5 Checks to Make When Weather Data Can't Be Found in PVSyst

Table of Contents

• First, organize the causes for meteorological data not being found in PVSyst

• Check item 1: Review the project's latitude, longitude, and place name entries

• Check item 2: Verify whether meteorological data from nearby locations can be used as a substitute

• Check item 3: Confirm that the type and units of the meteorological data are compatible with PVSyst

• Check item 4: Confirm where imported data is stored and how it is linked

• Check item 5: Assess the validity of the data based on terrain and local site conditions

• Decisions to avoid when meteorological data cannot be found

• Tips for stabilizing PVSyst meteorological data settings in practice

• Summary: Checking meteorological data is the first step to ensuring the accuracy of power generation simulations

First, organize the reasons why meteorological data cannot be found in PVSyst

When meteorological data cannot be found in PVSyst, the cause is not necessarily a single one. In many cases, multiple factors overlap, such as problems with place-name searches, mistakes in entering latitude and longitude, the absence of standard data corresponding to the desired location, a mismatched format for importing external data, and a failure to link the project location with the meteorological data location.

What particularly confuses beginners is that, after entering the installation location, they expect the meteorological data for that location to appear automatically. In PVSyst, a project's geographic information and meteorological data are closely related, but the meteorological data that exactly matches the entered address or place name is not necessarily provided automatically. Even if you search by city or region name, you may not find a match if the registered station name is written differently. Also, it is not uncommon for the actual installation site to be distant from the representative station in the meteorological database—examples include mountainous areas, coastal areas, power plant sites under development, factory premises, and idle land.

When weather data cannot be found, the first thing to do is not to assume “there is no data,” but to isolate at which stage the data is missing. The appropriate remedy depends on whether it doesn’t appear in a place-name search, whether you entered latitude and longitude but no nearby candidates are shown, whether you cannot import externally obtained data, or whether you cannot select the data in the project after importing it.

For example, if a place simply does not appear in a place-name search, entering the latitude and longitude directly may resolve the issue. Even when there are few nearby candidate locations, selecting a representative nearby point and checking factors such as elevation, whether it is coastal or inland, and the effects of snowfall or fog can allow you to treat it as approximate data usable in practice. On the other hand, if importing external data has failed, you need to check the column order, units, time intervals, missing values, the type of solar radiation, and so on.

An important point in using PVSyst is not to treat meteorological data as simply “what comes up in a search.” Meteorological data should be selected to match the project conditions, adjusted and validated as necessary, and adopted as simulation inputs. Therefore, especially when data cannot be found, it is necessary to systematically check geographic information, data format, surrounding conditions, and the linkage to the project, in that order.

Also, in PVSyst, a created project, site information, and meteorological data files can be treated as separate configuration items. Therefore, even if you think "the site has been created" and "the weather data has been imported," if they are not correctly selected within the project, they will not be reflected in the simulation. The phrase "weather data cannot be found" can include cases where the data is actually present but not selectable, or where it has been loaded but not associated with the project.

First, it's important to distinguish whether the issue is with the search criteria, with the data itself, or with management after loading. Making this distinction reduces the effort of needlessly changing settings or repeatedly searching for different weather data.

Checklist item 1: Review the latitude and longitude and place name input for the project site

When meteorological data cannot be found, the first things to check are the project site's latitude and longitude and the place-name entry. In PVSyst, the installation site's latitude, longitude, and elevation are used as the criteria for selecting meteorological data. If these are incorrect, candidates from entirely different regions may be shown, or the surrounding data you expect may not be found.

When searching by place-name input, differences in administrative divisions, city names, town names, Romanized spellings, abbreviations, historical names, and so on can cause searches to fail to return the expected results. Even for projects within Japan, the romanization of place names or post-merger municipality names may not match those in the database. For overseas projects, the same place name may exist in multiple countries or regions, so judging by the place name alone may lead to selecting the wrong location.

Therefore, in practice it is important not to rely solely on place names but to verify latitude and longitude directly. On a map, identify and obtain the latitude and longitude for a point near the center of the planned installation site, or for a point that represents the area where the photovoltaic equipment will be laid out. For large power plants, it is better to use a reference point near the center of the array layout or a point representing typical topographic conditions, rather than the site boundary. On sloping sites or sites along valleys, even differences of several hundred meters can change elevation and sunlight conditions, so it is safer not to skip map-based verification.

When entering latitude and longitude, attention to the sign is necessary. Mistaking north for south or east for west will specify a completely different hemisphere. Within Japan, latitude is commonly treated as a positive value and longitude likewise, but for overseas projects west longitudes or south latitudes may be relevant, so always check for the presence of a minus sign. Also be careful about the difference between degrees–minutes–seconds notation and decimal degrees. Entering degrees–minutes–seconds values directly into a decimal degrees field will cause the position to be offset.

For example, if you enter 35 degrees 30 minutes as 35.30 degrees, it will be different from the correct 35.5 degrees. Even if the values look close, they can represent a large difference on a map. If PVSyst cannot find the location correctly, it's a good idea to reverse-look up the latitude and longitude you entered on a map again to confirm that it actually points to the intended installation site.

Elevation is another item that is easily overlooked. If there is a large difference in elevation between the representative meteorological data point and the installation site, it will affect the interpretation of temperature conditions, snow conditions, and solar irradiance conditions. Even if a candidate meteorological dataset is found in PVSyst, using a site whose elevation differs significantly as-is can make it difficult to explain the results. This is particularly important in mountainous areas, plateaus, basins, and regions where elevation rises sharply from the coast to inland, so be sure to check the elevation difference.

Even if a place-name search yields no results, entering the latitude and longitude correctly lets you create a starting point to search for nearby meteorological data candidates. When you are not yet familiar with operating PVSyst, the first step in searching for meteorological data is to correctly set the project site’s location information. Before doubting the meteorological data itself, review whether the installation-site input is correct, whether it can be verified on the map, and whether the elevation is reasonable.

Confirmation Item 2: Verify whether meteorological data from nearby locations can be used as an alternative

If meteorological data for the planned installation site itself cannot be found, the next consideration is whether meteorological data from nearby locations can be used as a substitute. In solar power generation simulations, long-term meteorological data observed on-site is not always available. In many practical projects, representative nearby stations or wide-area mesh data are used to select data that closely match the conditions of the installation site.

However, not just any nearby location will do. You need to consider not only distance but also topography, elevation, distance from the sea, propensity for cloud formation, snow cover, fog, and wind patterns. Even if the straight-line distance is short, simply crossing one mountain can greatly change solar radiation and temperature conditions. Conversely, even if the distance is somewhat greater, if both sites are in the same plain with small elevation differences and similar climatic tendencies, they can often be treated as approximate data in practical work.

When searching for nearby meteorological data candidates in PVSyst, first check the distance from the installation site. Next, look at the elevation of each candidate location. Large differences in elevation can cause significant temperature variations, which affect module temperature and energy production. While solar irradiance is the most important factor for photovoltaic power generation, temperature-related losses also influence output, so it is important not to neglect temperature conditions.

For coastal projects, meteorological conditions can differ between locations close to the sea and inland sites. Sea breezes can suppress temperature increases and alter humidity and cloud tendencies. In mountainous areas, valley topography influences morning and evening shading, fog, snowfall, and the development of local clouds. For rooftop projects on factories and warehouses, roof-surface temperature conditions can be more severe than the surrounding environment, so it is necessary to consider not only the ambient air temperature from meteorological data but also the mounting configuration and ventilation settings.

When selecting alternative sites, we recommend comparing multiple candidates rather than deciding based on just one. On PVSyst, check the annual solar irradiation and temperature trends for several locations and look for values that are extremely high or low. If neighboring candidates differ greatly in annual power generation, carefully judge which set of meteorological conditions is closer to the actual site. In some cases, documenting the reasons for adopting particular meteorological data in internal documents or design notes will make it easier to explain later.

Also, when using an alternative site, the simulation results should include the premise that they "do not fully reflect the actual on-site observations." This is not a bad thing. In practice, it is common to carry out preliminary designs and proposal studies at a stage when long-term on-site observation data are not yet available. What is important is to recognize that you are using nearby data and to be able to explain the distance and differences in conditions.

When meteorological data cannot be found, it’s easy to become anxious, but if you can select appropriate data from nearby sites, it can be sufficiently used for preliminary assessments and comparative evaluations. For precise analyses related to final design, financial appraisal, or warranties, more reliable data or comparisons of multiple datasets may be required; however, a practical approach is first to identify candidate nearby sites and understand how they differ from the installation location.

Checklist item 3: Confirm that the types and units of the meteorological data match PVSyst

If you prepared meteorological data externally but PVSyst cannot find or read it, check that the data types and units match. Meteorological data include multiple elements such as solar irradiance, temperature, wind speed, and humidity, but for photovoltaic simulations the handling of solar irradiance is especially important. Even for irradiance there are different types: global horizontal irradiance, direct normal irradiance, diffuse irradiance, and tilted surface irradiance. You must verify which items PVSyst requires and which columns should contain what in the import format.

A common mistake among beginners is confusing the different types of solar irradiance. If, for example, you enter irradiance on an inclined surface where irradiance on the horizontal plane should be used, have inconsistent relationships between the direct and diffuse components, or fail to check whether the units represent energy per unit time or instantaneous values, then even if the data can be imported the simulation results will look unrealistic. Even if you feel that PVSyst cannot find meteorological data, the actual issue may simply be that required fields were missing during import.

Checking units is also extremely important. Solar radiation is handled differently depending on the temporal resolution of the data, such as hourly values, daily accumulated values, or monthly representative values. Also confirm whether temperature is given in degrees Celsius (℃) or in another unit. For wind speed, the units and the observation height may also differ. If you read data with mismatched units, sometimes an error will occur, and other times no error appears but abnormal results are produced; the latter is more dangerous in practice.

The time interval is also an important point to check. Whether the meteorological data are hourly, every 30 minutes, daily, or monthly affects how you load it and the temporal granularity of analyses you can perform. When conducting detailed time-series simulations in PVSyst, hourly data may be required. Conversely, for a rough assessment you may use monthly data. Make sure you understand the time interval at which the data you prepared were created.

Handling missing values is also important. If external data contains blank cells, abnormal values, symbols, description rows, unit rows, or comment lines, PVSyst may not read it correctly. Even if a spreadsheet appears fine, errors or inconsistencies can occur during import if text appears in the middle of numeric columns or if date formats change due to regional settings. Before importing data, check the header row, column names, date format, time format, missing-value notation, digit grouping, and decimal separator to reduce problems.

When using monthly data, check that all 12 months of the year are present and that leap years and data spanning year boundaries are handled correctly. When using time-series data, verify that the number of hours in a year matches expectations, that timestamps are continuous, and that there are no timezone offsets. Time shifts can affect peak solar irradiance times and shading assessments. This is especially true for data from overseas sources or outputs from external systems, where the handling of standard time, local time, and daylight saving time may be mixed.

Finding meteorological data for PVSyst is not just a matter of selecting a file. You need to verify that the data is formatted in a way that makes sense as input for PVSyst. If loading fails, check not only the file format but also the type of irradiance, units, time interval, missing values, and the date-time notation, in that order. By correcting these, data you thought was unavailable may become usable.

Checklist item 4: Verify the storage location and linkage of imported data

If you have imported meteorological data but cannot select it on PVSyst’s project screen, check the storage location of the imported data and whether it is linked to the project. In PVSyst, site information, meteorological data, projects, variants, etc. are each managed separately. Therefore, simply importing data does not necessarily make it automatically reflected in the project you are currently working on.

A common problem is registering meteorological data under a different site name so that it does not match the project's site information. For example, if the project name contains the power plant name while the meteorological data uses the name of a nearby city, it becomes difficult to find in the list. Check what name the imported data is saved under and which latitude and longitude it is associated with. If there are multiple datasets with similar names, you may end up selecting old data or data from another project.

Management of storage locations is often overlooked. In PVSyst’s working environment, the user data area, project data area, and folders for meteorological data may be separated. When using data migrated from another computer, data copied from a shared folder, or data from past projects, you need to check that they are correctly placed in the locations PVSyst references. Even if files exist, if they are not in locations that PVSyst’s management interface can recognize, they may not appear as selectable options.

Also, after importing external data, you may need to convert and register it as a meteorological data file within PVSyst. Simply placing the original tabular file in a folder may not make it usable as meteorological data within PVSyst. Make sure to load it in the import screen, assign the required fields, save it, and select it as the project’s meteorological data.

After you change the weather data within a project, also confirm that the changes are reflected in the simulation conditions. If variants created earlier with different weather data remain, the project-wide location information and the weather conditions for each variant may not match. Making a habit of checking which weather data are actually being used in the result reports and the settings screens will reduce the risk of performing calculations with incorrect data.

When working in a team, how you name data is also important. Including the site name, country or region, latitude and longitude, data year, and data type when naming or managing data makes it easier to identify later. Conversely, saving files under vague names like "weather", "meteo", or "test" will make it unclear which project the data was used for. As you become more familiar with using PVSyst, the number of configuration datasets increases, so it is efficient to establish naming rules from the outset.

Troubles finding weather data can occur not only when the data itself is missing but also because of registration or linking issues within PVSyst. If you cannot select the data after loading it, check in order the data name, storage location, site/location information, selection state within the project, and the settings for each variant. Simply performing these checks can sometimes resolve the issue without re-importing or recreating the data.

Checklist Item 5: Assess the validity of data based on terrain and on-site conditions

Even if meteorological data can be found, it does not necessarily mean it can be used directly for design. In PVSyst, what matters is not only whether you can select data, but also whether that data is valid for the local site conditions. In particular, for solar power plants, terrain and the surrounding environment have a large impact on energy production. Even if the meteorological data point is nearby, if it does not match the local topographical conditions, it becomes difficult to explain the simulation results.

First, what I want to confirm is whether the installation site is closest to a plain, a mountainous area, a coastal area, a basin, a plateau, or an urban area. In plains, wide-area meteorological data can often be relatively easy to use, but in mountainous areas the influence of elevation differences and valley topography becomes significant. In coastal areas, sea breezes, tendencies for cloud formation, and environmental conditions characteristic of salt-affected regions are relevant. In basins, summer high temperatures, winter cold, and the occurrence of fog can affect power generation and thermal losses.

Next, check whether there are terrain features or structures around the installation site that cast shadows. Meteorological data indicate broad-scale solar radiation conditions, but local shading from mountain shadows, trees, buildings, slopes, utility poles, and equipment support frames must be considered separately in PVSyst’s shading analysis and loss settings. Even if the meteorological data are appropriate, if they do not reflect on-site obstructions, there may be discrepancies with the actual power generation.

Surface conditions also play a role. In snowy regions, not only winter solar irradiance but also generation stoppages due to snow, reflection, and whether snow removal operations are carried out are relevant. In areas with high levels of sand and dust or near farmland, soiling losses can be significant. For rooftop projects that tend to run hot, not only ambient temperature data but also the ventilation conditions behind the modules and the mounting system configuration affect energy yield. In other words, meteorological data are important, but they do not by themselves represent all local conditions.

When assessing the validity of meteorological data, we look at annual solar radiation and monthly trends. If a single month is extremely high, winter solar radiation is unnaturally large, or the pattern differs greatly from nearby areas, we suspect errors in data type, units, or measurement location. In particular, if horizontal-plane solar radiation is confused with tilted-surface solar radiation, or monthly cumulative values are mistaken for daily average values, the figures may look reasonable at first glance but the annual power generation will be unrealistic.

In practice, it is important to be able to explain the input conditions of the meteorological data as well as the output results from PVSyst. In internal reviews or when explaining to clients, if asked "why did you use this meteorological data?", being able to explain that it is from a nearby location, that the elevation difference is small, that the terrain conditions are similar, and that multiple candidate datasets were compared will increase the credibility of the simulation. Conversely, simply using the first data shown makes it difficult to justify the validity of the results.

When meteorological data cannot be found, you ultimately need to decide which data to adopt. That decision should be made not only by whether candidates appear on PVSyst’s screen, but also by taking into account the site’s topography and installation conditions. By looking at the site’s location information, elevation, surrounding environment, shading, snow cover, soiling, and temperature conditions together, you can run simulations that are closer to real-world practice.

Decisions to Avoid When Weather Data Is Unavailable

When meteorological data cannot be found in PVSyst, you may choose data from an arbitrary location to keep the work moving. However, this can lead to significant rework later. In particular, for proposal documents, internal approvals, power generation guarantees, and materials related to investment decisions, the rationale for selecting meteorological data is important.

One mistake to avoid is selecting a nearby location based solely on distance. Even if the straight-line distance is short, weather conditions can differ greatly when mountains lie between the sites, there are large differences in elevation, or coastal and inland climates contrast. Distance is an important indicator, but it is insufficient to judge by that alone.

Another thing to avoid is casually selecting data that show a high annual energy production. When comparing multiple meteorological datasets, you tend to be drawn to candidates that predict larger output, but if you use data that are better than the actual site conditions, discrepancies are likely to appear in later performance comparisons. To maintain design margin, prioritize the validity of the data and avoid overly optimistic conditions.

Also, to avoid loading errors, be cautious about deciding to fill missing or anomalous values with zero as-is. If you set missing solar irradiance to zero, it assumes no generation during that period and will underestimate power output. Conversely, leaving abnormally large values as-is can cause power output to be overestimated. Missing and anomalous values should be checked against the data provider’s specifications and interpolation methods and handled appropriately as needed.

You may sometimes end up selecting data for a different location that has a similar place name. In international projects there can be multiple cities or regions with the same name, and if you don’t check the country, state, or latitude and longitude, you might use data for a completely different place. Even within Japan there are similar place names and historical names, so it’s important to verify coordinates, not just the place name.

It is important not to overlook problems with the meteorological data by looking only at the PVSyst results. If the energy production is higher or lower than expected, before suspecting module settings, PCS settings, or loss settings, you should verify whether the meteorological data are correct. In particular, if the annual solar irradiation is abnormal, no amount of adjustment to other settings will resolve the underlying cause.

When meteorological data can't be found, it's precisely when you should avoid rushing and systematically isolate the cause. By checking, in order, the project location, nearby candidates, data formats, storage locations, and on-site conditions, many problems can be sorted out. Conversely, if you proceed with unsupported substitute data, you'll later need to re-calculate, revise documents, and provide explanations, which will ultimately take more time.

Tips for Stabilizing PVSyst Weather Data Settings in Practice

To ensure stable meteorological data settings in PVSyst during actual work, it is important to follow the same verification procedure every time. If you operate by feel for each project, it becomes easy to miss settings or mix up data. Especially when multiple people use PVSyst or when reusing past projects, standardizing the verification procedure will improve efficiency.

First, at the start of a project, organize the basic information about the installation site. Confirm the site location/address, latitude and longitude, elevation, terrain classification, nearest major city, distance from the sea, and whether there are nearby mountains or valleys. Keeping these as a simple note will serve as a reference when selecting meteorological data. It is important not to complete the work solely on the PVSyst screen, but to cross-check with external maps, design drawings, site photographs, and land development drawings.

Next, compare multiple candidate meteorological datasets. Rather than deciding based on a single dataset, compare nearby locations, locations with similar elevation, and locations within the same climate zone. Check annual solar radiation, monthly solar radiation, and trends in average temperature to see if there are any extreme differences. Comparing multiple candidates clarifies the basis for selection and makes it easier to explain later.

When using external data, it is convenient to decide on formatting rules before loading. Check column names, date formats, time formats, units, handling of missing values, removal of unnecessary description lines, character encoding, and so on, and prepare the data in a form that can be imported into PVSyst. If you perform data formatting manually each time, errors are likely to occur, so it is a good idea to establish a checklist. In particular, the units of solar irradiance and the time interval are items you should always verify.

Within a project, manage meteorological data names so they are easy to understand. Use names that indicate the project name, site name, data type, year, and whether corrections have been applied, so that they are easier to identify when reviewed later. Because an increase in similarly named data can lead to mistaken selections, it is also important not to leave unnecessary test data or old data lying around.

After the simulation, check the weather data used in the report. Don’t just look at the result screen and consider it finished; check which location’s data is being used as an input condition and whether the annual insolation and temperature values are reasonable. When comparing multiple design proposals, confirm that the weather data are the same. If the weather data differ, you will be comparing differences in weather conditions rather than differences in module capacity or racking conditions.

Also, as you become more comfortable using PVSyst, you may want to examine differences in energy yield in greater detail, but it is important to first reinforce the reliability of your input data. Checking items in the order of meteorological data, site location, azimuth, tilt, shading, and loss settings makes it easier to sort out variations in the results. Meteorological data is both the first configuration item and the basis for all calculations, so handling it carefully alone will improve the overall quality of the simulation.

The ability to respond when meteorological data cannot be found in PVSyst is not merely an operational skill. It requires reading the conditions of the design site, understanding what the available data means, and making reasonable assumptions. For practitioners, the ability to grasp on-site conditions is as important as operating the interface.

Summary: Verifying meteorological data is the first step in ensuring the accuracy of power generation simulations

When meteorological data cannot be found in PVSyst, first check the project's latitude and longitude and the place name input, then consider using a nearby site as an alternative. If using external data, review the type of irradiance, units, time interval, missing values, and date/time format, and after import verify the save location and that the data are linked to the project. Finally, taking terrain and local site conditions into account, judge whether the data are appropriate for the installation location.

Meteorological data is the starting point for PVSyst power generation simulations. If there are errors here, subsequent array configuration, PCS selection, loss settings, shading analysis, and report preparation will be affected. Conversely, if the rationale for selecting the meteorological data is clear, it becomes easier to explain the simulation results and more persuasive in internal reviews and when explaining to clients.

In practice, long-term observational data for the actual planned installation site is not always readily available. Therefore, how to choose nearby data, how to account for elevation and terrain differences, and how to prepare external data are important. When learning how to use PVSyst, it is important not only to learn the on-screen operations but also to acquire the criteria for selecting meteorological data.

Moreover, accurately capturing on-site location information is indispensable for verifying the validity of meteorological data. If the locations of the planned solar power plant site, rooftop equipment, developed land, slopes, and nearby obstructions can be recorded correctly, it becomes easier to organize the site conditions, shadow analysis, and design parameters used in PVSyst. What is useful here is a positioning environment that can acquire high-precision location information on site.

LRTK is a high-precision GNSS positioning device that can be attached to an iPhone. Because it can record planned installation sites, surrounding structures, and terrain checkpoints on site with high accuracy, it can be used to organize installation locations for use in PVSyst, verify the positions of nearby objects that cause shading, and create on-site survey records. It is not a device that acquires meteorological data itself, but being able to accurately record on-site location information that serves as the basis for simulations is a great help in preparing PVSyst input conditions. Rather than managing meteorological data, design conditions, and on-site positioning information separately, creating a system that allows consistent verification from on-site surveys through simulation can improve the accuracy and explanatory power of photovoltaic system design.