【How to Set the Degradation Rate in PVSyst｜6 Fundamental Tips for Long-Term Forecasting】

Table of Contents

• The meaning of setting the degradation rate in PVSyst

• Prerequisites to determine before entering the degradation rate

• Basic 1: How to think about the annual degradation rate

• Basic 2: Consider separating first-year degradation and long-term degradation

• Basic 3: Impact of output decline to check in long-term generation forecasts

• Basic 4: Do not confuse guaranteed values and actual performance values

• Basic 5: Confirm the range of degradation rates with sensitivity analysis

• Basic 6: Revisit settings based on site conditions and inspection data

• Practical notes when handling degradation rates in PVSyst

• Site information required to improve the accuracy of long-term forecasts

• Summary: Setting the degradation rate is a key item linking long-term revenue and maintenance

What it means to set the degradation rate in PVSyst

When simulating a solar power plant in PVSyst, evaluating the design based only on the initial annual energy production will not allow you to correctly assess its long-term viability. Solar power systems do not maintain the same performance forever from the moment they are installed; their output gradually declines over time. The way to reflect this output decline in long-term forecasts is by setting the degradation rate.

The degradation rate is an indicator that shows how much the performance of a solar module or an entire power generation system declines over time. For example, even under the same solar irradiance, the same temperature, and the same shading conditions, the energy output immediately after installation and 20 years later will not necessarily be identical. Long-term financial projections, power generation guarantees, documents for financial institutions, internal investment decisions, and maintenance planning all require handling power generation estimates that take this aging-related degradation into account.

For practitioners learning how to use PVSyst, it is important not to treat the degradation rate as merely an input parameter. It's easy to just enter a number, but unless you check what assumptions that number is based on, how much it affects generation in each year, and whether it overlaps with other loss items, the credibility of the simulation results will be weakened. In particular, the longer the plant's operational period—20 years, 25 years, 30 years—the more small annual differences accumulate into large differences in generated energy.

In PVSyst, you can input design conditions and loss parameters in detail and review annual energy production, loss diagrams, monthly generation, performance ratio, and more. However, the degradation rate is an item that can be easily overlooked when using single-year simulations alone. Even if differences may not look significant when only comparing first-year generation, long-term forecasts directly affect revenue planning and maintenance policies. Therefore, the purpose of setting the degradation rate in PVSyst is not simply to reflect module performance decline, but to produce a projection that more closely matches the actual situation when operating a plant over the long term.

Moreover, the degradation rate affects not only generation but also comparisons between design options. Even a design with higher initial generation can be disadvantaged in cumulative generation if it is subject to conditions that cause stronger long-term degradation. Conversely, even if the first-year difference is small, a configuration that is expected to provide stable generation over the long term may be advantageous over the entire project period. When reviewing PVSyst results, it is important to consider single-year generation, long-term cumulative generation, and generation in future years reflecting the degradation rate separately.

Prerequisite Conditions to Set Before Entering the Degradation Rate

Before setting the degradation rate in PVSyst, the first thing to decide is the purpose of the simulation. Whether it is an early-stage rough design assessment, a comparison document for internal approval, or a long-term energy production forecast to submit to financial institutions or project owners, the way you treat the degradation rate will differ. Standard assumptions may be acceptable at the estimation stage, but for submission documents or materials related to contracts, the values must be numbers you can justify with supporting evidence.

Next, you need to clarify the forecast period. Whether you are forecasting for 10 years, 20 years, or nearly 30 years greatly changes the impact of the degradation rate. Even if the annual degradation rate appears small, the longer the period the more the cumulative energy production will diverge. For example, even with the same first-year energy production, the generation after 20, 25, or 30 years will differ depending on how you set the annual output decline. When entering the degradation rate in PVSyst, it is important to decide in advance up to which year you ultimately want to model the energy production.

Furthermore, it is necessary to clarify whether the degradation in question refers to the output decline of individual modules or to the performance decline of the entire power generation system. In general, the term "degradation rate" often refers to the age-related output decline of solar modules, but actual power generation is influenced by factors other than the modules. Deformation of the mounting structure, deterioration of cable connections, accumulation of dirt, poor drainage, vegetation growth, equipment replacement history, insufficient inspections, and so on also affect long-term power generation. If all of these are included in the degradation rate, they may overlap with other loss items.

To perform accurate long-term forecasting in PVSyst, it is important to consider degradation rate, soiling loss, wiring loss, mismatch loss, temperature loss, shading loss, and so on separately. Organizing them as: degradation rate being an element that changes with ageing; soiling loss being an element that varies with cleaning frequency and environmental conditions; and shading loss being an element that varies with nearby objects, terrain, and vegetation makes it easier to explain the input values. If you try to be conservative and input excessive values for everything, the energy production forecast will become unduly low, which can lead to incorrect design comparisons and business decisions.

Also, even with the same degradation rate, the results differ depending on whether you assume a constant percentage decline from the first year or assume a somewhat larger initial drop followed by a more gradual decline. For photovoltaic modules, it is common to assume that output changes during the initial period of operation and then declines gradually over the long term. Therefore, when performing long-term forecasts in PVSyst, you should consider whether to treat first-year degradation and long-term (age-related) degradation separately rather than using a simple constant rate.

Basic 1: How to Think About Annual Degradation Rate

When setting the degradation rate in PVSyst, the most fundamental parameter is the annual degradation rate. The annual degradation rate represents how much the output of the power generation equipment is expected to decline each year. In practice, the value used for long-term forecasts is determined by referring to module specifications, warranty conditions, past operational performance, local environmental conditions, and the power plant’s management policy.

When considering the annual degradation rate, what you need to be careful about is that even if the input value looks small, it becomes a large difference over the long term. For example, even a slight decrease in output each year, when accumulated over 20 or 25 years, results in a non-negligible difference in energy generation compared with the first year. In PVSyst’s single-year simulation, since one often focuses primarily on first-year generation, it can be hard to perceive the impact of the degradation rate. However, in long-term forecasts this difference affects cumulative generation, revenue from power sales, investment payback, and equipment replacement planning.

The annual degradation rate is not something that should simply be set conservatively. If an excessively large degradation rate is assumed, long-term power generation will be underestimated more than necessary, which can affect the evaluation of design proposals and decisions on project feasibility. Conversely, if the degradation rate is set too optimistically, future power generation may be overestimated. In practice, it is effective to prepare multiple values—such as a standard case, a conservative case, and an optimistic case—and check how much the results change.

The degradation rate entered in PVSyst should not be just a number but an explainable assumption. When using it in internal documents or submissions, it is important to be able to explain why that value was adopted. Whether it is based on module specifications, on the track record of past projects, or set as a conservative assumption in the business plan will affect how you write the documentation. It is a good idea to record this in project notes or calculation conditions so that when a person in charge reviews it later they can see which judgment led to that value.

Also, the annual degradation rate is not uniform and depends on the type of equipment and the installation environment. In locations prone to high temperatures, susceptible to salt corrosion, affected by snow accumulation or strong winds, or where dirt tends to accumulate, the risk of long-term performance degradation should be assessed carefully. Conversely, in power plants with high construction quality, good drainage and ventilation, and where regular inspections and cleaning are properly carried out, long-term performance retention is more likely. When using PVSyst, it is important not to look only at the on-screen input fields but to adopt an approach that considers both site conditions and operational conditions together.

Basic 2: Treat first-year degradation and long-term degradation separately

A common practical issue when setting degradation rates is whether the first-year drop in output and the age-related degradation from the second year onward can be treated as the same thing. For solar modules, there is a concept that, in the initial phase immediately after installation when operation begins, a certain change in output is expected. After that, it is common to assume that performance will gradually decline over a long period.

Therefore, when considering long-term energy yield in PVSyst, it is easier to separate the decline that occurs only in the first year from the decline that continues each year. When accounting for first-year degradation, look at how much the first-year energy yield falls from the initial nominal value. Meanwhile, for age-related degradation, look at how much it decreases each year from the second year onward. Confusing the two can lead to underestimation or overestimation of long-term projections.

For example, if you expect a certain output decline in the first year and then the same percentage decrease each subsequent year, versus expecting a larger drop in the first year followed by a more gradual decline thereafter, the energy production after 20 years will differ. When creating long-term forecasts using PVSyst results, you need to check from which year degradation is being applied and whether the first-year energy production is before or after degradation.

What practitioners need to watch out for is treating PVSyst’s single‑year results directly as the first‑year generation. If you do not clarify whether the single‑year simulation result is the design annual generation before reflecting degradation or already a value that reflects a specific degradation assumption, there is a risk of double‑counting degradation in the long‑term generation table prepared separately. In particular, when applying an annual degradation rate to PVSyst’s annual generation in a spreadsheet, you must be clear about how the first year is handled.

One advantage of separating first-year degradation from long-term (annual) degradation is that it makes it easier to explain to stakeholders. If you explain to the client and internal approvers that initial output changes are considered in the first year and annual degradation is applied from the second year onward, the assumptions behind long-term forecasts become clear. Conversely, if you simply say “we applied a degradation rate,” it is difficult to convey what declines were expected in which periods.

When setting degradation rates in PVSyst, it can be useful to check the range of settings available on-screen and the output items in the reports, and, as needed, supplement them with external long-term forecast tables. By separating the parts that can be expressed in detail within PVSyst from the parts managed in in-house financial models and generation forecast tables, practical handling becomes easier to organize.

Basic 3: The Impact of Output Degradation to Watch for in Long-Term Power Generation Forecasts

After setting the degradation rate, the next thing to check is how energy production changes year by year. When using PVSyst, it is important not to merely enter the input values and stop, but to examine how much the production decreases in each year and how that affects cumulative energy production.

In long-term power generation forecasts, it becomes easier to understand if you check milestones such as the first year, the 10th year, the 20th year, and the 25th year. If you only look at first-year generation, differences in design proposals and loss conditions are the main factors, but from the 10th year onward the impact of the degradation rate gradually becomes larger. By the 20th or 25th year, even small differences in the annual degradation rate result in clear differences in cumulative power generation.

Moreover, the impact of the degradation rate affects not only energy yield but also the performance ratio and the perceived plant utilization. In PVSyst's result screens you can inspect the flow of losses from solar irradiation to the final usable energy production, but for long-term forecasts you need to understand at which point the year-by-year output decline is being reflected. If you cannot distinguish whether a reduction in energy production is due to long-term degradation, shading, soiling, or temperature, it will be difficult to devise improvement measures after operations begin.

In practice, when creating long-term generation forecasts, it is common to use PVSyst’s reference-year generation as a starting point and then produce future-year generation figures that reflect an annual degradation rate. At that time, checking not only the generation for each year but also the cumulative generation makes the impact of the degradation rate easier to understand. What may look like a small difference on an annual basis becomes a large difference over the entire project period. For decisions on payback, maintenance costs, and equipment replacement, cumulative values are important.

Furthermore, for long-term forecasts it is necessary to consider the degradation rate, power sales conditions, maintenance costs, equipment replacement timing, and so on together. PVSyst itself is a tool strong in generation simulation, but for business viability assessment a financial model is required in addition to generation estimates. By passing generation figures that reflect degradation rates to the financial model, you can create more realistic long-term plans.

When sharing PVSyst results internally, it is easier to understand if you show not only the first-year energy production but also the representative-year production after degradation. For example, being able to explain "the first-year production is high, but it decreases like this over the long term" and "changing the degradation rate changes cumulative production by about this much" increases the transparency of design decisions. The purpose of setting the degradation rate in PVSyst is not the input task itself, but to create these kinds of long-term decision-making materials.

Basic 4: Do not confuse guaranteed values with actual performance

When setting the degradation rate, what you should pay particular attention to is the difference between the guaranteed value and the actual performance. Solar modules may specify warranty terms regarding output performance after a certain period. However, warranty terms are the minimum values the manufacturer guarantees under certain conditions and do not mean the modules will always degrade in exactly that way at an actual power plant.

In practice, whether you can directly use the guaranteed values as the degradation rate in PVSyst must be judged carefully. Guaranteed values are often set as thresholds that become subject to warranty if performance falls below them, and they may differ from the actual average degradation behavior. You may use conditions close to the guaranteed values to create conservative long-term forecasts, but even then they should be documented as "conservative assumptions based on warranty conditions."

On the other hand, an empirical performance value refers to the actual trend of performance degradation observed from similar equipment, past operational records, inspection data, and power generation monitoring results. When there is sufficient track record data, you can set a degradation rate that more closely reflects reality by referring not only to guaranteed values but also to the power generation trends and inspection findings from past projects. However, even when using empirical performance values, the same results are not guaranteed if site conditions differ. Changes in solar irradiance, temperature, humidity, salt damage, snowfall, wind, construction quality, or cleaning frequency will alter how degradation appears.

Those responsible for entering degradation rates into PVSyst must clarify whether they are using warranty values, actual performance values, or internal standard values. If a document simply lists “degradation rate,” it becomes unclear what the figure is based on. When another person later reviews it, if it is not clear whether the value is the warranty’s lower bound, the average from past projects, or a conservative estimate, re-examination and explanation will take additional time.

Also, when using guaranteed values, the conditions for the first year and for the years from the second year onward may differ. If the guarantee allows for a certain drop in the first year and then specifies a constant annual degradation rate thereafter, simply applying the same annual degradation rate across the entire period can lead to calculated results that do not match the guarantee conditions. If PVSyst settings alone cannot fully represent this, it is important to perform a separate calculation in the long-term energy production table and clearly state which assumptions were used.

Not confusing guaranteed values with actual performance values also contributes to the reliability of project feasibility assessments. By separately presenting conservative forecasts based on guaranteed values, expected values based on actual performance, and downside scenarios that account for risks, you can explain a power plant’s long-term plan in a more three-dimensional way. As for using PVSyst, rather than searching for a single correct value, it is important to decide which assumptions to adopt according to the purpose.

Basic 5: Check the range of degradation rates using sensitivity analysis

The degradation rate is a projected value for the future and cannot be determined with complete certainty. Therefore, when performing long-term forecasts in PVSyst, it is practically useful not to draw conclusions based on a single degradation rate but to perform a sensitivity analysis. A sensitivity analysis is the process of checking how much the results change when input conditions are slightly varied.

In a sensitivity analysis of the degradation rate, lower and higher degradation rates than the baseline case are set, and the resulting generation and cumulative generation are compared. This allows you to understand the extent to which the degradation-rate assumption affects the business plan. If a small change in the degradation rate causes a large change in the financial results, it indicates that long-term performance management is particularly important for that project. Conversely, if other factors have a greater impact, you may need to prioritize checking shading losses, soiling losses, equipment selection, and installation conditions.

The benefit of performing sensitivity analysis is that it makes internal explanations and decision-making easier. If you present only a single power generation forecast, you cannot tell how conservative that figure is or how much it might vary. By presenting multiple degradation-rate cases, you can share upside, baseline, and downside outlooks. This makes it easier to align the project owner, designers, contractors, and operations personnel on long-term risk perceptions.

When separating cases in PVSyst for comparison, it is important to keep all conditions except the degradation rate as identical as possible. If meteorological data, tilt angle, azimuth, array configuration, shading conditions, soiling losses, temperature conditions, etc. change simultaneously, you cannot determine whether the difference in energy generation is due to the degradation rate or to other conditions. In sensitivity analysis, the basic principle is to limit the number of conditions you change at one time.

Also, the results of sensitivity analysis should be used not only to look at differences in power generation but also to inform long-term operational policies. Even if the degradation rate is estimated to be on the higher side, some of the reduction in generation can potentially be mitigated through regular inspections, cleaning, checking connections, monitoring module surface conditions, and early detection of abnormal strings. While it is not possible to completely stop degradation itself, it is possible to reduce additional losses caused by factors other than degradation.

Sensitivity analysis is useful not only during the design phase but also after operations begin. By comparing measured power output with PVSyst’s predicted values and checking whether the actual decline in generation is within expectations, you gain a basis for revising assumptions about degradation rates. Rather than stopping after creating the initial simulation, continuously improving it by validating against operational data leads to higher accuracy in long-term forecasts.

Basic 6: Reassess settings based on site conditions and inspection data

The degradation rate set in PVSyst is an assumption made during the planning stage. After the plant actually begins operation, it is important to review it based on data obtained on site. To improve the accuracy of long-term forecasts, it is necessary to link the input conditions used at the design stage with the measured results after operation.

The first things to confirm as site conditions are the weather and the environment. In high-temperature environments, modules and peripheral equipment are prone to thermal stress, and humidity, salinity, dust, snowfall, strong winds, and the like can also affect long-term performance. In addition, conditions such as surrounding vegetation growing and creating shade, soil dust being easily stirred up, frequent bird damage or leaf fall, and poor drainage causing mud splashing can also contribute to reduced power generation. Rather than including all of these in the degradation rate, it is important to separate and record which elements relate to which loss items.

Important inspection data include power generation trends, string-level current and voltage, equipment shutdown history, cleaning history, visual inspection results, and records of anomaly detection. Regularly reviewing these data makes it easier to determine whether a decline in power generation is due to expected aging-related degradation or is caused by specific faults, soiling, shading, or connection failures. Simply observing that annual power generation has decreased does not allow you to decide whether the degradation rate should be revised or whether maintenance actions should be taken.

When reviewing PVSyst settings, compare measured generation with simulated generation. However, it is important to normalize the comparison to the same meteorological conditions. If the actual year's solar irradiation is low, the generation will naturally appear lower. Conversely, in years with higher irradiation, generation may appear higher even if degradation has occurred. Therefore, to confirm degradation trends, you need to examine changes in performance while taking differences in solar irradiation and temperature into account.

By using on-site data, the degradation rate settings in PVSyst become more practical. Numbers that were based on standard values or warranty conditions during the planning stage can be updated to assumptions tailored to the specific power plant once several years of operational data have been accumulated. This improves the accuracy of future energy yield forecasts, maintenance planning, timing of equipment replacement, and decisions on additional investments.

The degradation rate is not something you set once and forget. It should be reviewed according to the power plant’s condition—during design, after the start of operation, several years later, when equipment is renewed, and so on. Practitioners using PVSyst can achieve more valuable generation management by paying attention not only to simulations for initial design but also to re-simulations for operational improvement.

Practical considerations when handling degradation rates in PVSyst

When handling the degradation rate in PVSyst, you need to be careful about overlap with other loss terms. The causes of a long-term decline in power generation are not limited to degradation. There are various factors such as soiling, shading, temperature increases, wiring resistance, equipment downtime, poor connections, installation errors, and vegetation growth. If you lump these into the degradation rate, the simulation may appear conservative, but you will be unable to perform root-cause analysis.

For example, if you have already entered a reduction in power generation due to soiling as a soiling loss, and you also add a similar margin to the degradation rate, you will be double-counting the loss. Similarly, if shading effects are reflected in Near Shading or a 3D scene, and you also assume a large allowance for future vegetation shading in the degradation rate, it becomes unclear which loss is accounted for where. In practice, it is clearer to keep loss items separated as much as possible and to treat the degradation rate mainly as the output decline due to aging.

Also, attention is needed regarding the units and applicable scope of the input values. Whether you enter them as an annual rate, treat them as a decline after a certain period, apply them from the first year, or apply them from the second year onward—if you do not confirm this, the calculations may produce unintended results. In PVSyst’s screens and reports, check which conditions are reflected in which results, and if necessary, it is a good idea to record the contents of the settings screens.

Furthermore, in the submitted materials it is important to be able to concisely explain the assumptions for the degradation rate. Even if a power generation forecast table contains only numbers, readers cannot judge its validity without knowing the assumptions. Clearly stating the basis for the degradation rate, the year it begins to apply, whether there is degradation in the first year, whether a sensitivity analysis was conducted, and the relationship with other loss items will increase the credibility of the materials.

When creating multiple cases in PVSyst, be careful about how you name files and cases. If cases with different degradation rates, different soiling losses, and different shading conditions are mixed together, they can become difficult to compare later. Include information in the case names that indicates which condition was changed, and when sharing internally, make clear which case is the baseline.

Local information necessary to improve the accuracy of long-term forecasts

To improve the accuracy of degradation rate settings, it is essential to accurately capture on-site information as well as desk-based figures. PVSyst is a tool for performing high-precision simulations based on input conditions, but if the site conditions entered are inaccurate, the results will also diverge from reality. Especially for long-term forecasts, not only the information available at initial design but also information related to future operation and maintenance is important.

As on-site information, the most important factors are the terrain, orientation, tilt, and the relative positions of nearby obstructions. If there are buildings, trees, slopes, utility poles, fences, or equipment around the power plant, the impact of shadows varies by time of day and season. Even if the issue appears minor during design, vegetation growth or changes in the surrounding environment during long-term operation can affect energy output. Degradation rate and shading loss are separate factors, but from the standpoint of long-term power generation, both are related to future declines in output.

Next, an important factor is the condition of the installation surface. Ground unevenness, drainage conditions, loads during snowfall, susceptibility to mud splashing, ease of ventilation, and so on all affect the long-term condition of the equipment. In locations with poor drainage, the risk of soiling and corrosion increases, and layouts with poor ventilation may suffer greater losses due to temperature rise. By assessing these conditions on site, you can set more realistic assumptions for PVSyst’s temperature conditions, soiling losses, shading conditions, and long-term forecasts.

As-built information after completion also affects the accuracy of long-term forecasts. If the layout on the design drawings differs from the actual installation positions, shading patterns, array spacing, azimuth, and tilt angles may differ from what was assumed. If the PVSyst model does not match the actual condition of the plant, the baseline generation will be off even before accounting for degradation rates. Therefore, to improve simulation accuracy, accurate on-site positioning, as-built verification, photographic records, and point cloud records are important.

To make long-term forecasts useful for operations, it is important to accurately record the initial condition. If you record the state immediately after installation, you can compare how the equipment itself has changed when a drop in power generation is observed years later. By regularly recording module soiling, tilt of the mounting structure, surrounding vegetation, drainage conditions, ground changes, and so on, it becomes easier to distinguish between performance declines that should be treated as degradation rates and losses that can be improved through maintenance.

To deepen practical proficiency in using PVSyst, it is important not only to perform input operations in the software but also to consider how to measure the site, how to record the data, and how to incorporate them into the model. The degradation rate is a central parameter for long-term forecasts, but if the accuracy of the underlying site information is low, the reliability of long-term energy yield is also reduced. Continuously updating on-site information across the design, construction, and operation phases is fundamental to making PVSyst useful in practice.

Summary: Setting deterioration rates is a key factor that links long-term revenue and maintenance management

Setting the degradation rate in PVSyst is not simply the act of entering a solar module’s output decline. It is an important task for determining how much generation can be expected when operating a plant over the long term, how cumulative energy production will change, and which losses should be mitigated through maintenance and inspections.

When setting degradation rates, you need to clarify how to treat the annual degradation rate, whether to separate first-year degradation from long-term degradation, how to handle warranty values versus actual performance values, whether to perform sensitivity analysis, and whether to revise the figures based on site conditions and inspection data. If you input only numbers while leaving these issues vague, PVSyst results may look tidy but will become documentation that is difficult to explain in practice.

Especially for long-term forecasts, it is important to look not only at the first year’s power generation but also at future years’ generation such as the 10th, 20th, and 25th years. Even if the annual differences are small, they can have a large impact on cumulative generation over the entire project period. Comparing degradation rates across multiple cases and reviewing the standard case, conservative case, and downside case deepens understanding of long-term revenues and maintenance planning.

Also, the degradation rate should be considered separately from other loss items. If you include all factors such as soiling, shading, temperature, wiring, mismatch, and equipment downtime in the degradation rate, you will lose sight of the causes of the reduction in energy production. Because PVSyst allows you to break down and inspect individual loss items, it is important to configure them while being aware of where each loss occurs.

And to improve the accuracy of long-term forecasts, accurate on-site information is essential. By correctly capturing installation location, tilt, orientation, surrounding obstacles, topography, drainage, as-built condition after construction, inspection records, and so on, the input conditions for PVSyst come closer to reality. Connecting desk simulations with on-site conditions is the quickest way to increase the reliability of power generation forecasts.

Therefore, in the design and long-term operation of solar power plants, it is important to accurately measure the site, record it, and keep it in a state that allows later comparison. As a GNSS high-precision positioning device that can be attached to an iPhone, LRTK can streamline acquisition of on-site location information, recording of equipment positions, management of inspection photos, and as-built verification. To make long-term forecasts created with PVSyst useful for actual site management, it is essential to align the assumptions used in the simulation with the conditions on the ground. By correctly setting degradation rates and continuously recording site information, you can improve the accuracy of long-term power generation management and maintenance of solar power plants.