How to Decide PVSyst Loss Coefficients? 7 Points to Know Before Setting Them

Table of Contents

• Loss factors are correction values to make estimated power generation closer to reality

• Clarify the purpose of the simulation before deciding loss factors

• Treat the uncertainties of meteorological conditions and irradiance data separately

• Assess temperature losses based on the installation environment and racking conditions

• Consider soiling losses together with regional characteristics and cleaning schedules

• Confirm the design basis for wiring and electrical losses

• Use conservative-side and performance-side values appropriately for mismatch and degradation

• Verify shading losses not only by coefficients but also under 3D conditions

• Practical workflow for determining loss factors

• Summary

The loss coefficient is a correction value for bringing power generation closer to reality.

The loss factor in PVSyst is a correction value entered to bring the energy yield obtained under ideal conditions closer to that of a real power plant. A photovoltaic system does not continue to produce at maximum efficiency simply because sunlight falls on the panels. In reality, energy output is reduced by various factors such as module temperature rise, soiling, shading, wiring resistance, equipment conversion, module-to-module variability, aging, downtime, snow, and reflection conditions.

In using PVSyst, it is important not to treat loss coefficients as mere input fields. Entering numbers may be simple, but unless you verify that those values align with site conditions, design conditions, and operational conditions, the reliability of the simulation results will be reduced. For example, even for projects with the same generation capacity, appropriate loss settings differ between mountainous and coastal areas, ground-mounted and rooftop installations, dry regions and regions with high rainfall, and projects with regular cleaning versus those with an undefined cleaning schedule.

Loss coefficients are not merely conservative values used to make estimated generation appear lower. If you stack overly cautious figures, the generation may be underestimated, which can lead to incorrect investment decisions and misleading comparisons in plant design. Conversely, using excessively optimistic values can cause actual post‑completion generation to fall short of simulations, creating problems when explaining results internally or to customers. In other words, loss coefficients are neither something you can simply “set conservatively” nor just “use the standard values as‑is”; they are settings that must be balanced with a well‑founded rationale.

In practice, when determining loss coefficients, we comprehensively consider design values, manufacturer documentation, past project performance, on-site surveys, maintenance plans, the surrounding environment, and contractual assumptions. Especially when using a PVSyst report as submission material, it is important to be able to briefly explain, for each loss item, why that value was chosen. If the rationale for the loss coefficients is clear, it becomes easier to compare during design changes, analyze differences in power generation, and verify performance after construction.

PVSyst reflects losses at multiple stages. You can separately check where in the power generation process reductions occur: losses before solar irradiance reaches the module surface, losses during the stage where the module converts it into DC power, losses through wiring and conversion equipment, and losses up to the grid interconnection point. Therefore, when deciding on loss coefficients, it is important not only to consider the final annual energy yield but also to identify which losses are large by looking at the loss diagram and the individual items in the report.

Clarify the purpose of the simulation before determining the loss coefficient

Before deciding on the loss coefficients, the first thing to confirm is what this PVSyst simulation is being carried out for. If the purpose differs, even the same project will require a different approach to the loss coefficients adopted. Whether it is an initial candidate-site assessment, a basic design, a detailed design, a final check before construction, or a post-completion performance comparison, the required level of accuracy and the granularity of explanation will differ.

At the candidate site evaluation stage, detailed wiring lengths, equipment layouts, mounting-structure specifications, cleaning plans, and details of nearby obstructions are often not yet decided, so it is common to compare multiple options using loss factors within a general range. At this stage, it is more important to standardize the conditions for comparison than to determine a single precise value. For example, when comparing multiple land candidates, varying the loss factors too much between projects makes it difficult to tell whether differences are due to site conditions or to differences in input assumptions.

However, during the preliminary and detailed design stages, loss factors must be set based on more specific equipment specifications. As the module model, racking structure, array spacing, power conditioner capacity, wiring routes, the locations of junction boxes and combiner boxes, and the distance to transformer equipment are decided, wiring losses, mismatch losses, temperature conditions, and so on can be made closer to reality. If loss factors are left vague at this stage, it becomes difficult to trace which design change later affected the difference in power output.

When preparing business plans or materials for external submission, explainability is particularly important. Rather than simply choosing settings that yield higher power generation, assumptions should be neither overly conservative nor overly optimistic. In addition to figures such as annual power generation, PR, capacity factor, and monthly generation, the basis for loss coefficients may also be reviewed. Especially for large-scale projects, even small differences in loss coefficients can result in large differences in annual power generation, so you need to be able to explain the validity of the input values.

When the objective is to compare post-completion performance, the design assumptions and operational actuals should be considered separately. For example, if the design assumed standard soiling losses but in reality there was heavier soiling due to nearby construction or dust, explaining the gap with actual performance requires comparing the original settings with on-site conditions. In addition, there are elements that should be managed separately from the usual losses in PVSyst, such as generation outages, communication faults, output curtailment, and snow.

A practical recommendation is to organize the purpose before creating a simulation, categorizing it as "for comparison," "for design," "for submission," or "for verification." Also, when you enter loss coefficients, make a brief note explaining why you adopted those values. It's a mundane task when using PVSyst, but it will be extremely helpful when you review the conditions later. Especially when creating multiple cases, if you lose track of whether you changed the loss coefficients, the layout, or the equipment capacity, the reliability of the comparison will suffer.

Loss coefficients are not something you decide once and for all. As the design progresses, site survey results, equipment specifications, construction conditions, and maintenance conditions become more concrete. Each time this happens, reviewing the necessary items and updating values from the initial assumptions to ones closer to the detailed design is fundamental when using PVSyst in practice.

Consider the uncertainties of meteorological conditions and solar radiation data separately

A common source of confusion when deciding on loss coefficients is distinguishing between uncertainty in meteorological data and equipment-side losses. In PVSyst you input meteorological conditions such as solar irradiance, ambient temperature, and wind speed, and it calculates energy production based on those inputs. However, the meteorological data themselves exhibit year-to-year variability, site-to-site differences, and variations among data sources. If you try to absorb the uncertainty in meteorological data by applying large loss coefficients, it becomes difficult to identify which factors are actually causing the reduction in energy production.

Solar radiation data is the foundation of power generation simulations. If the annual solar radiation is set high, the electricity output will be high; if it is set low, the electricity output will be low. The loss coefficient essentially represents how much of that solar radiation is lost within the system. Therefore, the selection of solar radiation data and the setting of the loss coefficient are related, but need to be treated as separate issues.

For example, if the solar irradiance data for a region appear higher than historical performance, increasing soiling loss and temperature loss to make the final energy production match is not desirable. The apparent annual energy yield may line up, but the loss diagram will provide an explanation that differs from reality. If you are uncertain about the assumptions for solar irradiance, first check the type of meteorological data, nearby observation stations, the relationship with long-term averages, the number of years of data used, and monthly trends.

Also, even with the same annual solar irradiance, differences in monthly distribution change how energy yield and temperature-related losses appear. In regions with higher irradiance in summer, losses due to module temperature rise tend to be larger, while regions with higher irradiance in winter can be advantageous from a temperature standpoint. Therefore, when determining loss coefficients, it is important to consider monthly weather conditions as well as annual values.

Among meteorological conditions, wind speed affects temperature losses. For ground-mounted systems with good ventilation, modules cool more easily, while installations close to the roof surface or in poorly ventilated structures tend to trap heat. However, because wind speed data can be coarse or may not reflect the site's microtopography, you should not rely entirely on PVSyst’s temperature model and should verify its validity against the installation conditions.

In practice, it is easier to explain if uncertainty in meteorological data is treated separately as a risk rather than being mixed into a "loss factor." For example, use standard meteorological data for the baseline case and compare low-irradiance and high-irradiance cases as sensitivity analyses. Meanwhile, set the equipment-side loss factors based on local conditions. By separating them in this way, you can distinguish between "differences in solar irradiation conditions" and "differences in equipment losses" when explaining internally.

When using PVSyst, it is important not to adjust settings by looking only at the loss coefficient screen, but to check the whole sequence: selection of meteorological data, site configuration, monthly irradiance, ambient temperature, wind speed, and the loss chart of the simulation results. Especially when the energy production is higher or lower than expected, it is practical to first verify the assumptions behind the irradiance data, and if that still does not explain the discrepancy, then review each loss item in order.

Temperature loss is determined by the installation environment and racking conditions

In photovoltaic power generation, module temperature increases reduce generation efficiency. In PVSyst's loss settings, temperature loss is a factor that significantly affects annual energy production. Especially in regions like Japan, where summer temperatures are high and solar irradiance is strong, it is important to appropriately evaluate temperature loss. Temperature loss is not determined solely by ambient air temperature; it varies depending on the installation method, ventilation, racking height, distance to the roof surface, and the surrounding environment.

For ground-mounted installations, ventilation on the back side of the modules is more easily ensured, and heat tends to escape more readily than with installations mounted flush to the roof. Conversely, for roof-mounted installations, the influence of heat from roofing materials and insufficient ventilation can cause module temperatures to rise more easily. Furthermore, on low-pitch roofs, in locations enclosed by walls, or in places where wind does not pass through easily, temperature loss tends to be greater even at the same ambient temperature.

In PVSyst, you set parameters related to thermal loss coefficients and temperature models according to the mounting configuration. A common mistake beginners make is using the initial or general settings as-is without reflecting the actual racking conditions. You should confirm whether the installation is ground-mounted, rooftop, or close to building-integrated, and whether there is sufficient rear-side ventilation, and configure the settings to match the installation conditions.

Also, temperature losses are related to module specifications. Modules have a temperature coefficient that defines how much the output decreases with temperature rise. When you select module data in PVSyst, this temperature characteristic is reflected in the calculations, but it is assumed that the entered module information matches the actual modules used. If there are differences in model or specifications, they will affect not only temperature losses but also the voltage range and string design.

When determining temperature losses, the surrounding environment must not be overlooked. For example, if installed near heat-retaining surfaces such as asphalt or metal roofs, it may be affected by surrounding radiant heat. Conversely, elevated sites or open locations with strong wind flow can be expected to provide cooling effects. However, in windy locations, structural design conditions also come into play, so decisions should be made not only based on power output but also taking construction and safety aspects into account.

When reviewing PVSyst results, it is important to check whether the temperature losses are not extremely large or small compared with other similar projects. If temperature losses are smaller than expected, verify whether the ventilation conditions have been overestimated or whether the temperatures in the meteorological data are too low. Conversely, if temperature losses are large, check whether roof-mounted installation and ventilation conditions are being reflected, or whether the input conditions are too stringent.

Temperature losses cannot be completely eliminated on site. However, there is room to mitigate them at the design stage by ensuring ventilation of the racking, avoiding layouts that trap excessive heat, and understanding the surrounding environment. Therefore, one of the practical values of using PVSyst is not only determining the loss coefficient but also considering whether there is room for design improvements when losses are large.

Consider soiling losses in conjunction with regional characteristics and cleaning plans

Soiling losses occur when solar radiation is obstructed from reaching the cells due to materials that adhere to the module surface, such as sand and dust, pollen, bird droppings, fallen leaves, exhaust-related dirt, salt, and agricultural dust. When setting loss coefficients in PVSyst, soiling loss may appear to be a minor item at first glance, but depending on the region and operating conditions it can have a non-negligible impact on annual energy production.

When considering soiling losses, it is important to assess regional characteristics together with cleaning plans. In regions where rain falls regularly, natural washing can be expected to be effective, but in areas with long dry periods, high levels of dust, or nearby land development or agricultural activities, soiling tends to accumulate more easily. In addition, coastal areas experience salt deposition, locations with many birds experience localized soiling, and areas near forests or street trees can be affected by fallen leaves and tree sap.

If the cleaning plan is clear, it becomes easier to organize the approach to soiling losses. When regular cleaning is performed, because the period during which soiling accumulates is limited, the annual average soiling loss can be reduced to some extent. On the other hand, if the cleaning plan is undecided or left to rainfall, it is necessary to consider conservative settings based on the site environment. In particular, for low-tilt installations, rainwater does not run off easily and soiling tends to remain on the lower edge of the modules.

However, if soiling loss is set too high, it becomes difficult to understand its relationship with other losses. For example, if power generation is actually reduced due to shading or string layout effects, lumping that together as soiling loss can cause you to overlook design issues. Soiling loss should be considered strictly as losses caused by dirt on the module surface, and it is important to treat it separately from shading, temperature, wiring, and equipment losses.

When entering soiling losses in PVSyst, you can also consider applying monthly variations. For example, if the tendency for soiling accumulation differs between the rainy season and the dry season, monthly settings can more closely reflect reality than a uniform annual coefficient. If regional characteristics can be reflected—such as heavy dust near farmland during certain seasons, increased soiling during pollen season, or soiling being washed away after snowfall—it is worth considering a monthly approach.

In practice, during the initial planning stage it is realistic to provisionally set typical values and then revise them once site surveys and operational policies are finalized. Check site photos, the condition of surrounding roads, nearby facilities, land use, wind direction, rainfall trends, and the maintenance company's cleaning policies to provide a basis for the figures. If a power plant is already operating nearby, its performance data and inspection records can be useful.

Soiling losses are not an item that is completed during the design stage alone. If a decrease in power generation is observed after operations begin, verify on-site whether it is due to soiling and, as necessary, review cleaning frequency and maintenance plans. Comparing the soiling losses set in PVSyst with actual operational conditions improves the accuracy of settings for the next project.

Confirm the design basis for wiring losses and electrical losses

Wiring losses are losses that occur due to the resistance of cables during the process of transmitting power from the modules to the power conditioner and further to substation equipment and the interconnection point. When determining PVSyst loss coefficients, wiring losses are a relatively easy item to justify. This is because, if the cable length, cross-sectional area, current, voltage, and circuit configuration are known, they can be evaluated based on design calculations.

What beginners should be careful about is not treating wiring losses as merely a standard value. During the initial study phase it is acceptable to use provisional values, but once you enter detailed design you need to review them based on the actual wiring routes and cable specifications. Especially in large-scale ground-mounted installations, the distance from the array to the collection point tends to be long, and wiring losses affect power generation. Changing the equipment layout even slightly can alter cable lengths and thereby change losses.

It is also important to consider DC-side and AC-side losses separately. On the DC side, this involves the cables from the strings to the combiner box, the collector box, and the power conditioner (inverter). On the AC side, it involves the cables and transformers from the power conditioner to the transformer equipment, the receiving equipment, and the point of interconnection. In PVSyst, if you are not conscious of which stage a loss is entered at, you may double-count the same loss or, conversely, omit it.

When setting wiring losses, consistency with the design drawings is important. If single-line diagrams, layout drawings, cable lists, and equipment arrangement drawings are available, cross-check them against the input values in PVSyst. At stages where detailed drawings are not yet available, you may use standard values from projects of the same scale or estimated routes, but in such cases make it clear that these are assumed values. If you assume they will be updated later to match the detailed design, you can progressively improve the accuracy of the simulation.

Electrical losses involve not only wiring losses but also the efficiency of conversion equipment, auxiliary consumption, transformer losses, losses at connection points, and so on. The efficiency of power conditioners is largely calculated based on equipment specifications, but it is necessary to confirm that the entered equipment data match the actual specifications. Also, how much to include auxiliary consumptions such as transformer losses, nighttime consumption, and monitoring devices depends on the purpose of the simulation.

In PVSyst reports prepared for submission, it is important to check that wiring losses and electrical losses are not at extreme values. If wiring losses are too small, they may not reflect the actual cable lengths or current conditions. If they are too large, the wiring route may be inefficient, cable sizes may be insufficient, or input values may be duplicated. It is not simply that large losses are bad; you need to assess whether they are reasonable from a design perspective.

Wiring losses are an aspect that can often lead to design improvements. Revising equipment layout, optimizing cable sizes, shortening collector routes, and streamlining circuit configurations can sometimes reduce losses. When comparing multiple proposals in PVSyst, rather than simply looking at differences in energy production, checking how wiring losses have changed makes it easier to identify potential design improvements.

Differentiate between the safety side and the performance side for mismatches and degradation

Mismatch loss is the loss that occurs when modules within the same string or array do not have exactly the same output characteristics. Even modules of the same model have manufacturing variations, and after installation their outputs can diverge due to differences in soiling, temperature, shading, and aging. When determining loss coefficients in PVSyst, mismatch loss is easy to overlook, but it is important for long-term energy yield assessment.

When assessing mismatch loss, check module selection, string configuration, uniformity of azimuth and tilt, and the presence of shading. If modules with different azimuths or tilts are mixed within the same string, current variation increases and losses tend to rise. Also, if local shading affects some modules, the impact of mismatch becomes larger. Therefore, mismatch loss should not be considered solely as an isolated coefficient but must be evaluated together with the layout and string design.

Regarding degradation, it is important to consider separately the first-year drop in output and the long-term annual degradation. Because solar power plants are often planned for operation of more than 20 years, long-term energy yield forecasts, not just first-year generation, are important. In PVSyst, by running simulations that take into account aging degradation, you can evaluate future annual generation and cumulative energy production.

When setting the degradation rate, refer to module specifications, warranty terms, performance records of similar projects, and the operating environment. However, guaranteed values are for warranty purposes and may differ from actual degradation behavior. In evaluations that emphasize historical performance, past data is used as a reference, while in conservative business planning a somewhat more conservative degradation rate is applied—it's important to choose according to the purpose.

What is important here is not to confuse the "safety side" with the "actual side." For financial institutions and conservative assessments of long-term cash flow, a somewhat safety-side degradation rate may be used. On the other hand, when comparing with actual power generation or analyzing operational improvements, using an overly conservative degradation rate can prevent accurately capturing the real performance decline. It is necessary to make clear for what purpose that coefficient is being used.

Mismatch and degradation may not be apparent immediately after a plant is completed. Even if the first year is as expected, variations between strings can become larger after a few years, or degradation of some modules may advance. Therefore, when performing long-term forecasts in PVSyst, we check not only the single-year generation but also the year-by-year decline in generation and the cumulative generation.

As a practitioner, when determining mismatch losses and degradation rates, it is important not only to use standard values but also to consider whether design variability factors can be reduced. Aligning orientation and tilt, avoiding grouping shaded areas into the same circuit, designing appropriate string lengths, and detecting abnormal strings early in post-construction inspections are measures that can be taken at each stage of design, construction, and maintenance.

Check shading losses not only by coefficients but also under 3D conditions

Shading losses occur when solar irradiance reaching the module surface is blocked by surrounding buildings, trees, utility poles, fences, inter-row shading between mounting structures, terrain undulations, and the like. When defining loss coefficients in PVSyst, shading losses are an item that should preferably be verified using 3D scenes and obstruction conditions as much as possible rather than being treated solely by a simple percentage input.

The impact of shadows is not constant throughout the year. In winter and in the morning and evening, when the sun’s elevation is low, shadows become longer, and the way shadows appear differs greatly from daytime in summer. Not only obstacles on the south side but also those to the east and west affect power generation in the morning and evening. Especially for self-consumption systems or projects where time-of-day generation is important, it is necessary to check not only the annual generation but also the impact of shadows by time of day.

For ground-mounted installations, the relationship between array spacing and tilt angle affects inter-row shading. Increasing the tilt angle can improve sunlight reception conditions in winter, but it may also increase inter-row shading. Conversely, widening array spacing can reduce shading losses, but it may decrease the capacity that can be installed on the same site. Therefore, shading losses should be evaluated not only in terms of energy generation but also in balance with land-use efficiency and installed capacity.

For rooftop installations, adjacent buildings, rooftop equipment, parapets, chimneys, antennas, railings, and similar structures can cause shading. Even small obstacles can affect the output of an entire string if they cast shadows on part of a module for extended periods. When performing shading analysis in PVSyst, it is important to enter the positions, heights, and distances of obstacles as accurately as possible.

When shading losses are entered only as a coefficient, there is a problem that the rationale can become unclear. Of course, in the initial study phase it is sometimes acceptable to provisionally assign an approximate shading loss. However, at advanced stages of design it is necessary to verify shading conditions concretely using on-site surveys, drawings, 3D models, photographs, terrain information, and so on. Especially for projects with many surrounding obstructions, the setting of shading losses affects the reliability of power generation forecasts.

In PVSyst results, you can check the extent of losses caused by shading. If shading losses are large, consider reviewing the array layout, defining areas where modules are not placed, changing string grouping, and ensuring adequate separation from obstacles. The practical point is not simply to accept shading losses as numbers, but to see whether they can be reduced through design improvements.

Also, shading losses include shading caused by distant terrain and shading caused by nearby obstructions. In mountainous areas, terrain toward the horizon can block morning and evening sunlight. In urban areas and on rooftops, nearby structures create localized shading. Because these arise from different mechanisms, it is easier to explain if they are not lumped together as the same shading loss but are separated and checked to the extent possible.

Shading loss settings are closely related to the accuracy of the on-site survey. If the site dimensions, obstacle heights, module layout, orientation, and tilt are not correctly captured, no matter how carefully you configure them in PVSyst, the results will diverge from reality. To improve the accuracy of power generation simulations, it is essential not only to operate the software correctly but also to increase the accuracy of site information acquisition.

Practical workflow for determining loss coefficients

When determining loss coefficients in PVSyst, rather than entering items as they come to mind, organizing them according to a fixed procedure can reduce mistakes. First, confirm the project's purpose and the intended use of the simulation. Whether it is a site comparison, detailed design, submission materials, or performance verification will change the required level of accuracy. Once the purpose is clarified, gather the meteorological data to be used, site conditions, equipment specifications, design drawings, and on-site information.

Next, we confirm the assumptions that have a large impact on power generation. We check the solar irradiance data, the module surface tilt and azimuth angles, the array configuration, equipment capacity, string design, and shading conditions. If there are errors in these basic conditions, adjusting the loss coefficients will not produce correct results. In particular, the azimuth direction, tilt angle, installed capacity, number of modules, and power conditioner capacity are items prone to input mistakes.

On that basis, we will sequentially review temperature loss, soiling loss, wiring loss, mismatch loss, equipment loss, degradation rate, and shading loss. For each item, document the basis for the input values. The bases include manufacturer specifications, design calculations, past projects, site conditions, maintenance plans, in-house standards, and so on. Even if it is difficult to thoroughly demonstrate every item in detail, it is important to at least record the rationale for decisions such as "adopted standard values," "based on design calculations," or "considered site conditions."

Next, review the loss diagram in PVSyst. By inspecting the loss diagram you can understand at which stages, from solar irradiance to the final output, losses occur and how large they are. If a particular loss is unusually large or small, check the input values. For example, if the wiring loss is very small, verify that cable conditions were not left blank; if the shading loss is larger than expected, confirm that obstruction settings or inter-row spacing are correct; and if temperature loss is too small, check whether the mounting structure conditions are overly optimistic.

When comparing multiple cases, clearly define what is being changed. For example, narrow down the variables according to the purpose of the comparison: a case that changes only the tilt angle, a case that changes only the array spacing, a case that changes the cabling route, a case that changes the cleaning frequency, and so on. Changing multiple conditions at the same time makes it difficult to determine which factor affected the difference in power generation. For PVSyst use, case management and organizing assumptions are extremely important.

When explaining to internal staff or customers, do not simply list the loss coefficients in detail; clearly explain the main factors that are affecting the power generation. Not all loss items are of equal importance. Depending on the project, shading loss may be the most important, while in others temperature loss, soiling loss, or wiring loss may be critical. By using a loss diagram to show which items have the greatest impact on power generation, you can more easily gain the understanding of stakeholders.

Finally, retain the assumptions for comparing actual post-completion performance. PVSyst simulations are forecasts at the design stage. After operations begin, actual solar irradiance, temperature, downtime, power curtailment, soiling, failures, cleaning history, and other factors will affect performance. To compare the difference between the design loss coefficients and actual performance, you need to save the original input conditions and keep them in a state where they can be reviewed later. If the conditions are lost, it becomes difficult to judge whether the performance was good or poor.

Summary

PVSyst's loss coefficients are an important setting for bringing power generation simulations closer to reality. However, simply entering the default values does not necessarily produce results that match site conditions. When determining loss coefficients, it is important to first clarify the purpose of the simulation and then, in order, check the meteorological data, installation conditions, racking conditions, wiring design, equipment specifications, maintenance plan, and surrounding environment.

Temperature losses are considered based on the installation environment and ventilation conditions; soiling losses are based on regional characteristics and cleaning plans; wiring losses are determined by design calculations; mismatch and degradation are addressed through long-term operation considerations and purpose-specific safety margin settings; shading losses are considered based on site conditions and 3D analysis. It is important not to determine any loss in isolation, but to assess them in connection with the overall project's design conditions.

Also, loss coefficients are not something you enter once and forget. They should be reviewed whenever new information becomes available during the process of site selection, basic design, detailed design, pre-construction checks, and post-completion verification. To master PVSyst in practice, it is essential not only to record the input values themselves but also to document why those values were chosen and to make a habit of verifying their validity with loss diagrams and reports.

Losses related to shading, wiring, and racking conditions in particular are greatly influenced by the accuracy of on-site information. By accurately capturing not only the assumptions on the drawings but also the actual terrain, obstacles, installation location, orientation, tilt, and surrounding environment, the input accuracy for PVSyst also improves. If the site coordinates, elevation, and positions of structures can be obtained accurately, the explanatory power of the simulation results will also increase.

Therefore, if you want to bring the design of a solar power plant and PVSyst’s energy yield predictions closer to actual site conditions, improving the accuracy of on-site surveys is also important. LRTK, as a GNSS high-precision positioning device that can be attached to an iPhone, can capture location information on site and streamline point cloud measurements, coordinate recording, and photo documentation. As a preliminary step before considering loss factors in PVSyst, accurately capturing site conditions, surrounding obstructions, racking locations, and terrain makes it easier to assess shading conditions, perform layout studies, and verify post-construction results. The accuracy of simulations depends not only on inputs within the software but also on how accurately the site can be captured. By combining PVSyst’s energy yield predictions with on-site measurements using LRTK, it becomes easier to make consistent decisions from design through construction to operational verification.