Features

The Solargis platform brings all Solargis products under one roof, offering one environment for solar project development. Solargis Prospect and Solargis Evaluate, both part of the Solargis platform, ensure reliable decision-making from early screening to securing project financing. 

In Prospect, you can explore and quickly assess and compare multiple locations to identify the most promising ones using reliable solar resource data. Once a location is selected, you can proceed to Evaluate, where high-resolution data is used for detailed project analysis and bankability assessments - all without needing to leave the Solargis platform. 

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Access Solargis Evaluate alongside other Solargis solutions through a single, streamlined interface. Manage users and team collaboration seamlessly in one platform. Easily add or remove team members, and onboard new users with just a few clicks, ensuring everyone has the access they need to work efficiently.

Keep track of all your projects through Solargis Home. View your complete project list, see where each project is assigned, track the latest activity, and access everything from a central platform. Filter out your most recent projects, restore archived projects and manage your labels.

More about Solargis Home->

Within your Solargis Evaluate tier subscription, the purchased credits give you flexibility in your spending. If you are unsure whether you want to use TMY or Time Series data at the moment of purchase, you can decide what dataset you want to use at the time of project activation. 

Once you run out of credits, you can buy additional ones, or if you are left with remaining credits at the end of your subscription period, you can opt to transfer them into your next subscription. This is valid only on condition that you remain in the same subscription plan.​

See pricing ->

Early-stage evaluation
As you enter the initial stages of PV project assessment, you can initiate the “Early stage” phase. This phase marks the beginning of the evaluation process, allowing for preliminary planning to ensure the project's viability.

TMY P50 data allows for a balanced view of expected performance without the need for Time Series data, making it an efficient choice for preliminary decision-making before moving into more detailed, high-resolution analysis.

Full evaluation
When you decide that it’s time to move the project further, you can upgrade to full evaluation any time. In this phase you can work with sub-hourly Time Series data and gain access to the full suite of Solargis Evaluate features, such as generating bankable reports that help with securing project financing. 

Within our platform, you can now request consultancy services or additional data services directly, saving time on email communication and file exchanges as the project data is already included in the request. 

You can directly request

• Data services:

  • High temporal resolution data: 1-, 5-, 10-minute data
  • TMY data (Pxx): P99, P95, P90, P75, P10
  • GHI/DNI uncertainty

• Consultancy services: 

  • Enhanced Solar Resource & Meteo Assessment
  • Site Adaptation of Solargis Model Time Series Data
  • Ground Surface Albedo Time Series
  • Enhanced PV Energy Yield Assessment
  • Ground Surface Albedo Evaluation Based on Site-Adapted Data

Additional services reduce the uncertainty of PV power plant design and increase your confidence in the project's long-term viability. Attract investments by achieving more accurate financial estimates and increase the credibility of project evaluation. 

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Solargis provides solar and meteorological data within latitudes 60 S and 65 N.

All land is covered except polar areas.

At the moment of project activation, Solargis Evaluate generates Time Series for the available historical period up to last month, so that you are working with the latest data available.

Long history of data includes typical weather as well as anomalies. Every new data request benefits from the latest model improvements in accuracy.

More about data coverage ->

Solargis offers the most extensive validation based on publicly available solar data coming from high-end, quality-controlled pyranometers and pyrheliometers.

We are committed to transparency by publicly disclosing the detailed results of the validation in the Solargis Validation Report.

At the same time, we are continuously adding new validation sites all around the world to make sure that our solar models perform according to our high standards globally. 

More about solar model validation ->

Enhance the resilience of your PV design by accounting for extreme weather with 15-min data and optimize for the best PV performance. By default, Solargis Evaluate works with 15-minute Time Series data referring to a history of up to 30 years, including all meteorological and environmental factors relevant for PV energy simulation and analysis. 

Using 15-minute Time Series data for PV power plant design captures high-frequency variations in solar and weather conditions. This leads to more accurate modeling of power output and helps optimize PV power plant technical components. 

As a result, the simulation accounts for both short-term fluctuations and long-term variability, optimizing the power plant design to meet the business model requirements and withstand extreme weather. 

By using the full history of data, you can adapt the PV design to account for short-term variability and long-term trends, while grasping the effects on future conditions, ensuring the system is resilient to potential shifts in temperature and other conditions. 

When designing a PV power plant, it is possible to choose from multiple terrain models that lead to different layouts:

• Copernicus in 30m resolution (1 arcsec | global | 2011-2015 | surface model - including trees and buildings)

• SRTM (Google Earth) in 30m resolution (1 arcsec | global | 2000 | terrain model - excluding trees and buildings)

• SRTM (Solargis) in 90m resolution (3 arcsec | global | 2000 - 2017 | terrain model - excluding trees and buildings)

Experimenting with different elevation data results in different energy yields, but doesn’t affect solar and meteorological data. Horizon shading is calculated from the environmental data and depicts the terrain elevation and shading in the location’s surroundings. You can modify and enter your own horizon data if needed. 

More about the importance of terrain data ->

The advanced energy system designer allows you to design the PV array layout, including mounting selection, tilt, and rack spacing. Additionally, the PV energy design supports multiple mounting types at once. 

Below you can find the list of mounting types that Solargis Evaluate supports on horizontal or inclined plane: 

• Fixed angle
• Tracker one-axis NS with adjustable azimuth 
  • Backtracking
  • Rotation limits
• East-west mounting

More about array configuration ->

When the array is populated with PV modules, the Energy System Designer automatically calculates optimal tilt, azimuth, row spacing, and other relevant settings. The proposed configuration represents the optimal PV design settings tailored to the selected location, mounting type, and local climate.

The 3D interactive scene enables viewing the system from various angles and perspectives, providing a clearer understanding of the layout in a geographical context and potential issues.

You can define different types of objects, such as buildings, trees, hedges, and other physical elements that might affect the solar power plant layout. 

By using restricted line tool you can draw the service line and define its width, which allows for the placement of inverters into these safe zones. 

Line objects can be used to draw any objects that impact the shading of the PV power plant and their height can be defined up to 500m. 

If you have defined these objects using a different tool, you can simply import them in a KML format. It is possible to import segments (non-overlapping polygons), restricted areas (overlapping polygons), and shading line objects (polylines).

More about service lines, restricted areas, and line objects ->

The capabilities of the energy system designer go beyond a simple 3D design and selection of PV hardware. Our PV design incorporates advanced settings for electrical layout, including inverter setup, placement of transformers, and defining cabling losses. 

The system automatically selects the most appropriate generic PV modules and inverters and intelligently places transformers. It lets you manually define factors like cabling, degradation, and environmental losses. 

If you have a preferred model of a commercial PV modules or inverters, you can directly pick specific models from the PV Components Catalog. You can then optimize the position of the inverter according to the limitations of the location. You can tailor it to your project’s power output, efficiency, module compatibility, and unique requirements of your project. 

Detailed information about each inverter option is provided, including technical specifications and performance data.

More about inverter configuration ->

The built-in validation tool checks for potential problems like voltage mismatches, incorrect inverter settings, or grid connection issues. This feature helps you identify and fix issues before energy simulation.

By ensuring all components work together correctly, the validation process increases system reliability and improves performance. All attributes of the energy system validator must be defined correctly to run a PV simulation. You can check the status of the validator anytime during the design process and adjust what is needed.

More about energy system validation ->

The PV Components Catalog is a reliable source of technical specifications, verified by Solargis experts and algorithms, adhering to a transparent set of verification steps. A dedicated team maintains and organizes the catalog through close collaboration with manufacturers, covering both current component specifications and historical data for previous models. The catalog serves as a platform for real-time updates, ensuring you always have access to the latest product information.

The PV Components Catalog integrates with Solargis Evaluate for immediate use of publicly listed components in energy yield simulations and PV designs. You can also connect your Solargis Evaluate account via API to add your own components.

The Solargis PV simulator is built on scalable cloud infrastructure with intelligent preprocessing capabilities. The simulation engine delivers high precision in computation, while maintaining high accuracy of the results. Additionally, it supports parallel simulation requests, enabling multiple scenarios to run simultaneously. 

Most importantly, Solargis Evaluate does not block your hardware resources, allowing you to work simultaneously on multiple tasks without interruption.

More about Solargis information security ->

Solargis PV simulation uses ray tracing technology and anisotropic sky model.

It considers all kinds of shading defined by both horizon data in the Solargis data model and shading objects present in the physical world model. The precise path of sunlight is simulated by tracing individual rays between the sky and solar cell surfaces as it travels through the 3D environment.

The ray tracing algorithm is based on Monte Carlo backward path-tracing, where we trace back the source of light to each cell and take into account multiple bounces until the source of light is reached. This is validated with bifacial_radiance.

3D ray tracing-based simulation allows us to calculate for hilly terrains and bifacial panels with no limitation. 

Ray tracing delivers more accurate results by leveraging detailed geometric information about the scene and precise calculations for each ray. This provides exceptional precision in simulations, although with greater computational effort compared to the faster but less detailed view factor method.

In Solargis Evaluate we approach PV system losses in greater detail. Our systematic approach to PV system losses starts by dividing them into optical and electrical parts. By methodically addressing each type of loss and employing robust calculation methods, we provide a comprehensive and reliable estimate of the expected energy output based on the actual power plant definition. 

We provide monthly breakdowns of PV system losses by category, providing seasonal and interannual variability of monthly PV losses. This helps in making informed decisions about component sizing (e.g., inverter capacities) and PV system configurations to accommodate seasonal peaks and decrease stakeholders’ financial risks.

Some examples of the PV losses we take into account include: 

• Shading losses
• Spectral losses 
• Inverter losses 
• Conversion losses
• Angular losses
• Auxiliary losses
• AC cable losses

More about PV system losses ->

In regions with frequent snowfall it is important to calculate the impact of snow on PV power production. Solargis snow losses model uses data from the ERA5 model and in-house satellite-model solar radiation data which allows us to categorize snow losses into three types based on their impact on PV power production:

• Partial Losses: Some solar energy is absorbed by the snow, but not all. This typically occurs when a thin layer of snow covers the modules, allowing some irradiation to pass through.

• Total Losses: All solar energy is absorbed or reflected by the snow, resulting in no power production. This occurs when the snow cover is thick enough to block all sunlight.

• Snow Slide Events: Snow slides off the PV modules rapidly, often triggered by rising temperatures. This results in a sudden increase in power production as the modules are cleared of snow.

When calculating snow losses, we not only account for the location but also the tilt of the panels. Steeper angles allow snow to slide off or melt more quickly. Additionally, we incorporate a variety of other factors and calculate snow melting in the background, factoring in variables such as temperature and wind conditions. 

Accounting for snow losses has a direct impact on the forecasted energy production, ensuring a more accurate and realistic projection of PV output. This level of precision increases the reliability of the bankable report, providing a solid foundation for securing project funding and reducing the risk of overestimations in financial assessments.

More about modelling snow losses in PV systems ->

The ground's surface albedo influences the amount of sunlight that reaches the solar modules, particularly in utility-scale solar installations, where the spacing between modules allows sunlight to hit the ground.

Ground surface albedo becomes especially important when bifacial PV systems are installed. 

Understanding albedo can lead to higher energy yields, making it an important consideration in the design of bifacial PV systems.

Our approach uses a sub-hourly Time Series of solar radiation and in-house calculated albedo data, making it possible to capture the short-term variability in front and rear-side solar radiation received by PV modules throughout the day. 

This approach, combined with ray tracing technology that accounts for factors such as shading from torque tubes, provides a more accurate simulation of how reflected light interacts with bifacial modules. 

The energy system designer allows for adjustments to ground surface albedo settings to reflect ground reflectivity as a whole, or separately per every segment with monthly granularity.

More about albedo ->

Early-stage evaluation with TMY: TMY data aggregates historical weather patterns into a "typical" year, providing a reliable representation of average solar radiation, air temperature, and, to a lesser extent, wind speed. For early-stage project evaluation, TMY data offers a quick and cost-effective means of estimating solar and PV potential. This makes it useful during the pre-feasibility phase, where developers need to perform high-level assessments to determine the viability of a project.

However, TMY data is far from perfect. It smooths out significant weather fluctuations, and its low granularity—typically in hourly time step —fails to capture critical types of variability. These include:

• Short-term variability (intra-hourly fluctuations)
• Interannual variability and seasonal changes
• Long-term variability and climate change

The primary limitation of TMY data is its failure to capture extreme weather events like storms or high winds, which can disrupt solar generation. By averaging these extremes into typical patterns, TMY underestimates real-world variability and leads to overly optimistic performance predictions. 

Full evaluation with Time Series data: As a project moves from the early stage into full evaluation, it is crucial to transition from TMY data to high resolution Time Series data. Unlike TMY, Time Series data is typically available in 15-minute intervals, covering periods of up to 30 years. This resolution provides developers with a much more granular, accurate representation of weather patterns and variability, allowing them to simulate solar power generation in real-world conditions with far greater precision.

For example, high resolution data captures the impacts of extreme weather events like cloud cover, high winds, air pollution, or snow. These events, which are often overlooked in TMY-based simulations, can have significant consequences for energy generation, system performance, and project financials.

The contrast in data volume between TMY and Time Series is evident:

• TMY typically offers around 8,760 data points per year (one per hour)
• High resolution data, by comparison, provides over 1 million data points per year (at 15-minute intervals)

More about TMY and Time Series data ->

Deep dive into Global horizontal irradiation, Global tilted irradiation, Direct normal irradiation, and Diffuse horizontal irradiation, presented in charts and tables in yearly, daily, hourly, and sub-hourly resolutions.

Understand your project’s solar data and analyze the variability of the solar resource over the full period of satellite data retrieval.

More about solar radiation modelling ->

The charts detailing parameters such as air temperature, precipitation, ground surface albedo, and precipitable water, with data presented in graphs and tables at yearly, monthly, and hourly resolutions provides insights into the site local conditions.

For example, to help identify strong winds that may limit operation or threaten the structural integrity of the PV system, wind parameters, including wind direction and wind gusts, are provided within the delivered data.

More about meteorological models ->

Thanks to the fact that model inputs start from 1994, there is enough data to calculate the expected interannual variability for the site conditions.

Accounting for interannual variability lets you create designs that can withstand extreme weather. Moreover, it will significantly mitigate inaccurate estimates, enhancing the resilience of design and lowering the risk of overestimated financial returns.

More about interannual variability ->

Besides the theoretical specific and total photovoltaic power output, we calculate the Performance Ratio (PR), which is based on the EIC 61724-1 standard. This is to help you understand the maximum potential of your PV design and set reasonable expectations for operational targets. 

The PV statistics section includes charts and tables for theoretical photovoltaic power output values, which can be found in yearly, daily, hourly, and sub-hourly resolutions. This helps with informed decision-making, accurate budgeting, and proactive management to optimize energy production and mitigate risks.

PV performance degrades by some percentage every year. The degradation rate depends on factors such as module type, system design, environmental conditions, and maintenance practices.

We provide a year-by-year breakdown that enables you to assess your system’s performance over its lifetime. The calculations incorporate the user-provided degradation rate, offering a more accurate estimate of the system’s PV energy yield.

For key parameters such as GHI, DNI, GTI, and PVOUT we provide monthly histograms in up to 15-minute resolution. The combination of histograms offers a richer, multi-dimensional perspective on solar system performance, leading to improved long-term estimates, performance optimization, and variability insights of a PV energy system.

Monthly histograms offer valuable insights into the high-frequency fluctuations of solar radiation throughout the day, providing insights into the variability of solar power delivered to the grid. This analysis helps manage the risks associated with limited capacity of grid to absorb this variation.

Frequent variability of PV output may also result in higher energy losses due to the design of inverters and strings. High-frequency variability and technical limitations of PV components are considered in the PV simulation and reflected in the section on PV losses.