What is PVSyst? Input parameters affecting simulation accuracy

Table of Contents

• What is PVSyst

• Why input parameters affect accuracy

• Input item 1 Meteorological data and site information

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• Input item 4 Inverter and circuit conditions

• Input item 5 Shading geometry and electrical effects

• Input item 6 Loss parameters

• Input item 7 Temperature, aging, and operational conditions

• Practical approach to entering inputs to improve accuracy in the field

• Summary

What is PVSyst?

PVSyst is dedicated software for designing photovoltaic power generation systems, assessing capacity, and analyzing energy production. The official documentation describes it not as a mere rough-estimate tool but as a framework for conducting detailed time-step simulations on a per-project basis while comparing multiple design proposals, including orientation and tilt, equipment configuration, wiring, temperature, shading, and various losses. As a result, a major feature is that it visualizes not only annual energy production but also where losses occur, allowing you to identify weaknesses in the design. When people search for "What is PVSyst" their intent is not simply to learn the name, but to understand how trustworthy it is, what inputs improve accuracy, and where errors may grow. In that sense, what matters is not memorizing a list of the software’s functions, but understanding what to input, at what level of granularity, and how closely to align those inputs with actual site conditions. The official guidance also emphasizes both design-stage simulation and comparison with measured operational data, which suggests the software is meant to be used with both input accuracy and validation accuracy as dual pillars. Do the items affect accuracy?

The accuracy of this software is determined more by how the assumptions are set than by the elegance of the formulas. Even in the official documentation, various losses have default values that appear reasonable in the initial state, but it is recommended that, after completing the first simulation, the loss coefficients be carefully redefined for each project. In other words, getting a number at first and that number being close to actual site conditions are separate issues. You can produce results using the default values, but adopting them as-is tends to lead to calculations with a weak basis for accuracy. The validation page explains that simulation results are influenced by many parameters, with meteorological data and the actual behavior of modules in particular being major sources of uncertainty. While a certain validity for year-scale prediction accuracy is demonstrated, if the input values are off, the results will, naturally, be off by the same amount. In short, PVSyst's accuracy should be regarded not as the accuracy of the software alone but as the overall accuracy that includes input conditions and the quality of operator settings. 1 Meteorological data and site information

The first input items to look at are the site information and meteorological data. In the official tutorials, management of meteorological data, data import, generation of synthetic meteorological data, and consistency checks are treated as independently important topics. Conversely, this means meteorological input is the foundation of power generation forecasts, and if it is weak, even later high-precision shading calculations and equipment settings will not fully raise the overall reliability. Recent official releases also list meteorological data import support and sub-hour analysis as major features, showing the high importance of meteorological input. Even within the same prefecture, weather conditions can vary greatly between coastal and inland areas, between lowlands and high elevations, and between urban and open areas. Therefore, it is essential to correctly set the site's latitude, longitude, and elevation, and to verify to what extent the chosen meteorological data represents that specific site. Official documents also state that year-to-year variations are mainly governed by annual variations in meteorological data, and when considering the range of future forecasts, the validity of meteorological input is a top-level issue. Ta is insufficient if it merely "exists." It is necessary to consider which period to use as the representative year, whether the site's actual conditions match the seasonal characteristics, and whether anomalous years are being overrepresented. Official explanations regarding probabilistic assessments also state that long enough time series of meteorological data are important for handling annual variability, and that the idea of applying simple probabilistic corrections on a monthly or daily basis is not appropriate. Therefore, in practice when seeking higher accuracy, inputs that emphasize representativeness across multiple years are more important than datasets that merely look good for a single year. 2 Installation orientation, tilt angle, and surrounding conditions

Next important are the module plane’s azimuth, tilt, installation configuration, and the surrounding terrain and obstruction conditions. In official documents, project design first defines the orientation and tilt of the receiving surface, any required tracking or row layout, and then deals with distant horizon shading and nearby shading. In other words, the geometric conditions of where and how sunlight is received are the entry point for generation calculations. Depending on these, the temporal distribution of incident irradiance changes. Official materials also show that the irradiance conditions reaching the receiving surface vary with its orientation, and that differences in the installation surface affect the output distribution. A common mistake here is to omit precise azimuth verification because site drawings appear to face south, or to input roof pitch or racking conditions roughly. Even if the annual sum difference appears numerically small, it will manifest as monthly bias or morning/evening output differences, and cannot be ignored in proposals for customers or in self-consumption studies. The issue is not just “whether there is a shadow or not,” but also understanding at what time, on which row, and at what height the shadow occurs. Horizon shading from distant mountain ranges or buildings and nearby shading from local equipment, upstands, fences, or trees require different approaches to input. Replacing all of this at once with a simple loss rate tends to make the temporal distribution of generation and the impact of partial shading drift away from reality. Installation azimuth and surrounding conditions are input items that should be refined as a set, not individually. 3 Module electrical characteristics

The third pillar that affects PVSyst's input accuracy is the electrical characteristics of the module. The official component database tutorials also explain how to define modules and inverters based on their datasheets. In other words, it's not enough to simply select a model name; you need the perspective to check under what assumptions the specification values are registered and whether the required characteristic values are appropriate. In practice, you must always verify that the products used on site match the definitions in the database. The temperature coefficient is one that is easy to overlook. The official documentation shows that various temperature coefficients for maximum power point power, open-circuit voltage, and short-circuit current are used in the model. Even if they appear to have the same nominal output under standard test conditions, if the rate of decline with temperature rise differs, the actual summer output and behavior under high irradiance will change. If you want to improve generation forecasts, it's essential not only to look at nominal capacity but also to check the temperature coefficients.

Input regarding module quality is also important. According to the official explanation, module quality loss is a parameter that represents how reliable the actual module performance is relative to the specification values, and the default value is initialized based on tolerance information. This reflects the idea that nominal values do not necessarily translate directly into the same performance in the field. If this point is not considered during the design stage, there's a risk of projecting the catalog's ideal values directly onto annual energy production, which can later lead to a discrepancy of "it produces less than expected."

4 Power conditioners and circuit conditions

In generation output calculations, not only the module-side but also the power conditioner-side condition inputs directly affect accuracy. Official documentation explains that inverters do not always track the maximum power point, and will enter limiting or stop operations if the input voltage falls outside the allowable range. In other words, a design that goes outside the voltage window will appear in calculation results not merely as a "slight inefficiency" but as a clear loss factor. Do not decide the ratio of DC capacity to AC capacity by intuition. Official materials indicate that an inverter's rating is defined as AC-side output, that the DC power required on the input side is higher by the amount of efficiency, and that the module-side nominal output is based on standard test conditions and is difficult to reach in actual operation. Thus, judging oversizing or margin solely by the apparent capacity ratio may lead to misreading behavior in real environments. It is necessary to design from both voltage and power aspects, taking into account the site's temperature and orientation conditions. Care is also necessary when using equipment that has circuits. Official documentation shows that when there are multiple tracking circuits, each is treated independently, while there are also constraints in simulation. In projects that connect circuits with different orientations or different numbers of modules, you must organize the design philosophy not just to match the total capacity, but to determine which input connects to what. If this is unclear, you will not be able to correctly evaluate how shading and temperature effects manifest in separate circuits. 5 Shadow geometry information and electrical effects

The most important aspect of shadow input is not to represent the visual appearance of shadows, but to represent them in a way that captures their electrical effects. The official description of the module layout feature states that to calculate electrical shading mismatch losses in detail, you must define the exact position of each module in 3D and also associate each module with the string, the subarray, and the inverter to which it belongs. In other words, shadow calculation becomes accurate only when both the geometric model and the electrical connection model are in place. If not, even if the field understanding is "a corner of the roof is shaded only in the morning," the simulation tends to treat it as a simple average loss. In reality, however, partial shading limits the current of specific strings, and even with the same solar irradiance loss rate, the effect on output differs. The official documentation also explains that partial shading of modules changes each module's current–voltage characteristics, and the array loss is determined by the sum of those changes. The accuracy of shadow input affects the reproducibility of losses during peak periods and mornings/evenings more than it does the annual sum. It is that module layout is usually an input that should be finalized at the end of the design. The official guidance also states that changing shadow conditions or system definitions later affects the layout definition and requires revision, so module layout is generally handled at the final stage. In practice as well, if you create a rough layout first and then change the equipment configuration, the consistency of shadow evaluation tends to break down. Shadow input should not be postponed; refining it in the proper sequence is the quickest path to accuracy. 6 Loss parameters

As an input that suppresses power generation, the first thing to address is incident angle correction. The official documentation describes incident angle correction as the phenomenon in which the more obliquely sunlight strikes the glass surface, the more reflection increases and the solar irradiance reaching the cell surface decreases. This is hard to notice if you only look at noon in midsummer, but it is more effective under morning/evening, winter, and low-tilt angle conditions and leads to monthly generation discrepancies. Even if azimuth and tilt are entered correctly, treating this correction carelessly makes the evaluation of received irradiance shallow. The official materials state that soiling strongly depends on rainfall and the surrounding environment, can be set on a monthly basis, and is treated in simulations as irradiance loss. While it is small in residential areas, around farmland and industrial zones it can show seasonal or persistent impacts of a few percent. A common practice in the field is to handle it with a uniform fixed annual value and leave it at that, but in reality many sites change between dry and rainy seasons, so considering it month-by-month is closer to reality. Entering it as a pure percentage alone can be misleading. The official documentation explains that wiring losses are essentially determined by resistance, and the loss rate you set does not directly become the annual loss rate. It also indicates that, in annual results, wiring energy loss often amounts to about sixty percent or so of the nominal loss rate specified, so designing with only a fixed-percent intuition misreads the reality. You need to adopt an approach that thinks in resistance terms, taking into account distance, current, voltage, and circuit configuration. Tch losses and quality losses cannot be ignored either. The official materials state that module mismatch is caused by the module with the lowest current in a string dominating the overall current, and that quality loss is an input representing the confidence in actual module performance. Whether you leave these at their default values or revise them to match project realities will change how the annual generation appears. Especially for projects where you understand actual device variability and procurement conditions, tightening these parameters makes it easier to step away from “desktop ideal values.” 7 Temperature, degradation over time, and operating conditions

Temperature conditions are an input that has a very strong effect on power generation calculations. The official documentation explains that while a module’s nominal performance is specified at 25℃, the actual array temperature during operation is considerably higher, resulting in thermal losses. Furthermore, PVSyst handles temperature in two layers: a steady-state thermal balance model and a transient model that derives the actual temperature from it, making the setting of the U value (the heat transfer coefficient) important. Whether the installation is highly open, close to a roof, or how well ventilated it is, the temperature rise under the same solar irradiance will differ. If you consider simulations using only instantaneous values for a single year, you will overlook long-term changes. The official materials list, as subjects to be addressed, not only long-term module degradation but also the increase in mismatch due to differences in degradation between modules. When creating long-term balances, assessing warranty values, or preparing multi-year generation forecasts, you should not judge based only on first-year results; degradation and operating conditions should be handled as separate layers. Especially in projects that include maintenance planning and performance evaluation, the presence or absence of this input changes the quality of decision-making. How to proceed with inputs to increase the level

What is effective when you want to improve accuracy is not to enter everything in detail from the start. First, enter the site, orientation, basic configuration, and main equipment and run an initial simulation to see where losses are concentrated using the loss diagram. Then, it is efficient to sequentially bring elements such as soiling, wiring, temperature, quality, mismatch, and the electrical effects of shading closer to actual field conditions. The official documentation also recommends treating default losses as a starting point in the initial stage and revising them later according to the system. It is also important not to get priorities wrong. Spending time on detailed electrical-shading calculations while the representativeness of the meteorological data is weak will cause overall accuracy to hit a ceiling. Conversely, if the meteorology and orientation are reasonable and the equipment definitions are accurate, adjustments of shading and losses can bring results quite close to reality. Official probabilistic assessments and validation descriptions also show that the primary causes of annual variability and uncertainty are first the weather and then module-related parameters, so prioritized input improvements are important. By creating a system that can be compared with measured data, the accuracy of subsequent projects greatly increases. Official materials also explain that by incorporating measured data and comparing it with simulation results, you can analyze actual operational behavior and small anomalies. If you do not stop at a one-time prediction but operate in a way that reviews temperature settings, soiling losses, and shading reproducibility based on comparisons with actual performance, PVSyst can be used not merely as an estimation tool but as a design platform that continuously learns.

PVSyst is a professional software that can simulate the power generation of photovoltaic systems in detail, but the essence of accuracy lies not in the software name or number of functions but in how closely each input item is aligned with site reality. Particularly important are meteorological data and site information, installation orientation and surrounding conditions, module temperature characteristics and quality, power conditioner voltage conditions, geometric information of shading and its electrical effects, and various loss parameters. Official documents also indicate that the uncertainty of results in many cases strongly depends on how these input conditions are set. If you want to improve simulation accuracy, it is worth reviewing how site information is collected. If installation location, obstacle positions, and reference points on roofs or within the site remain ambiguous, there are limits to how carefully you can enter data. That is why it is important to adopt an approach that captures high-precision on-site location information alongside generation simulation at the design stage. For example, by utilizing an iPhone-mounted GNSS high-precision positioning device such as LRTK, positional information obtained in the field can be handled consistently across design, construction, and inspection stages, and as a result it becomes easier to establish the assumptions for simulations.