PVsyst Manual Explanation | 4 Points to Note for Meteorological Data Settings

In solar power generation simulations, not only installed capacity, module specifications, tilt angle, azimuth, and loss conditions, but also the meteorological data settings greatly influence how the results appear. Even when working with PVsyst's manual or help, if you proceed without fully confirming the meaning of the meteorological data, you may end up estimating generation based on assumptions that differ from the project's location or installation conditions.

In particular, the handling of site, solar irradiance, timeframe, and temperature conditions is often questioned by designers, construction teams, clients, and internal reviewers. In PVsyst, meteorological data are treated not as mere supplementary information but as the assumptions underpinning the simulation, so it is important to be able to explain which data were selected and for what reasons they were adopted.

This article summarizes four points to check in the meteorological data settings for practitioners who interpret the PVsyst manual in practical work. Rather than the operational procedures themselves, it focuses on the decision points to verify before and after data entry.

Table of Contents

• Basics to grasp before reading the meteorological data settings in the PVsyst manual

• Point 1: Align the site and coordinates with the project conditions

• Point 2: Do not confuse the types and units of irradiance data

• Point 3: Check the period, missing data, and outliers to align the assumptions for annual energy production

• Point 4: Document temperature, wind speed, and surrounding conditions in a way that can be explained on-site

• Summary: Meteorological data settings are the task of explaining the assumptions behind the energy production simulation

Basics to Know Before Reading the Meteorological Data Settings in the PVsyst Manual

When checking the workflow of a generation simulation using the PVsyst manual, many people in charge first look at on‑screen input items such as module capacity, tilt angle, azimuth, system configuration, loss conditions, and report outputs. However, in practice, the meteorological data that forms the foundation of the simulation is the item most likely to have its validity questioned. Meteorological data is an important input condition that can change the assumptions for annual and monthly energy production even under the same equipment conditions.

Meteorological data used in PVsyst mainly involve global irradiance on a horizontal plane, ambient temperature, diffuse irradiance on a horizontal plane, wind speed, and so on. Global irradiance on a horizontal plane and ambient temperature are important as the basic inputs for simulations, while diffuse irradiance on a horizontal plane and wind speed are treated differently depending on the data source and configuration conditions. Some data providers may include information such as humidity, precipitation, snowfall, and wind direction, but not all meteorological files necessarily use the same items.

Therefore, it is not safe to assume that simply choosing a nearby point or leaving the default settings is sufficient. You need to organize which meteorological data were used and what conditions were assumed according to the project’s location, topography, installation method, and the level of explanation required by the recipient. In particular, when presenting power generation figures in external documents, not only the numerical results but also the assumptions from which those numbers were calculated are important.

PVsyst handles meteorological data by associating geographic location information with meteorological files. There are several ways to manage this: site information that includes monthly meteorological conditions; meteorological files with hourly or sub-hourly data; importing external data; and generating synthetic data. When reading the manual, it is important not only to understand what is being set on each screen but also to distinguish whether the data is location information, a meteorological file, or time-series data used for simulation.

For example, on the site-selection screen, you should not only pick a location close to the address, but also verify that the latitude, longitude, elevation, and time zone do not deviate significantly from the project conditions. When importing solar irradiance data, confirm what the source data represent—horizontal irradiance, diffuse component, direct component, or values already converted to a tilted surface. The difference between monthly and hourly data also affects how you interpret annual energy production, evaluate shading, and check monthly trends.

Also, meteorological data should not be judged solely as correct or incorrect. In practice, it is important to be able to explain which assumptions guided the selection, why that data was used, and to what degree of accuracy the results should be interpreted. Power generation simulations do not guarantee future output; they are an exercise in presenting projections based on certain assumptions. Therefore, it is necessary to clearly specify the source of the meteorological data used, the location, the period, whether any corrections were applied, and the input conditions.

If you intend to use the PVsyst manual in practice, merely memorizing the on‑screen operation steps is insufficient. It is important to translate the functions described in the manual into project‑specific checklist items. For meteorological data settings, focusing on four factors—location, solar irradiance, time period, and temperature conditions—makes it easier for even a first‑time operator to establish a clear checking workflow.

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The first thing to check when setting meteorological data is whether the simulation site and the weather-data location match. In photovoltaic power generation simulations, it is necessary to reflect the solar irradiance and temperature conditions at the actual installation site as accurately as possible. If you complete the setup based only on a nearby address or municipality name, you may not be able to fully account for site-specific characteristics such as mountainous areas, coastal locations, basins, or developed land.

Even within the same municipality, meteorological tendencies can vary due to elevation differences, distance from the sea, the influence of mountains, the tendency for cloud formation, and the presence or absence of snowfall. It may not always be possible to provide observation points or weather files that exactly match the site, but even in such cases it is important to verify what area the selected data represents and how closely it matches the on-site conditions.

When checking the location settings in the PVsyst manual, pay attention to the meteorological data selection screen and the site information fields. Verify that the latitude, longitude, elevation, time zone, and other information do not deviate significantly from the actual site conditions. Latitude and longitude affect the solar position calculations. Elevation can be related to differences in temperature and weather conditions. The time zone is important when handling time-series data to confirm the correspondence between irradiance timing and solar position.

In practice, site positions are cross-checked against drawings, survey data, equipment layout plans, property boundaries, and the power plant's representative point. When the plant site is large, deciding where to place the representative point is also important. Whether you designate the approximate center of the site as the representative point, use a location near the main array layout as the reference, or choose which parcel to use as the reference when there are topographical differences, organizing these decisions in advance makes it easier to explain later.

A common mistake in site selection is using data from nearby urban areas or from a different elevation zone as-is and performing calculations even though conditions differ from those at the actual planned power plant site. Data from urban areas may be easier to obtain, but solar radiation, temperature, wind, and snowfall patterns can differ in suburban, mountainous, coastal, and snowy regions. When available data are limited, record the reasons for selecting the most appropriate location and be prepared to provide supplementary explanations as needed.

Also, when a site is on a slope or in a developed/graded area, we check not only the coordinates but also the surrounding environment. If there are mountains, trees, buildings, slope faces, transmission facilities, or the like nearby, local differences in shading and wind conditions may occur that are not reflected in the meteorological data itself. Meteorological data indicate broad-area assumptions for solar radiation and temperature and do not automatically represent all site-specific shading conditions or topographical effects.

In manuals, the process is sometimes described as selecting a site, loading meteorological data, and linking it to the project. However, in actual practice, verification steps before and after that are necessary. First, confirm the project’s official location and determine the representative coordinates to be used for the simulation. Then compare those coordinates with the site information of the selected meteorological data, and if there is any discrepancy, organize the reasons why it is acceptable. Finally, record the chosen site and the rationale for the decision in submission materials and internal memos.

By performing this task, when clients or designers ask why this meteorological data was used, you will find it easier to respond not only with an explanation of the interface but also as a matter of practical judgment. Setting meteorological data is not merely a data-entry task; it is the work of defining the simulation’s assumptions. Carefully verifying the site and coordinates is the first step to improving your ability to explain the power output.

Note 2: Do not confuse the types and units of solar radiation data

One of the most important elements in weather data configuration is solar irradiance. The power generation of a photovoltaic system varies greatly depending on how much sunlight reaches the equipment surface. Therefore, if you set things up without checking the type, units, and temporal resolution of the irradiance data, the calculation results may be off. When reading the PVsyst manual, you need to confirm not only the import procedure but also which type of irradiance you are inputting.

Solar irradiance can be described in several ways, such as global irradiance on a horizontal plane, diffuse irradiance on a horizontal plane, direct irradiance, and irradiance incident on an inclined surface. Because solar power generation equipment is normally installed with fixed tilt and azimuth angles, the irradiance on a horizontal plane is not treated directly as the irradiance on the power-generating surface. In simulations, meteorological data such as horizontal-plane irradiance are used to calculate the irradiance received according to the equipment’s tilt and azimuth angles.

If you don’t understand this, treating values already converted to a tilted surface as horizontal irradiance or entering the same component multiple times can produce unnatural results. When importing external files, it’s important not to rely solely on column names; check the original data documentation and the data provider’s specifications. In particular, abbreviations such as GHI, DHI, DNI, and GTI are similar, so clearly specify which values correspond to which fields in PVsyst.

Checking units is also important. For solar irradiance there are values that indicate instantaneous intensity at a given moment and values that are accumulated over a fixed period. The input fields and interpretation change depending on whether you are working at time-of-day (hourly), daily, monthly, or yearly granularity. For example, when handling time-of-day data you can more easily and finely examine the sun’s position and the effects of shading at each time. On the other hand, using monthly averages or accumulated monthly values can be convenient for estimating annual generation, but they may be less suitable for detailed evaluation of shading by time of day or peak output.

The PVsyst manual explains data formats and required fields in the sections on creating and importing meteorological data. Practitioners need to do more than look at the specified field names as input boxes; they must verify what each column in the source data represents. If the column order, units, time notation, or handling of missing values are incorrect, the file may load but its contents can be inappropriate. The absence of errors on the screen does not necessarily mean it is correct.

A common mistake when setting solar irradiance is omitting unit conversions and checks on temporal resolution. If you import source data without confirming whether the values are timestamped, daily accumulated values, or monthly totals, estimated power generation can become extremely large or small. You also need to verify whether the time stamps are in local time or standard time, and whether they indicate the start of the measurement interval or the end.

The validity of solar radiation can be checked to some extent by examining monthly trends. Solar radiation typically varies with the seasons. In some regions it is higher in summer, while in others some months may be lower due to the rainy season, typhoons, snowfall, or reduced winter sunshine hours. Checking monthly graphs or lists for months that are unusually high or low makes it easier to notice input errors or problems with missing-data handling.

Also, if the source of solar radiation data differs, values at the same location may differ. Data based on observations, data based on satellite estimates, data based on long-term averages — when the creation method differs, the characteristics change as well. In practice, rather than treating any single dataset as absolute, it is important to determine which data is appropriate for the purpose of the project. Submitted materials may place importance on long-term representativeness, whereas comparisons with the actual performance of existing facilities may verify meteorological conditions close to the target period.

Solar irradiance data are the conditions at the core of energy yield simulations. When confirming how to set them in the PVsyst manual, prioritize understanding the meaning of the data over simply filling in input fields. Check the types, units, timestamps, periods, and handling of missing data, and after importing, examine monthly trends and consistency with the generated energy. By making this process a habit, you can move closer to simulations that you can explain in practice rather than accepting calculation results at face value.

Note 3: Check the time period, missing data, and anomalous values to align assumptions for annual power generation

When setting meteorological data, always check which period of data you are using. Since power generation simulations often report annual power generation, you need to confirm that the meteorological data covers one year or can be treated as a representative year. However, meteorological data used in practice include time-series data for a specific year, long-term averages, and representative-year data that combine trends across multiple years. If you set the period without understanding its meaning, the explanation of the results will be ambiguous.

For example, if a particular year had an unusually large number of clear days, a simulation using that year’s weather data might yield higher estimated power generation. Conversely, using data from a year with a lot of rain or cloud cover could result in lower estimated generation. Data based on long-term averages or a representative year are less likely to be influenced by the unusual weather of a single year, but they do not necessarily match the actual generation performance of a specific year. It is important to understand this difference.

When checking meteorological data items in the PVsyst manual, be careful not to overlook how the time periods are handled. Confirm whether the data represent averages over how many years, whether they are monthly averages or continuous time-series data, and whether missing values have been filled in. Especially for data imported from external sources, what appears to be one year’s worth may have gaps in some periods. Calculating with missing periods left unaddressed can produce unnatural drops in monthly energy production or lead to different interpretations of results depending on the imputation method used.

When checking for missing values, first verify that the number of rows and the time span of the data match expectations. For time-stamped data, check that the timestamps cover one year continuously, that there are no missing dates, and that the same timestamps are not duplicated. For monthly data, confirm that all 12 months are present. Although this appears to be a simple task, file conversions or aggregation steps can cause issues such as shifted date columns, duplicated timestamps, or a missing final day.

Be attentive to anomalous values. If solar radiation shows large values at night, daytime values are continuously zero, temperature values are unrealistic, or monthly solar radiation differs extremely from the trends in surrounding areas, input errors or data-processing problems may be suspected. Especially after performing unit conversion, time conversion, or matching columns in external files, it is important to check whether anomalous values have occurred.

In order to align assumptions for annual power generation, it is useful to record in reports and internal documents the period of the meteorological data used. Rather than merely stating that meteorological data were set, document which locations, which periods, which temporal resolution, and which data-completion or interpolation settings were used. If you can explain the meteorological data assumptions when asked by the recipient, it will be easier to communicate the context of the simulation results.

In power generation simulations, we check not only annual totals but also the balance of monthly power generation. Missing or anomalous values in meteorological data can cause unnatural steps in the monthly generation. To determine whether these are within the natural range of seasonal variation or a data problem, it is important to check solar irradiance, temperature, and generated power together. By checking monthly trends, you can more quickly detect configuration errors or data inconsistencies.

Checking the period, missing data, and outliers is unglamorous but an important step that supports the quality of power generation simulations. If you only follow the PVsyst manual's operating procedures, you might feel the work is complete once the data are loaded. However, in practice it is the post-loading checks that determine quality. By verifying that the input data constitute appropriate representative conditions for the project and performing corrections or re-importing as necessary, you can reduce rework in later stages.

Point 4: Record temperature, wind speed, and surrounding conditions in a form that can be explained on-site

In meteorological data settings it's common to focus on solar irradiance, but ambient temperature and wind speed also influence how power generation is assessed. Photovoltaic systems generally produce more electricity with higher irradiance, but higher module temperatures can sometimes reduce output. In regions with high ambient temperatures or installation conditions that limit back-side ventilation, how temperature conditions are treated will affect the interpretation of the results.

Checking the temperature-related sections in the PVsyst manual shows that ambient air temperature, wind speed, mounting type, and thermal conditions all affect the calculations. In practice, rather than treating these as difficult theory, it is important to organize them as assumptions you can explain on site. For example, whether the installation is ground-mounted or rooftop, whether backside ventilation is easily achieved, and whether surrounding structures tend to trap heat will change how you approach module temperature.

Even if meteorological temperature data represent values for nearby locations, local conditions at the actual installation site can differ. This is because heat retention varies depending on the developed site's ground surface, roofing materials, paved surfaces, surrounding buildings, and the orientation of slopes. The same applies to wind speed: broad-area meteorological data do not necessarily reflect the airflow around equipment. When there are windbreaks, buildings, slopes, or densely clustered mounting racks, the actual cooling conditions can change.

However, that does not mean you should finely adjust temperature or wind speed conditions more than necessary. Simulations are not a simple matter in which accuracy always improves as you increase the number of input items; it is important to set justified conditions appropriately. In practice, rather than entering finely guessed values that cannot be verified on site, it can be easier to explain if you use standard conditions and make those assumptions clear.

What you should check regarding temperature conditions is whether the ambient temperatures in the weather data are not extreme, whether the monthly trends look natural, and whether the thermal settings are reasonable for the equipment's installation method. It is common for power generation efficiency to decrease during high temperatures in summer, but how much of an impact to expect depends on module specifications, installation method, ventilation conditions, and simulation settings. Checking the relationship between seasonal solar irradiance and temperature conditions, not just annual energy production, makes the report easier to interpret.

If wind speed is included in the meteorological data, check the validity of the values. Wind can affect module cooling, but it does not fully represent on-site airflow. It is a good idea to document site conditions such as whether the location is open or surrounded by many obstacles, and whether ventilation is ensured by the height and arrangement of the mounting structure. In particular, on rooftops or in confined sites, the thermal environment may differ from that of a standard ground-mounted installation.

It is also important to record surrounding conditions. Meteorological data indicate broad-area conditions, but actual power generation is also affected by local shading, snow, soiling, nearby structures, terrain, and the state of maintenance. These cannot be resolved by meteorological data settings alone, so they need to be distinguished from explanations of the meteorological data. When generation is lower than expected, a record of the configured conditions is indispensable to determine whether the cause is a problem with the meteorological data, the effect of shading, or equipment losses.

What I recommend in practice is leaving a verification memo for the meteorological data settings. The memo should summarize the site used, coordinates, period, type of solar radiation, time granularity, air temperature, wind speed, and any site-specific notes. It does not need to be long, but it is important to leave enough information to understand the rationale later. If the person in charge changes or questions arise after submission, having the documented basis for the settings makes it easier to respond.

Temperature, wind speed, and surrounding conditions, while not as prominent as solar irradiance, are elements that support the explanatory power of power generation simulations. When checking how to set them using the PVsyst manual, do not just enter the on-screen numbers but interpret them in relation to the actual site conditions. Treat meteorological data as broad-area assumptions and site conditions as local assumptions, and by recording both separately you make explanations of the power output more practical.

Summary: Configuring meteorological data is the task of explaining the assumptions for power generation simulations

When proceeding with energy-yield simulations using the PVsyst manual, meteorological data settings tend to be treated as just part of the procedure. However, in practice meteorological data are the important assumptions that underpin the results. Checking whether the measurement location matches the actual site, whether the irradiance type and units are appropriate, whether the period and any missing data present problems, and whether temperature and wind-speed conditions can be explained with respect to the site makes it easier to justify the simulation results.

Especially when presenting power generation in submission materials, the annual power generation figure alone is insufficient. You need to be able to explain which meteorological data were used, why that site was chosen, what period the representative value covers, and what site conditions were assumed. Power generation simulations do not fully guarantee future generation; they provide projections based on certain assumptions. Whether those assumptions can be made explicit determines the quality of the materials as practical documentation.

The four points to pay attention to when configuring meteorological data are location, solar radiation, time period, and temperature conditions. For location, verify the validity of the coordinates, elevation, and the site’s representative point. For solar radiation, check the type, units, temporal resolution, and the month-by-month trends after import. For time period, examine the target year, representative year, long-term averages, and any missing or anomalous values. For temperature conditions, organize temperature, wind speed, mounting method, and the surrounding environment in a form that can be explained on site. Even covering just these four items makes the manual useful not merely as an operational guide but as a tool for practical decision-making.

Also, configuring meteorological data is not a one-time task. If design conditions change, equipment layout changes, or the requirements of the submission destination change, the assumptions behind the meteorological data need to be reviewed. The level of explanation required varies between preliminary studies, basic design, detailed design, pre-construction checks, and post-construction comparisons. Even if rough estimates are sufficient for a preliminary study, submission materials require clear justification. For comparisons with existing equipment performance, it may be necessary to compare against meteorological conditions that are close to the actual period.

What matters for practitioners is not just memorizing the screen procedures in the manual, but preparing so they can explain the results. The numbers from power generation simulations are determined by the cumulative set of assumptions you make. Carefully check the meteorological data settings, and if you document the rationale for your decisions, it will be easier to use them for internal reviews, explanations to clients, and post-construction comparisons.

In planning and constructing a solar power plant, it is necessary to check not only simulations but also on-site surveys, pile locations, installation extents, as-built conditions, progress management, and so on. If you want to connect and manage desktop power output assessments with on-site information, separate and organize meteorological data, design conditions, on-site inspection records, and construction management information, and keep them in a form that allows the rationale to be traced later; this makes it easier to explain the flow from the design stage to on-site verification.