What is PVSyst? A Beginner's Primer on Power Generation Forecasting

Table of Contents

• What PVSyst is used for

• Why PVSyst is used for energy yield prediction

• The energy yield prediction workflow beginners should understand first

• Main input conditions handled by PVSyst

• Considerations for losses that are easy to overlook in energy yield prediction

• Key indicators to check first on the results screen

• Common pitfalls beginners are likely to encounter

• Precautions when using PVSyst results in practice

• How the accuracy of site conditions affects energy yield prediction

• Summary

What is PVSyst used for?

PVSyst is power generation simulation software used to predict the energy yield of photovoltaic power systems and to organize design parameters and loss conditions. In planning a solar power system, various factors affect energy yield, such as installation location, solar irradiance, temperature, panel orientation, tilt, equipment configuration, wiring, shading, and loss conditions. PVSyst is used to input these conditions and to check annual and monthly energy yields, the breakdown of losses, and indicators related to system performance evaluation.

Many of the people who search for "What is PVSyst" are practitioners who have begun work related to designing photovoltaic systems, conducting project feasibility studies, forecasting energy production, preparing proposal documents, and performing technical checks. At the first stage, they are often bewildered by the number of screens and input fields, unsure what to enter, which results to look at, or how accurately predictions can be made. However, to summarize PVSyst's role in one sentence: it is a tool for examining, with supporting evidence, under what conditions and to what extent a solar power generation system can produce electricity.

However, using PVSyst does not automatically produce the correct energy production. If the input conditions are inaccurate, the results will also be inaccurate. Only by appropriately reflecting the site's solar irradiation conditions, topography, shading effects, equipment layout, device specifications, and operating conditions will the output approach predictions that can be used in practice. In other words, it is easier to understand PVSyst not as "a device that provides the answer" but as an analysis environment for organizing conditions and quantitatively checking forecasts of energy production.

For power generation forecasting, simply multiplying installed capacity by solar irradiance is insufficient. In actual power generation, losses accumulate: losses before sunlight reaches the panel surface, losses when the panel converts sunlight to electricity, output reduction due to temperature rise, wiring losses, losses from conversion equipment, shading effects, soiling, degradation over time, downtime, and so on. In PVSyst, you can check these losses step by step, making it easier to explain where generation is being reduced.

What is important for beginners is not to try to learn only how to operate PVSyst. Simply filling in the input fields on the screen will not allow you to judge the meaning of the results. First, understand which factors determine a photovoltaic system’s energy yield, and then look at how PVSyst handles each of those factors. That will allow you to read the numbers and loss diagrams shown on the results screen not as a mere list of figures but as material for verifying the validity of the design conditions.

Why PVSyst Is Used for Power Generation Forecasting

In planning solar power generation projects, generation forecasts form the basis for business and design decisions. Unless you understand points such as how much generation can be expected annually, how large seasonal variations are, whether generation efficiency relative to installed capacity is reasonable, and whether the impacts of shading and temperature are not excessive, you cannot judge the quality of a design. The reason PVSyst is used is that it can organize each of these conditions one by one and consolidate the results into a report that is easy to review.

In the field of energy yield forecasting, it is important to be able to explain results to stakeholders. For example, if the annual energy yield in a design proposal is lower than expected, you cannot consider corrective measures unless you can explain whether the cause is solar irradiance, shading, equipment configuration, or temperature losses. PVSyst allows you to trace input conditions and the flow of losses, making it relatively straightforward to identify the causes of a reduced energy yield. This makes it easier for designers, construction personnel, project owners, financial stakeholders, maintenance personnel, and others to discuss matters based on the same assumptions.

It is also suitable for comparing different scenarios when conditions change. By comparing multiple cases — for example, changing the panel tilt angle, changing the installation orientation, changing the combination of equipment capacities, or revising the shading conditions — you can identify which factors have the greatest impact on power generation. Beginners will find it easier to get a feel for power generation forecasting by altering conditions little by little and seeing how the results change, rather than trying to find the optimal solution from the start.

PVSyst not only produces annual energy yield estimates, but also serves to record the design assumptions. For energy yield forecasts, it is important afterward to know which meteorological data was used, what system capacity was assumed, which loss rates were set, and to what extent shading was taken into account. If only the forecast results remain and the assumptions are unknown, those figures cannot be properly evaluated. PVSyst reports are also used as documentation for stakeholders to verify these assumptions.

On the other hand, PVSyst’s results are not absolute values but predictions based on the conditions you set. Actual power generation varies due to factors such as year-to-year weather variation, snow, soiling, individual differences in equipment, operational shutdowns, and changes in the surrounding environment. Therefore, it is important not to read PVSyst’s results as “this will definitely be the amount of generation,” but rather as “given these assumptions, this amount of generation can be reasonably expected.” Simply adopting this perspective will significantly deepen your understanding of power generation forecasts.

The Power Generation Forecasting Process Beginners Should Understand First

The basic flow of power generation forecasting proceeds in the following order: decide the conditions of the installation site, set the meteorological data, input the equipment configuration, account for shading and losses, and check the simulation results. For beginners, rather than jumping straight into detailed loss settings, it is important to grasp this overall picture first. If you understand what is being decided at each stage, you can reduce input errors and misinterpretation of the results.

The first thing you should decide is the installation location. The electricity output of a solar power system varies greatly by location. Factors such as solar irradiance, temperature, latitude, surrounding terrain, the presence or absence of snow, and how prone the area is to cloud cover all affect generation, so correctly specifying the installation site is the starting point. If the site is set incorrectly, no matter how accurately you enter the equipment configuration, the predicted generation will diverge from the actual on-site conditions.

Next, configure the meteorological data. Meteorological data includes information such as solar irradiance and temperature, which form the basis for power generation calculations. What is important here is to be aware of the types of data, the period covered, and their representativeness. Whether you use past average meteorological conditions or observed values from a specific period will change the meaning of the results. Beginners tend to treat meteorological data as mere input fields, but they need to understand that this information is the foundation of power generation forecasts.

Next, configure the equipment layout such as solar panels and power conversion devices. By entering the panels' capacity, number of units, series or parallel configuration, combinations with converters, installation tilt, orientation, and so on, the system calculates how much of the solar radiation received by the equipment can be converted into electrical power. Here, since misreading device specifications or unit errors can easily affect the results, it is important to verify consistency with catalog values and design drawings.

Next, set the shading and loss conditions. Surrounding buildings, trees, terrain, and shading between racking rows are factors that reduce power generation. Also consider losses such as temperature, soiling, wiring, conversion, degradation, and downtime. What is difficult for beginners is deciding which losses to anticipate and to what extent. Here, you need to combine site surveys, design conditions, past performance, and general technical knowledge to aim for settings that are neither excessive nor insufficient.

Finally, review the simulation results. Instead of looking only at the annual generation, check the monthly generation, the breakdown of losses, the balance of generation relative to installed capacity, and whether any extreme losses have occurred. If you find anything unusual in the results, return to the input conditions and check. Power generation forecasting is not a one-time task of entering data and stopping; it is a process of iterating between conditions and results to improve accuracy. Adopting this iterative mindset is the first step in progressing from a beginner to a practitioner.

Main input conditions handled by PVSyst

PVSyst handles a wide range of input conditions, but what beginners should grasp first are the installation site, meteorological conditions, system capacity, installation azimuth, tilt angle, equipment configuration, shading, and loss conditions. Each of these directly affects power generation. You don’t need to understand everything perfectly before you start operating the software, but knowing which input affects what will make it easier to interpret the results.

The installation location is the starting point for power generation forecasts. If latitude or longitude change, the sun’s altitude and azimuth also change, and the amount of solar radiation received over the year differs. Especially on large sites or in mountainous areas, solar radiation conditions can vary within the same municipality due to terrain and elevation. If the location is set roughly, it may not sufficiently reflect the actual site conditions.

Among meteorological conditions, solar irradiance and air temperature are particularly important. Solar irradiance is the basis of power generation, and temperature is related to reductions in panel output. In general, the more sunlight there is, the greater the power generation, but in high-temperature environments the panel temperature rises and conversion efficiency can decrease. Therefore, it is necessary to consider not only solar irradiance alone but also temperature conditions in combination.

Installed capacity is an important parameter that indicates the scale of a power plant. The relationship between the total capacity of the solar panels and the capacity of the conversion equipment affects the amount of power generated and the occurrence of output limitations. Increasing panel capacity may seem to simply increase generation, but if the capacity balance with the conversion equipment is poor, output can be constrained during certain periods. PVSyst allows you to check the effects of such capacity balance.

Installation orientation and tilt angle also have a major impact on energy production. In many regions, the closer to south-facing the installation is, the more annual sunlight it receives; however, site shape, slopes, building roofs, connection conditions, and other factors can make it impossible to install in the ideal orientation. The approach to tilt angle also varies depending on whether you prioritize annual energy production or aim to adjust seasonal imbalances in generation. PVSyst allows you to compare these conditions by varying them, making it useful for evaluating design proposals.

Shadow conditions are aspects that beginners are likely to overlook. Shadows do not simply reduce power generation; their impact can vary greatly depending on the time of day and the season. For example, if shadows appear only in the morning and evening, if shadows extend longer in winter, or if parts of nearby equipment cast shadows, the effect on power generation will differ according to local conditions. Underestimating shadows can cause actual power generation to be lower than predicted.

Loss conditions take into account wiring, conversion, temperature, soiling, degradation over time, and downtime. Each of these may seem small on its own, but when they accumulate they can have a large impact on annual energy production. Beginners tend to enter loss rates arbitrarily, but loss settings are a critical factor that determines the reliability of generation forecasts. Avoid unfounded optimistic settings and choose values that match site conditions and design parameters.

Considerations for Losses Often Overlooked in Power Generation Forecasting

What matters in forecasting power generation is understanding how output declines. In solar power generation, the energy from the sun does not become electrical energy directly. It passes through the atmosphere, reaches the panel surface, is converted into direct current power inside the panel, travels through wiring, and goes through conversion equipment to become alternating current power that can be used. Losses occur at each of these stages.

One point beginners often overlook is that losses are not caused by a single factor but by multiple elements that occur sequentially. For example, there are shading losses, reflection losses, temperature-related losses, wiring losses, conversion losses, and losses due to equipment downtime. Looking at just one of these alone does not explain the overall energy production. When reading PVSyst’s loss diagrams and result screens, it is important to check, in order, at which stage and to what extent energy is being lost.

Temperature losses are an aspect you should particularly understand. Solar panels produce more power the more sunlight they receive, but at the same time the panel temperature rises. When panel temperature increases, output generally decreases. Therefore, even in regions with strong sunlight, temperature losses can be large depending on ambient temperature and ventilation conditions. Differences such as rooftop versus ground-mounted installation, mounting height, and airflow also affect temperature conditions.

Losses due to shading are also important. Shadows not only reduce power generation but also affect the electrical balance. If only some panels are shaded, the reduction in power generation can be greater than a simple area ratio would suggest. In addition to nearby buildings and trees, you should check for shading from adjacent panel rows, equipment, fences, and the terrain. Especially in winter, when the sun's altitude is lower, shadows that are not a problem in summer can have a major impact.

Soiling losses are another item that beginners tend to underestimate. Dust, pollen, fallen leaves, bird droppings, and residual dirt after snowfall reduce the light reaching the panel surface. The degree of soiling varies depending on the region, surrounding environment, rainfall, cleaning frequency, and installation angle. When forecasting power generation, if soiling is not taken into account at all, discrepancies with actual results are likely to occur, so an estimate based on the local environment is necessary.

Wiring losses and conversion losses are related to system design. When cables are long or currents are high, wiring losses increase. Even in conversion equipment, efficiency varies with load factor and operating conditions. Because these can be improved during the design stage, we sometimes review equipment layout and device capacities based on PVSyst results. Power generation forecasts are not merely estimates; they also provide clues for design improvements.

Metrics to check first on the results screen

Because the PVSyst results screen displays many figures, beginners can easily be unsure where to start. The items you should check first are annual energy production, monthly energy production, the plausibility of energy production relative to the system capacity, the breakdown of losses, and representative performance indicators. Rather than trying to understand all the numbers at once, it is important to grasp the big picture first.

Annual energy production is the figure that tends to attract the most attention. In feasibility studies and proposal documents, how much energy can be produced over a year is important. However, it is risky to make judgments based solely on annual generation. Even with the same annual generation, differences in seasonal distribution, the nature of losses, and the relationship to installed capacity can change how a design is evaluated. Annual generation should be checked as a starting point, and its breakdown examined afterward.

Monthly power generation helps to understand seasonal variations. Solar power generation changes month to month depending on irradiance conditions and temperature variations. In some regions, even when solar irradiance is high in summer, losses due to high temperatures can be significant. In winter, although the amount of solar radiation is low, temperature conditions can sometimes be favorable. By checking monthly changes, you can grasp the seasonal characteristics of power generation.

The breakdown of losses is extremely important for evaluating results. If power generation is low, it is necessary to determine whether the cause is insufficient solar irradiance, shading, temperature, or equipment configuration. A loss diagram shows where and to what extent the solar energy is reduced in the process from incoming solar energy to the final electrical output. Beginners should prioritize understanding the flow by which generation decreases rather than memorizing loss figures.

Check the balance between power generation and installed capacity. If the generation is extremely high or low, there may be errors in the input conditions. For example, check whether there are any anomalies in the site settings, installed capacity, tilt angle, azimuth, loss rate, or the handling of shading. If the results differ from expectations, it is important not to draw immediate conclusions but to go back and verify the input conditions.

Performance indicators are used to assess the overall efficiency of an installation. Rather than judging solely by the indicator values, interpret them together with the installation and design conditions. In locations with heavy shading, sites with constraints on tilt or orientation, or in high-temperature environments, there may be reasons for lower indicator values. Conversely, if results appear unnaturally good given the conditions, the loss settings may be too optimistic. The better the results, the more necessary it is to verify the underlying assumptions.

Common Pitfalls for Beginners

The biggest pitfall for beginners is entering values without understanding what the input fields mean. PVSyst lets you configure many parameters, but if you enter them without understanding each one's meaning, the simulation may appear to complete while producing results that are difficult to use in practice. At first, it is more important to focus on how the values you enter affect energy generation than on fine operational details.

A common stumbling block is the handling of meteorological data. Meteorological data are the foundation of power generation forecasting, but beginners may assume that any dataset will produce the same results. In reality, if solar irradiance or temperature data change, the power generation will change as well. Using data without considering its representativeness, distance from the site, elevation difference, and regional characteristics can cause discrepancies with actual power generation.

Another common stumbling block is entering the equipment configuration. The number of panels, the series count, the parallel count, and the capacity of power conversion equipment are related to the electrical design. If you enter these incorrectly here, assessments of output limits and losses will be affected. Beginners tend to think it is enough to match only the installed capacity, but in reality the connection configuration and the operating range are also important. You need to develop the habit of entering data while cross-checking against design drawings and equipment specifications.

Shading is also a difficult aspect to handle. Even if it is known that there is shading on site, the results change depending on how it is modeled. If the heights and positions of surrounding obstructions, the terrain, the spacing between panel rows, and so on are not appropriately represented, the impact of shading cannot be correctly evaluated. In particular, if shading is lightly estimated with an insufficient site survey, predicted power generation tends to be larger than actual output.

Setting loss rates can also be a stumbling block. Soiling, wiring, downtime, degradation, and similar factors may lack detailed information at the initial stages. Even in that case, rather than choosing an unreasonably small value without justification, you need to set values that take site conditions and operational conditions into account. In power generation forecasts, stacking optimistic numbers will make the final predicted generation optimistic as well. When using these forecasts for business decisions, it is important to set assumptions that you can explain.

Care is also needed in how you read the results. Beginners tend to feel reassured simply by checking whether the annual energy production is close to the expected value. However, the numbers may merely happen to look plausible, and the breakdown can reveal inconsistencies. You need to check monthly generation, loss diagrams, capacity balance, the effects of shading, and so on, and determine whether the results are physically plausible. To master PVSyst is not just to become familiar with its operation, but to be able to explain the validity of the results.

Practical considerations when using PVSyst results in practice

When using PVSyst results in practice, it is important to accurately convey the meaning of the predicted values. Power generation forecasts do not guarantee future generation. They are estimates based on the specified meteorological conditions, equipment conditions, and loss assumptions. Actual generation will vary due to year-to-year weather differences, equipment condition, maintenance status, downtime, and changes in the surrounding environment. If these assumptions are not shared with stakeholders, the forecasted values may take on a life of their own.

In practice, you are expected not only to present the figures shown in the report but also to be able to explain their rationale. If you cannot explain why these meteorological conditions were used, why this loss rate was chosen, why this layout was selected, or how you assessed the impact of shading, the reliability of the power generation forecast will not improve. PVSyst results need to be evaluated together with the input conditions.

Also, when comparing multiple options, it is important to standardize the comparison conditions. If one option assumes losses conservatively while another assumes them lightly, it will not be a pure design comparison. When changing things like panel layout, tilt angle, equipment capacity, or shading conditions, you must clearly state what is being changed and what is being held constant. If the assumptions for the comparison are ambiguous, you will not be able to tell whether the differences in the results are due to the design or to the input conditions.

Power generation predictions are used differently in the early design stage, detailed design, pre-construction checks, and post-operation evaluation. In the early design stage they are used to confirm rough potential, while in detailed design they are used to detail equipment configuration and losses to increase accuracy. Before construction they are used to verify consistency with drawings and site conditions, and after operation they are used to compare with actual generation and serve as the basis for analyzing differences between predicted and actual output. Even with the same PVSyst results, the way they are interpreted changes depending on which stage they are used in.

Especially when using it for project feasibility studies, it's important not to overestimate the energy generation. The larger the estimated generation appears, the better the business plan looks, but if actual output falls short of forecasts it will affect the project's financial performance. When site conditions are uncertain, conducting sensitivity analyses to understand how much generation would change if solar irradiance or loss conditions vary can provide reassurance. PVSyst can also be used for such condition comparisons.

The accuracy of on-site conditions affects power generation forecasts

When performing energy yield predictions in PVSyst, the accuracy of on-site conditions is critically important. No matter how carefully you configure the settings in the software, if the site's location, topography, obstacles, installation area, tilt, orientation, or shading conditions are inaccurate, the reliability of the results will be reduced. Energy yield prediction may appear to be a desk exercise, but in reality it depends heavily on the quality of the site information.

If the installation site's position information is inaccurate, it affects solar irradiation and shading evaluation. In particular, in mountainous areas, on slopes, or where there are nearby buildings or trees, even a difference of a few meters (a few ft) can change on-site conditions. Accurately identifying land boundaries, equipment layout, access roads, and the positions of surrounding obstacles improves the accuracy of the conditions entered into PVSyst.

Also, understanding the terrain is important. On flat land you can consider the layout relatively simply, but on sloped land the panels’ orientation, height, row spacing, and the way shadows extend become more complex. If you design without correctly grasping the site’s elevation differences, unexpected shading or construction constraints may be discovered later. To improve the accuracy of power generation forecasts, you need to make the desk-based design conditions match the actual site conditions as closely as possible.

In shadow assessments, the accuracy of on-site measurements is also important. If you do not know where surrounding buildings, trees, utility poles, slopes, and existing equipment are located and how tall they are, you cannot properly reflect the impact of shadows. Relying solely on what you observe on-site can cause you to overlook changes in shadows due to season and time of day. By measuring location and height information and incorporating it into the design data, you can produce power generation forecasts that are easier to explain.

Thus, in power generation forecasts using PVSyst, acquiring on-site data is as important as the settings within the software. Differences in predicted power generation arise not only from differences in calculation methods but also from the accuracy of the on-site conditions entered. Beginners tend to focus on on-screen operations, but in practical work the quality of the on-site information that supports "what to input" determines the results.

In site surveys, having a setup that can efficiently record location information, elevation, the planned installation area, obstacles, and the surrounding environment makes it easier to organize the assumptions for power generation forecasts. For linking power generation forecasting, design, construction, and maintenance, consistency between on-site coordinate data, photos, notes, and drawings is also important. To bring PVSyst results closer to practical application, it is essential to measure the site accurately and establish a workflow that reflects that information in the design conditions.

Summary

PVSyst is simulation software for predicting the electricity generation of photovoltaic installations and for organizing design conditions and loss parameters. What beginners should understand first is that PVSyst is not merely a tool for producing annual generation figures, but a tool for checking which conditions determine generation, at which stages losses occur, and under which assumptions the results are based.

In predicting power generation, many factors are involved, such as the installation site, meteorological data, system capacity, azimuth, tilt angle, equipment configuration, shading, temperature, wiring, soiling, downtime, and degradation. By using PVSyst, you can organize these conditions and check annual energy production, monthly generation, breakdown of losses, and performance indicators. However, the reliability of the results is heavily dependent on the accuracy of the input conditions. It is important not only to become familiar with the operation but also to be able to explain the basis for the input values.

Beginners do not need to try to understand every detailed setting perfectly from the start. First, it is important to grasp the basic workflow: choose the installation location, set the weather conditions, enter the equipment configuration, reflect shading and losses, and review the results. Furthermore, if the results differ from expectations, instead of looking only at the annual generation, check the monthly generation and loss diagrams and take an investigative approach to find the cause, which will deepen your understanding.

When using PVSyst in practice, it is also important not to treat predicted values as guaranteed values. Energy production fluctuates due to year-to-year weather variations and operating conditions. PVSyst results should be read as a reasonable estimate based on the conditions you set, and must be explained to stakeholders together with the underlying assumptions. In particular, for business feasibility studies and design comparisons, aligning input conditions and clarifying the rationale for loss settings will increase the credibility of the results.

To improve the accuracy of power generation forecasts, grasping site conditions is essential. If information such as installation location, topography, obstacles, shading, site boundaries, and the planned equipment area remains unclear, no matter how carefully you configure settings in PVSyst, the forecast may end up differing from actual on-site conditions. In solar PV planning, it is important not to separate desk-based simulations from on-site surveying, and to reflect accurate field information in the design conditions.

If you want to improve the accuracy of on-site surveys and efficiently obtain location information that can be used for generation forecasts and design studies, utilizing LRTK (iPhone-mounted high-precision GNSS positioning device) is also effective. If the planned equipment footprint, obstacle locations, and verification points on site can be recorded with high precision, it becomes easier to organize the assumptions to input into PVSyst, and the explanatory power of the generation forecast is enhanced. To ensure generation forecasts do not remain mere desk calculations but lead to practical, site-specific decisions, it is important to combine PVSyst simulations with high-precision on-site positioning.