Finally, prospects on the need for developing reliable and cost-effective snow mitigation strategies for solar panels are discussed, paving the path for future studies.

1. Introduction

Photovoltaic (PV) technologies have attracted substantial interest and investment from various industries and government agencies, giving rise to their worldwide utilization. The global solar power market size was USD 163.7 billion in 2023 [1]. The PV installation capacity in the U.S. grew from 1 gigawatt (GW) to 15 GW between 2010 and 2022 (Figure 1). By the end of September 2019, the U.S. had installed over 2 million solar PV systems, totaling about 71 GW of solar capacity, and generating over 100 terawatt-hours (TWh) of electricity [2]. The trend in installing solar panels has been exponentially increasing in the past 5 years. In 2021, the solar market reached 100 GW of installed capacity in the U.S., and the net solar PV energy generation was ∼161 TWh [3]. The last reported U.S. solar capacity was 140 GW in early 2023 [4]. On a global level, more than 135 GW of new PV deployment capacity was installed in 2020 alone [5], increasing to 295 GW in 2022 [6].

To enhance the resilience and operational efficiency of these installations, particularly in regions susceptible to heavy snowfall, robust design solutions have been developed. These solutions focus on ensuring mechanical durability under significant snow loads [7], incorporating structural reinforcements [8], panel tilt configurations [9,10,11], and the use of materials adapted to withstand low temperatures and high mechanical stress. For example, as discussed by Papargyri et al. [12] and further supported by the research of Sahu et al. [13] on bimodal HDPE, optimizing material properties significantly improves the mechanical strength and stress tolerance of PV modules under varying environmental loads, including floating solar systems. Such design innovations are critical for preventing physical damage to the panels and maintaining consistent energy output during the winter months. However, it is important to acknowledge that despite these advancements, the solutions may not be entirely sufficient for managing the challenges posed by extremely heavy snowfalls. In regions where snow accumulations can reach several feet, even the most robustly designed PV systems may experience damage and operational disruptions. The sheer volume and weight of the snow can exceed typical design specifications for load handling, potentially leading to mechanical failures in addition to reduced energy output. Therefore, further research and development of more advanced technologies and snow mitigation strategies are necessary to fully address the impacts of severe winter conditions on the operation of solar energy systems.

Considering the growing trend in PV installation, many experimental and numerical investigations have been performed to predict energy losses due to snow accumulation on PV modules. Figure 2 shows various scenarios of snow covering PV modules, aiming to develop passive and/or active snow mitigation strategies [14]. The extent of the reduction in energy generation depends on snow characteristics (i.e., thickness, density, weight, and wetness), weather conditions (i.e., ambient temperature, wind velocity, and sun light), and module characteristics (i.e., orientation, tilt angle geometry, and frameless vs. framed structure). Andrews et al. [15,16] conducted research on the impact of snow on yearly yield losses for two types of solar modules (crystalline and amorphous) at different module angles (10°, 20°, 40°, and 60°) in Truckee, California. Their findings revealed that the yearly yield loss varied, with percentages of 4.4%, 3.5%, 3.5%, and 2.9% observed for module angles of 10°, 20°, 40°, and 60°, respectively. In a separate study, Marion et al. [17] utilized both numerical simulations and experimental methods to examine the monthly energy losses caused by snow accumulation on PV modules in areas of Colorado and Wisconsin. They reported that these losses could be as high as 90% during snowy seasons. Townsend and Powers investigated the snow-related energy losses of PV modules at various inclinations in California. They found that the monthly losses could reach up to 80%, 90%, and 100% of the expected yield for modules placed at 39°, 24°, and 0°, respectively. Overall, annual losses in energy generation due to snow have generally ranged from 1% to 12%.

To examine various aspects of snow accumulation issues on solar panels, extensive interviews were conducted with utility companies that own assets in snowy regions. For example, an interview with a solar company in Milwaukee, Wisconsin, revealed a substantial reduction in energy generation due to snow (Figure 3). At one site, during the month of January, a 135 kilowatt (kW) capacity solar plant produced approximately 6 megawatt-hours (MWh) (Figure 3), which increased to 7 MWh in February, and further rose to 11 MWh in December. Conversely, in July, the solar plant generated around 40 MWh, indicating a six-times increase when compared to January. This difference is significantly beyond the differences in sunlight conditions in summer vs. winter months.

Another example is in Boston, MA; when snowstorms occur early in winter, PV modules with less than 30-degree tilt angles remain covered with snow throughout the entire season, resulting in zero energy generation for months. A solar site with 2000 PV modules experienced annual energy production losses of 137 MWh, equivalent to USD 44,000 in 2021. This translates to a revenue loss of USD 22 per module per year. In New Jersey, wet snow posed significant challenges, particularly after drops in ambient temperature, creating an ice layer between the snow and the module’s surface. This ice layer led to snow coverage of the panels for weeks. In Ontario, Canada, snow remained on modules for weeks at subzero temperatures.

Older systems with single inverters were particularly affected, while newer systems with multiple inverters demonstrated reduced snow losses. A utility-scale solar company with sites in Japan, Ontario, and New York experienced annual snow losses of 5%. Fifteen of their sites encountered complete losses for a few days, and one site in northern Japan suffered 97% losses only in January. In Idaho, PV modules experienced months of no energy production due to snow coverage, while in Wisconsin, the freezing of wet snow overnight resulted in a month-long coverage of the modules. Annual snow losses ranged from 3% in southern Wisconsin to 5% in the north. In Alberta, Canada, snow losses varied between 2% and 5% annually. In Indianapolis, where snow accumulation on PV modules was generally not a significant issue, snow accumulation took five days to melt from the PV modules in 2019. In Minnesota, a solar site with 4800 PV modules encountered annual snow losses of 256 MWh in 2021, amounting to USD 35,500 (which translates to ∼USD 7.4 per module per year) due to snow accumulation in 2021. This means an annual loss of ∼23.3 kilowatt-hours (kWh) per panel, or approximately 8.26%, due to snow coverage. Such data are crucial to understanding the broader impact of seasonal variations on solar energy production.

In addition to interviews with operators of utility-scale solar companies, simulations were conducted using a System Advisor Model (SAM) [18] to assess energy generation losses due to snow accumulation on solar panels. JA solar PV modules with a capacity of 200 watts (W) were installed with a tilt angle of 25 degrees facing the south at an outdoor facility in Toledo, Ohio. Weather data of the exact location of the PV modules were downloaded using the “NSRDB” database provided by SAM. A Kinko Solar Co 240 W inverter was entered into SAM using the inverter CEC database. Snow events (accumulation followed by subsequent natural removal) were monitored by a Tilt IP camera (purchased from FDT). Over a period of four months, a total of 600 h of snow coverage was recorded.

By analyzing the recorded videos, the precise duration of snow cover was determined and entered in the SAM to quantify the hours of snow losses for each day during the winter season. This was achieved by creating a SunEye hourly shading file, where hours of snow cover were entered into the file for each day and hour during the winter season. Subsequently, the annual energy generation of modules unaffected by snow accumulation (no shading data were entered) was compared to that of those modules that experienced snow throughout the winter season, utilizing the SAM. The analysis revealed that a module without any snow coverage would generate 449 kWh annually, while a module exposed to natural snow events during the 2021/2022 season yielded 428 kWh energy generation. This translates to an annual loss of 4.7% in Toledo, Ohio, which is considered a region that does not experience heavy snowfall. Similarly, simulations were performed for the 2020/2021 winter season, yielding an annual energy generation of 425 kWh for a module that experienced natural snowfall. This translates to an annual energy generation reduction of 5.3%.

For U.S. states that experience at least 10 inches of annual snowfall [19], the total energy generated in 2021 in the utility-scale sector was 29,803 gigawatt-hours (GWh). We estimated this to be valued at around USD 4.9 billion using the value of electricity in each state. Our comprehensive interviews with solar companies operating in snowy states in the U.S. revealed an annual loss of 2–5%. With an average of 3.5% annual loss in energy generation due to snow, around USD 160M in revenue was lost in the U.S. utility solar sector alone in 2021, and this is predicted to be ∼USD 200M in 2023. These results underscore the critical impact of snow accumulation on the operational efficiency and economic viability of solar power installations across varied geographic landscapes, emphasizing the need for enhanced predictive models and effective snow mitigation strategies in future solar project planning and development.

Methodology

To thoroughly investigate these issues, this study employs a two-fold approach: (a) integrating quantitative data from energy outputs and weather conditions, and (b) qualitative insights obtained through interviews conducted with solar facility operators. This two-fold approach of combining data-driven analysis and real-world observations/experiences provides a robust framework for understanding the economic impacts of snow accumulation on solar panels.

The remainder of this paper is organized as follows. The ‘Maintenance and Repair Costs’ section examines the financial implications of snow accumulation on PV modules, detailing the direct costs associated with snow removal and the broader economic impacts of maintenance and repairs. ‘Magnitude of Snow Issues in Various U.S. States’ provides a geographic analysis of snow-related energy losses, demonstrating the variable impact across different regions. The subsequent section, ‘Snow Mitigation Methods’, evaluates both traditional and innovative strategies employed to mitigate the effects of snow on solar panels, assessing their effectiveness and cost-efficiency. ‘Bifacial Modules’ explores the advantages and limitations of using bifacial PV modules as a solution to reduce snow-related losses. ‘Future Prospects and Need for Passive Snow Removal Mechanisms’ discusses the development and integration of passive snow removal technologies, such as coatings and surface treatments, highlighting their potential benefits and limitations. The final section, ‘Conclusions’, summarizes the key findings of the study, reflects on the economic impact of snow on PV systems, and calls for further research into efficient snow mitigation strategies. Each section builds on the next, culminating in a comprehensive understanding of the economic and operational challenges posed by snow accumulation on photovoltaic systems and highlighting potential areas for future research and technological advancement.

2. Maintenance and Repair Cost Associated with Snow Accumulation on PV Modules

Snow exerts excessive and non-uniform stress on PV modules, cells, and systems, with uncertain long-term effects. The presence of heavy snow on PV modules can lead to mechanical and structural damage (Figure 4), necessitating maintenance, repairs, and, in severe cases, module replacements. In regions that experience heavy snowfall (over 40 inches annually), the snow load can be somewhere from 260 kg to 450 kg on a 1 × 2 ${\mathrm{m}}^2$ standard PV module annually (Table 1). This is assuming a relatively light snow with a density of 100 $\mathrm{kg}/{\mathrm{m}}^3$. Such loads cause reduction in the modules’ lifetime and require extensive maintenance work every year. Over the lifespan of a PV module (25 years), a total load of 6.5 tons to 11.25 tons can be applied on it due to snow. This load is equivalent to the weight of five F-150 pickup trucks.

Module replacements are particularly costly and can vary based on the module wattage and location, with an average cost of USD 1100 per module for materials and labor [20]. PV modules can range in material cost up to USD 1.5 per watt, with low-wattage modules (250 W) priced at up to USD 875 and high-wattage modules reaching up to USD 1400 for materials, labor, and maintenance. The cost breakdown of PV modules consists of 50% for materials, 25% for labor and permits, and 25% for maintenance and overhead expenses. The removal of a damaged PV module alone can amount to USD 600, in addition to an additional USD 350 for the new replacement module, adding up to a total of USD 950 [21]. Repairing a module can cost up to USD 700, with specific repairs such as fixing a cracked module or hail damage ranging from USD 150 to USD 500. Repairing broken glass of a PV module can reach up to USD 450.

For, residential solar systems, expenses on PV module repairs typically range between USD 200 and USD 1250, with an average hourly repair rate of USD 100 [22]. In the case of a 9 kW system, inspection costs alone can reach USD 325. Maintenance costs alone can reach up to USD 150, with additional expenses of approximately USD 135 sometimes incurred for electrician services [23].

Due to potential mechanical damages to PV modules due to snow accumulation and costs associated with that, some asset owners both in the residential and utility solar sectors use mechanical methods to remove snow from the modules. However, cleaning of PV modules generally costs between USD 10 and USD 20 per module. For a system consisting of 10 modules, maintenance costs can amount to up to USD 700, while inspection costs and materials account for USD 370 and USD 330, respectively.

3. Magnitude of Snow Issues in Various U.S. States

As discussed earlier, snow accumulation on solar panels results in an annual energy production loss of 2–5% on average. The magnitude of this loss is significantly higher in snowy regions of the U.S., where electricity prices tend to be elevated. The extent of these losses varies among states and is categorized into three groups based on their average annual snowfall: 12 states experience heavy snowfall (>40 inches, highlighted in red), 16 states have moderate snowfall (between 20 and 40 inches, highlighted in orange), and 8 states have light snowfall (between 10 and 20 inches, highlighted in yellow), as shown in Figure 5B. The occurrence of heavy snowfalls (Figure 5A) is particularly prominent in the vicinity of the Great Lakes, due to a phenomenon known as the lake effect, wherein very cold air passing over a relatively warmer body of water generates substantial snowstorms. These storms originate over the Great Lakes and traverse a considerable distance from Minnesota to Maine.

Furthermore, there is considerable variation in snowfall amounts within each state. For example, in Massachusetts, Cape Cod experiences an average of 23.8 inches of snow per winter, while the western half of the state receives an average of 77.1 inches. In Arizona, the southwestern corner, comprising the Sonoran Desert, sits at a slightly higher elevation than sea level, resulting in minimal snowfall, with occasional light snow accumulation of around an inch. However, at higher elevations, above 5000 feet, snowfall amounts can range from 6 inches to over 35 inches, depending on the specific location. California is generally considered a state with negligible snowfall, but the presence of the Sierra Nevada region in the northeast leads to substantial regional disparities. While most of the state receives minimal snowfall, the Sierra Nevada mountains experience hundreds of inches of snowfall annually, with Alpine County averaging 140.2 inches [19].

In Colorado, snowfall is almost certain throughout the state during winter, but the disparity in amount of snowfall based on the location is significant. The eastern flat half of the state typically witnesses 45–55 inches of snow accumulation, while the other side, comprising the western half, has a median snowfall of 126.4 inches and an average of 113.5 inches.

Similarly, Illinois’s northern half experiences double the amount of snowfall compared to its southern counterpart. Northern Illinois receives a median of 34.4 inches of snow per winter, while southern Illinois has a median of 11.2 inches. Indiana, which also borders the Great Lakes, exhibits a similar pattern, with the northern half receiving nearly triple the snowfall when compared to the southern half. Northern Illinois and the Chicago area have an average of 43.3 and 24.1 inches, respectively, while the southern half averages 15 inches per winter [19].

Maryland, being a state stretching from the Atlantic Ocean to the Appalachian Mountains, exhibits varying snowfall patterns. The coastal region experiences an average of 10.5 inches, whereas the western half of the state has an average snowfall of approximately 70 inches. Michigan demonstrates a similar trend, with the southeastern region averaging 42.3 inches, while the Upper Peninsula receives over 115 inches of snowfall on average, aligning with the lake effect phenomenon. Montana, like other large states, displays significant differences in snowfall amounts across its various regions. The eastern half experiences a median of 43.7 inches and an average of 57.1 inches, while the southern half of the center of the state witnesses a median of 141.9 inches and an average of 129.8 inches. The center of the state receives the most snowfall, with a median of 50.7 inches and an average of 44.2 inches. Situated within high desert terrain, New Mexico spans an elevation range of over 2000 to 13,000 feet. The northern half of the state experiences an average snowfall of nearly 40 inches, while the southern half receives an average of approximately 7.8 inches. In the state of New York, the southern coastal region, which encompasses New York City, experiences relatively low snowfall. However, as one moves towards the northern and western regions, there is a significant increase in snowfall. For instance, the coastal areas observe an average of less than 30 inches of snowfall during winter, whereas the regions immediately north and west receive double or triple that amount. The Adirondacks in New York witnesses the highest rate of snowfall within the state, with an average exceeding 126 inches.

Despite North Carolina not being renowned for severe or prolonged winters, there exist notable differences in snowfall between the northern and southern halves of the state. The mountainous areas, such as the Great Smoky Mountain National Park, typically experience over 10 inches of average snow accumulation throughout the winter, whereas coastal regions rarely encounter even an inch. Similarly, Ohio, like other states bordering the Great Lakes, undergoes a substantial variation in snowfall between the northern and southern regions. The southern half commonly witnesses less than 20 inches of snowfall during the entire winter, whereas the northern half experiences an average of 40.6 inches. Although Oregon is not geographically expansive, it exhibits considerable disparities in snowfall rates across its territory. Coastal areas have the least snow accumulation, averaging around one-tenth of an inch. In contrast, the eastern regions, characterized by an elevation exceeding 2000 feet, receive approximately 10 inches of snow throughout the winter. Moreover, the presence of the Cascade Mountain Range contributes to the central part of the state receiving an average snowfall of 89.3 inches and a median of 20 inches. Thus, while extremely heavy winters are possible, the typical snowfall total remains around 20 inches. Due to its unique composition of high desert and mountainous regions, Utah encounters substantial snowfall. While most areas of the state receive approximately 20 inches or less per winter, the north central region tends to receive over 100 inches in a single season. Virginia, akin to its neighboring state Maryland, exhibits geographical diversity, extending from the ocean to the mountains. Along the east coast, snowfall does not exceed 10 inches in a season, whereas mountainous regions commonly observe over 20 inches. Washington, similar to Oregon, displays notable variations in snowfall across its territory and includes sections of the Cascade Mountains. Coastal and island areas rarely experience more than 5 inches of snowfall in one season. In contrast, the eastern half of the state and mountainous regions receive on average approximately 37.4 and 51.1 inches of snow, respectively. The highly mountainous nature of West Virginia contributes to significant disparities in snowfall. Snow accumulation doubles from around 17 inches in the northwest region to over 30 inches in the southern portion. Furthermore, another doubling occurs from the southern to the eastern part of the state, where snowfall averages 70 inches per season. Wisconsin, like other states bordering the Great Lakes, encounters the "lake effect", which contributes to challenging winters in the Midwest. The eastern and southwest ends of the state receive an average snowfall of roughly 45 inches per season. However, sections bordering a lake witness substantially greater snow accumulation. For instance, areas along Lake Superior’s shore observe an average of 97.7 inches of snowfall in a season. Owing to its size, location, and elevation, Wyoming experiences rigorous and snowy winters. However, snowfall varies significantly within the state. The average snowfall in Wyoming ranges from 38 to 59 inches across the state, with the exception of a specific region. In the northwest corner of Wyoming’s geographical area, there is a distinct phenomenon where the snow accumulation exceeds 150 inches per season [19].

In snowy regions of the U.S., the total capacity of photovoltaic (PV) modules exceeds 42 GW, with approximately 70% of these modules belonging to the utility-scale sector [3]. In 2021, the total solar energy generation in the U.S. reached 161,500 gigawatt-hours (GWh), supported by a cumulative solar capacity of 100 gigawatts (GW). Assuming an average module wattage of 350 watts, the estimated number of PV modules in the U.S. amounted to approximately 286 million in 2021, which had increased to 400 million PV modules by the beginning of 2023.

To determine the distribution of modules across heavy-snowfall, moderate-snowfall, and light-snowfall states in both the utility-scale and residential sectors, an analysis was conducted, and is presented in Table 2, comparing the energy output of these modules to the total energy generated in 2021 (161,500 GWh). Based on the data obtained from “eia.gov”, around 6.9% of total utility-scale solar energy generation in the U.S. is in heavy-snow regions. This is around 11,200 GWh of electricity generation in 2021, which increased to 15,700 GWh in 2023 due to the increase in total solar capacity from 100 GW in 2021 to 140 GW in 2023. This implies that there is around 9.7 GW of utility-scale solar capacity in heavy-snow regions. Assuming an average wattage of 350 W per module, this means that the utility-scale sector in heavy-snow regions in the U.S. accounts for approximately 28 million PV modules. For the 28 million modules, the monetary value of their energy output is estimated to be around USD 2.5 billion. However, in the residential sector, the number of PV modules reduces significantly to around 10 million, resulting in an annual energy generation of approximately 5600 GWh, valued at around USD 1.1 billion. In this sector, an energy production loss of 196 GWh is predicted with an estimated monetary loss of USD 39M.

Similarly, around 4.4% of total utility-scale solar energy generation in the U.S. is in moderate-snow regions (annual snowfall of 20–40 inches). This was around 7200 GWh of electricity generation in 2021, reaching 10,100 GWh in 2023. This implies that there is around 6.1 GW utility-scale solar capacity in moderate-snow regions. Assuming an average wattage of 350 W per module, this means that the utility-scale sector in heavy-snow regions in the U.S. accounts for approximately 17 million PV modules, generating approximately USD 1.7 billion worth of electricity. Of the USD 1.7 billion-valued energy generation, these modules lose about 3.5% of that annually due to snow, which is valued at approximately USD 60 million, or 354 GWh. In the residential sector, the number of PV modules remains at around 10 million, generating approximately 5600 GWh of energy, valued at approximately USD 1 billion, where snow causes a 196 GWh reduction in energy generation, or USD 35 million of annual economic losses.

In light-snowfall regions, it is estimated that there are approximately 29 million utility-scale PV modules. These modules produce annual energy generation of approximately 16,000 GWh, reflecting an economic value of around USD 2.2 billion. Having said that, the influence of snowfall has been estimated to reduce the annual energy generated by around 560 GWh, resulting in economic losses amounting to approximately USD 77 million. In the residential sector, it has been approximated that the total number of PV modules is 6 million in states that experience light snowfall. These modules contribute to an annual energy generation of around 2900 GWh, with an estimated economic value of roughly USD 400 million. However, snow accumulation effects have been estimated to reduce this energy generation by approximately 102 GWh annually, leading to economic losses amounting to USD 14 million per year.

The value of the electricity generated was estimated by comparing the total energy generation with the average value of electricity in each respective state. These findings highlight the significant contribution of PV modules in snowy regions to the overall energy generation and their varying impact across utility-scale and residential sectors.

4. Snow Mitigation Methods

4.1. Tractors

To manually remove snow from PV modules, it is necessary to clear the snow-covered ground in front of the modules. In regions with heavy snowfall, utility-scale companies employ tractors (Figure 6A) to clear the ground as the accumulation of heavy snow can impede the sliding of snow from the modules, hindering labor access for manual removal. In some cases, even when temperatures rise above melting point, substantial snow can remain in front of the modules for weeks. This prevents snow gliding/sliding of the modules, leading to substantial mechanical stresses and loss in energy generation. The sole solution to this issue involves utilizing tractors to clear the ground, enabling manual labor to reach the modules and facilitating snow sliding of the modules onto the ground.

Tractors are significant investments, with a Kubota M6 tractor priced at USD 66,000 and a Kubota M7 tractor costing USD 109,000 [24]. Moreover, these tractors entail maintenance costs of up to USD 2.45 per hour and fuel costs of up to USD 7.25 per hour. If the tractor is purchased outright, the total cost of clearing snow for one hour would amount to approximately USD 32.5. However, if the tractor is financed through the manufacturer, this cost can increase to around USD 37.7 per hour.

For small residential and commercial solar installations featuring ground-mounted systems, the purchase or financing of tractors is often not economically justifiable. In such cases, when snow clearance becomes necessary, asset owners typically engage the services of snow clearing companies, incurring costs ranging from USD 30 for residential 4 kW systems, to USD 70 for commercial (up to 100 kW) systems per visit [25]. In regions experiencing heavy snowfall annually, asset owners may opt for seasonal contracts with snow clearing service companies, which can amount to costs ranging between USD 200 and USD 600 for systems up to 100 kW.

4.2. Manual Removal

The primary approach for mitigating snow accumulation on PV modules is through manual snow removal (Figure 6B). Nonetheless, this method is both expensive and inefficient. A 9-kilowatt (kW) PV system consisting of 25 panels necessitates a cost of up to USD 635 to hire professional cleaning services, equivalent to USD 25 per module. The typical expenses associated with labor for module cleaning range from USD 100 to USD 150 per hour [26]. Major utility-scale solar companies typically spend approximately USD 8 per module annually exclusively for snow cleaning purposes. Several companies provide snow cleaning services for PV modules, with costs varying depending on the location. For a PV system comprising of 25 modules in Indiana, the estimated total cost for snow cleaning is USD 261, with labor costs amounting to USD 237 and an additional allowance of USD 25 for snow removal equipment [27]. This cleaning cost could escalate to USD 286 in Ohio and potentially reach USD 291 in Minnesota, translating to USD 11.6 per panel or USD 33,260 per megawatt (MW) annually. These costs encompass the equipment delivery of materials of equipment, expenses to safeguard existing structures surrounding the PV modules, the time required for labor setup, and the actual duration of snow removal. Mechanical cleaning always involves humans operating in extreme weather conditions and risks of injuries. A single labor injury in the U.S. costs up to USD 50,000 per incident.

4.3. Heating

Various heating methods have been utilized to clear snow from PV modules [28,29,30,31,32]. Rahmatmand et al. [30] explored thermal heating through two distinct methods. The first method involved utilizing an electrical resistance heater placed on the module’s surface (Figure 6C). The second method entailed the reversal of current through the PV module to generate heat. However, their study revealed that heating alone is ineffective in complete snow removal from PV modules. This limited efficacy can be attributed to the presence of the module’s bottom frame, which impedes snow sliding off, as well as the formation of icicles at the lower part of the PV module.

A Norwegian technology company called "Innos" has developed a system that addresses these challenges by effectively melting snow from PV modules [31]. The system operates by introducing a current through a diode, which heats up the solar cells and subsequently melts the snow. It incorporates a control system that supplies power to the PV modules when they are fully covered with snow where the snow load reaches 75 kg/m² [32]. Reported results indicate that this system successfully melted 2 kg of snow per square meter within one hour.

However, one significant drawback of this system is its power consumption, where it has been reported that the melting energy for each module is 500 W [32], as solar system owners endeavor to minimize operational costs and avoid undue increases in power usage.

4.4. Solar Trackers

The utilization of solar trackers represents a contemporary approach to address the reduction in energy generation of photovoltaic (PV) modules caused by snow accumulation. Two distinct categories of trackers are commonly employed: single-axis and dual-axis trackers. Single-axis trackers enable the rotation of modules along a single axis, typically in a back-and-forth motion. In contrast, dual-axis trackers (Figure 6D) not only allow the panels to move back and forth but also possess the capability to rotate them both left and right. This flexibility empowers dual-axis trackers to extract the maximum solar power potential from a set of modules. Solar trackers tackle the snow issue through two primary mechanisms. Firstly, they optimize the energy generation of the modules throughout the day. Secondly, when snow accumulates on PV modules, trackers can rotate them to a steep angle, aiming to facilitate snow gliding from the modules. While tracking can theoretically help with snow removal, the transition of snow due to temperature gradients has the potential to form ice layers and icicles, adhering the snowpack strongly to the surface of the module that cannot slide off by tracking or tilting the module.

Most tracking systems optimize electricity generation by dynamically moving the modules to align with the sun’s position over the course of the day. This continuous adjustment ensures that the panels receive solar radiation at an optimal angle, maximizing their efficiency in converting sunlight into electricity. Solar trackers are predominantly employed in ground-mounted PV modules. The angle of incidence, which represents the angle at which sunlight interacts with the surface of a PV module, directly influences its ability to convert light into electricity. A narrower angle of incidence leads to higher energy production from the PV module. Solar trackers play a crucial role in reducing this angle by orienting the panels to directly face the sun, maximizing the perpendicular alignment between the modules and the incoming light.

There are notable advantages associated with the installation of solar tracking systems. Solar trackers generally increase the energy generation of PV modules by up to 35% for single-axis systems and up to 45% for dual-axis systems [33]. Additionally, solar trackers optimize land usage, enabling the highest density of PV module capacity per square unit. This means that the required area for a solar system can be minimized, resulting in a reduction in PV module expenses. In certain U.S. states, utilities may compensate solar system owners for surplus energy generated, making it advantageous to generate solar energy in excess of consumption.

However, along with these advantages come significant disadvantages. Solar tracking systems are very expensive, as they require additional components and increased labor for installation. The cost of a system for large utility-scale solar sites can increase by USD 0.1 per watt capacity, although this cost can vary depending on the system’s size and location [34]. The cost escalates significantly for small residential and commercial systems, with a single-axis system ranging from USD 500 to 1000 per module [35]. Adding trackers to a residential 4 kilowatt (kW) system results in an additional cost of USD 7000, making it more cost-effective to install more PV modules rather than opting for a tracker system in such cases. Generally, a fixed-angle ground-mounted system with 15 PV modules (300 W capacity per module) costs USD 14,600, whereas a ground-mounted system with a single-axis tracker costs USD 22,000, and a system with a dual-axis tracker costs USD 30,000 [36]. The fixed system generates annual energy savings of USD 1100, resulting in an estimated payback period of 13 years. In comparison, the single-axis tracker system generates USD 1430 of annual energy savings, with a payback period of 15.5 years, while the dual-axis tracker system generates USD 1540 of annual energy savings, leading to an estimated payback period of 19 years, which is 6 years longer than the fixed ground-mounted system. The maintenance costs of the system also increase with trackers due to the additional mechanical components they require [37]. Moreover, heavy snow can cause damage to solar tracker systems due to its weight [38], impeding the movement of the modules and potentially causing structural damage [39].

5. Bifacial Modules

Bifacial photovoltaic (PV) modules (Figure 7) are essentially crystalline PV modules that incorporate solar cells on both the front and back sides. This unique design enables them to capture sunlight from multiple directions. Furthermore, they have the capability to harness reflected sunlight from various surfaces such as water, ground, snow, and their surroundings. This advantageous feature results in significantly higher efficiency in solar energy generation compared to standard modules. Bifacial modules exhibit exceptional performance in snowy conditions, primarily due to the fact that snow can enhance the intensity of reflected sunlight from the ground, which the back side of the module can absorb [40,41].

A study conducted by Western University in Ontario, Canada, investigated the impact of snow losses on both bifacial and monofacial modules through an analysis of hourly data encompassing energy, solar irradiation, and albedo measurements (which quantify the diffuse reflection of solar radiation) [42]. It has been revealed that by utilizing bifacial PV modules instead of monofacial ones, annual snow losses could be significantly reduced from 16% to just 2%. Bifacial modules exhibited a remarkable 19% performance increase during winter, primarily attributed to the reflection of snow in comparison to conventional monofacial modules. This enhancement in energy generation occurs through two mechanisms. Firstly, sunlight reflected from the ground contributes to solar energy generation from the module’s back side. Secondly, when the module starts generating electricity from the back side, its surface heats up, leading to the melting and removal of snow from the front side of the module, enabling solar energy generation from both sides.

However, despite the advantages of bifacial modules, there are also downsides to consider. Bifacial modules are generally more expensive than regular modules, with small-scale solar systems incurring costs that can be up to USD 0.2 per watt higher than monofacial modules. For example, a small 6-kilowatt (kW) system could cost an additional USD 1200 compared to regular systems [43]. This price discrepancy decreases significantly when applied to large-scale utility solar sites, where bifacial panels may cost just 5 cents more per watt [43]. Another drawback of bifacial modules is that they cannot be installed on rooftops, requiring available ground space for their installation [44]. In conclusion, bifacial PV modules are a worthwhile investment if financial capacity exists, and adequate flat space is available for installation.

6. Future Prospects and Need for Passive Snow Removal Mechanisms

Active snow removal methods are often costly and inefficient, especially during severe weather conditions like heavy snowfall. Due to that, efforts have increasingly focused on the development of passive strategies that do not rely on external energy sources [45]. In order to achieve passive snow removal from PV modules, attention has been directed toward creating icephobic coatings with diverse characteristics, aimed at reducing ice adhesion or delaying/preventing ice formation. Noteworthy examples include superhydrophobic surfaces, slippery liquid-infused porous surfaces (SLIPS), hydrated surfaces, interfacial slippage, low interfacial toughness surfaces, and stress localization. These surface designs have shown potential in reducing ice adhesion strength and facilitating ice removal. However, the emphasis on reducing snow adhesion and promoting its removal has been comparatively limited [46,47,48,49,50,51,52].

Snow, unlike ice, is a porous medium made of water, ice, and air, and it exhibits various morphologies and physical properties dictated by atmospheric thermodynamic conditions during its formation. Although ice exhibits a significantly higher surface adhesion strength than snow, the low density of snow poses substantial challenges in its natural removal from surfaces due to its weight. Snow removal not only depends on accumulation thickness and external forces like wind but also relies on snow-specific physical properties such as flake size, liquid water content (LWC), and density. Additionally, surface properties such as roughness and surface energy play a role. Some structured surfaces have been implemented to aid snow removal, where the addition of low-interfacial-toughness coatings have been attempted on PV modules. However, complete and efficient snow removal has not been achieved, and the application of coatings to the module surfaces has proven labor-intensive, with concerns about durability due to their minimal thickness.

Structured surfaces’ efficiency in snow removal can be snow-type dependent and may suffer from increased snow adhesion if water infiltrates the surface texture through frost formation. Furthermore, snow’s high solar diffusive reflectivity (high albedo constant) in cold regions can prolong its presence on surfaces, leading to capillary-driven interfacial melting/icing cycles and contributing to snow/texture interlocking. Moreover, structured surfaces are vulnerable to multiple icing/deicing cycles and abrasion, which can increase snow adhesion. Elastomers with plasticization through lowered crosslink density, combined with interfacial slippage, have demonstrated potential in reducing ice adhesion. However, rough snowflakes can easily interlock with highly flexible surfaces, hindering effective shedding.

In recent research efforts, a range of hydrophobic, superhydrophobic, and hydrophilic coatings have been investigated for their potential in mitigating snow accumulation on PV modules passively [53,54,55,56,57,58,59,60,61,62,63,64,65,66]. However, findings suggest that employing these coatings does not efficiently facilitate snow removal from the PV modules. In fact, certain cases have demonstrated that untreated PV modules experience faster snow removal compared to coated ones. Moreover, concerns have emerged regarding the transparency and durability of such coatings when applied to PV modules. Therefore, passive snow removal methods have not been applied in the solar industry due to their limited effectiveness. Instead, active snow removal methods have been more common, despite their high cost and low efficiency.

7. Conclusions

In conclusion, the past decade has witnessed exponential growth in photovoltaic (PV) module installations, making it crucial to address the significant economic effects associated with snow accumulation on these modules. Snow accumulation poses a significant threat to the economic viability of PV systems by lowering solar energy production. Consequently, understanding the economic losses of snow on PV modules is vital for informed decision-making in the deployment of solar systems.

Interviews with solar industry experts and System Advisor Model (SAM) simulations have revealed that in regions prone to snowfall, annual economic losses due to snow accumulation range from 1% to as high as 12% of the total energy generation, amounting to a total of USD 313M for utility-scale and residential solar only. Furthermore, snow-related damage necessitates costly interventions, including module repairs, maintenance, and even complete module replacements, causing substantial financial costs.

While employing passive snow mitigation strategies on PV modules is favorable, their availability is limited due to the mechanical durability, robustness, and compliance of such methods (i.e., applying snow removal coatings). Therefore, implementing preventative maintenance schedules is still a viable but not efficient option. In this regard, advancements in predictive maintenance technologies can be pivotal, allowing for the early identification and rectification of potential snow-related damage before it escalates into costly repairs. Further innovations in PV module design, such as integrating stress-resistant features, can also improve their durability against heavy snow loads. These strategies not only minimize the direct costs associated with the repairs and downtime of the system but also extend the operational lifespan of the installations, enhancing their overall economic and functional efficiency.

To provide a clear picture of the scale of these impacts, Table 3 summarizes the annual energy and economic losses due to snow accumulation by different levels of snowfall. These tabulated data serve to quantify the financial implications across varied geographic conditions and highlights the critical need to strategize the implementation of any innovative snow mitigation strategies.

In regions characterized by heavy snowfall (more than 40 inches of annual snowfall), solar companies employ a variety of different snow mitigation strategies. Among these, solar trackers and bifacial modules have emerged as the most effective methods for reducing snow-related energy losses. Solar trackers enhance the shedding of snow by adjusting the tilt of the panels, while bifacial modules use reflected sunlight from snow to generate additional energy and facilitate melting.

However, these active snow mitigation methods have negative impacts, including high costs, inefficiency, limited scalability, and the potential for causing damage to the modules. Despite the effectiveness of bifacial modules in mitigating snow accumulation, their higher cost and the need for specific installation conditions limit their widespread adoption.

Passive approaches, such as applying coatings, have been explored but have shown minimal efficiency, with concerns regarding their durability and transparency. Thus, there is a critical need for the development and integration of more efficient passive snow removal technologies. Innovations in materials science could lead to new coatings or surfaces that significantly reduce snow adhesion, improving the efficiency and operational reliability of PV systems in snowy environments in a sustainable and reliable manner.

In future, the solar industry should focus on integrating advanced snow mitigation technologies into standard practices, to enhance feasibility and efficiency of solar energy in regions that experience heavy snowfall. Additionally, further research into predictive models can better anticipate and manage the impacts of snowfall on solar energy production, optimizing system design and maintenance strategies.

Author Contributions

Conceptualization, A.H.A.Y. and E.K.; methodology, A.H.A.Y.; data curation, A.H.A.Y. and E.K.; writing—original draft preparation, A.H.A.Y. and E.K.; writing—review and editing, A.H.A.Y., E.K., and H.S.; supervision, H.S. All authors have read and agreed to the published version of the manuscript.

Data Availability Statement

The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding author.

Conflicts of Interest

The authors declare no conflicts of interest.

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. Installed PV capacity in the U.S. from 2010 and its projection till 2027 for residential, commercial (non-residential), and utility-scale solar. There is an increasing trend in installed capacity from 2010 to 2023, and a projection of continuous increase in capacity from 2024 till 2027. It is clear that the utility-scale solar contributes the major portion of the U.S. capacity and is growing more rapidly than other segments of the market. Source: https://www.woodmac.com/industry/power-and-renewables/us-solar-market-insight/ (accessed on 9 September 2022).

Figure 2. (A) Heavy snow accumulation covering commercial/residential PV modules. Source: https://solarbuildermag.com/featured/do-you-need-a-solar-snow-management-system/ (accessed on 1 June 2024). (B) Snow covering a solar plant that sometimes leads to annual losses of up to 10%. (C) Heavy snow remaining on the PV modules, even when snow is mechanically removed/cleared from the ground. Source: https://insidesources.com/green-where-the-sun-doesnt-shine/solar-panels-snow/ (accessed on 10 December 2023).

Figure 3. Energy production of a solar company in 2021 over 12 months. Snow significantly reduced energy production: in January the 135 kW capacity solar plant only produced around 6 MWh, while in July the plant produced around 40 MWh (more than 6 times the January production).

Figure 4. (A) Snow accumulation on PV modules applies considerable mechanical load on them, causing structural damages and shortening their lifetime. Source: https://solarquarter.com/2022/02/16/longi-hi-mo-5-pv-modules-recognized-by-cgc-for-strong-resistance-to-inhomogeneous-snow-load/ (accessed on 20 November 2023). (B) Hail and freezing rain have penetrated the PV glass. Source: https://www.maysunsolar.eu/blog/does-hail-have-the-potential-to-destroy-solar-panels (accessed on 20 November 2023). (C) Heavy snow accumulation has damaged PV modules and deformed their structure. Source:https://www.aquasoli.com/blog/snow-load-damages-reported-in-japan/ (accessed on 20 November 2023).

Figure 5. (A) U.S. map highlighting, in red, 12 states that experience heavy snow accumulation (more than 40 inches of annual snowfall), and 16 states, highlighted in orange, that experience moderate snowfall (between 20 and 40 inches of annual snowfall). Module frame damaged by snow accumulation (provided by Ed Hutchinson). (B) Graph classifying snowfall in all U.S. states into 3 categories: heavy snowfall (more than 40 inches of annual snowfall), moderate snowfall (between 20 and 40 inches of annual snowfall), and light snowfall (between 10 and 20 inches of annual snowfall). Data source: Average snowfall by state [updated November 2022], World Population Review, https://worldpopulationreview.com/state-rankings/average-snowfall-by-state (accessed on 10 March 2023).

Figure 6. Snow mitigation methods from PV modules. (A) Clearing snow from the ground using tractors, followed by (B) labor-based manual removal of snow from PV modules. (C) Sketch showing a method used to thermally heat snow. (D) Dual-axis tracker system that allows a change in the module’s tilt angle at any time. Using this tracker system, modules are tilted to higher angles to help with snow sliding. Source: https://www.eco-worthy.com/collections/solar-tracker-system (accessed on 1 March 2024).

Figure 7. Sketch showing the working principle of bifacial modules (illustration by Alfred Hicks, NREL). Source: https://www.nrel.gov/pv/pv-bifacial-irradiance-toolkit.html (accessed on 1 April 2023).

Table 1

A table presenting annual snowfall and snow load per module in U.S. states with heavy snowfall (over 40 inches or 1 m). The module size is assumed to be $1\times 2{\mathrm{m}}^2$ and the average snow density is assumed to be $100{\mathrm{kg}/\mathrm{m}}^3$.

State	Vermont	Maine	New Hampshire	Colorado	Michigan	New York	Massachusetts
Annual Snowfall (m)	2.25	2	1.8	1.7	1.5	1.4	1.3
Annual Snow Load per Module (kg)	450	400	360	340	300	280	260
Module Snow Load over Lifetime (kg)	11,250	10,000	9000	8500	7500	7000	6500

Table 2

A table presenting the number of panels, energy generated, and total value of electricity produced in heavy-, moderate-, and light-snowfall areas in the U.S. in the year 2023, comparing utility-scale and residential solar.

Utility-Scale Solar
Annual Snowfall (in)	Heavy $\ge \mathbf{40}$	Moderate $\mathbf{40}\ge \mathit{x}\ge \mathbf{20}$	Light $\mathbf{20}\ge \mathit{x}\ge \mathbf{10}$
Number of Panels (million)	28	17	29
Total Annual Energy Generated (GWh)	15,700	10,100	16,000
Total Value of Electricity Produced Annually (million USD)	2500	1700	2200
Annual Energy Lost Due to Snow (GWh)	550	354	560
Total Annual Losses Due to Snow (million USD)	88	60	77
Residential Solar
Annual Snowfall (in)	Heavy $\ge \mathbf{40}$	Moderate $\mathbf{40}\ge \mathit{x}\ge \mathbf{20}$	Light $\mathbf{20}\ge \mathit{x}\ge \mathbf{10}$
Number of Panels (million)	10	10	6
Total Annual Energy Generated (GWh)	5600	5600	2900
Total Value of Electricity Produced Annually (million USD)	1100	1000	400
Annual Energy Lost Due to Snow (GWh)	196	196	102
Total Annual Losses Due to Snow (million USD)	39	35	14

Table 3

Summary of annual energy and economic losses due to snow accumulation on PV modules.

Region	Annual Energy Loss (%)	Annual Loss (million USD)
Heavy-Snowfall States	3.5–12%	88
Moderate-Snowfall States	2.5–10%	60
Light-Snowfall States	1–5%	77
Total Losses		225

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