Terms & Concepts
This page explains some of the more complex topics you might come across when creating an energy site or creating a simulation request.
Energy Sites
System Losses/Derate
The GeneralDerate_Percent parameter is used to specify system losses that affect the energy output of a PV system but are not separately modeled by either of the SolarAnywhere solar simulation models (CprPVForm or pvlib). If you know the system losses, GeneralDerate_Percent can be calculated as:
For example, a system loss of 14% can be converted to a General derate percent of 86% using the above equation. Table 1 shows a comparison of system losses between power models:
Losses in the pvlib model
The system loss percentages presented in Table 1 are widely accepted default values for each loss component. However, these values can differ from system to system. You can adjust the defaults and calculate custom system losses using the formula:
It is important to note that the total system loss is not simply the sum of the individual losses. The default system loss and GeneralDerate_Percent are calculated using Eqn (1) and (2) in the following steps:
The Total System Losses used to calculate the GeneralDerate_Percent should account for losses due to inverter efficiency, shading, PTC rating and degradation, as well as general system losses not explicitly specified. The power model calculates Total System Losses:
Total System Losses = General System Losses x Inverter Efficiency (%) x PTC Rating (kW) x Shading x Degradation
A degradation factor of 0.5% is considered for the CprPVForm model and cannot be modified.
GeneralDerate_Percent = 100 – System Losses (%)  Eqn (1) 

pvlib (PVWatts)  CprPVForm  

General Derate Percent (Default)  86%  85% 
System loss categories and defaults  Soiling = 2% Shading = 3% Snow = 0% Mismatch = 2% Wiring = 2% Connections = 0.5% Lightinduced Degradation = 1.5% Nameplate Rating = 1% Age = 0% Availability = 3% 
Soiling, Snow, Mismatch, Wiring, Connections, Age, Availability 
Losses excluded from GeneralDerate_Percent  Inverter Efficiency  Inverter Efficiency, Shading, Degradation, Nameplate (STC) rating 
Losses in the pvlib model
The system loss percentages presented in Table 1 are widely accepted default values for each loss component. However, these values can differ from system to system. You can adjust the defaults and calculate custom system losses using the formula:
Eqn (2) (Source: PVWATTS documentation) 

 Calculate total system loss from individual components using Eqn (2).
100% × [ 1 ( 1  0.02 ) × ( 1  0.03 ) × ( 1  0.02 ) × ( 1  0.02 ) × ( 1  0.005 ) × ( 1  0.015) × ( 1 0.01 ) × ( 1  0.03) ] = 14%  Calculate GeneralDerate_Percent from System Loss percent using Eqn (1).
GeneralDerate_Percent = 100 – 14 = 86%
The Total System Losses used to calculate the GeneralDerate_Percent should account for losses due to inverter efficiency, shading, PTC rating and degradation, as well as general system losses not explicitly specified. The power model calculates Total System Losses:
Total System Losses = General System Losses x Inverter Efficiency (%) x PTC Rating (kW) x Shading x Degradation
A degradation factor of 0.5% is considered for the CprPVForm model and cannot be modified.
Albedo Percent
Albedo (also called ground reflectance) is defined as the fraction of the Global Horizontal Irradiance that is reflected off the ground. The Albedo_Percent parameter is used by both SolarAnywhere solar simulation models (CprPVForm or pvlib) to adjust the incident irradiance on the PV module so that it accounts for the effect of irradiance reflected off the ground. To specify the albedo percent, insert Albedo_Percent="{Decimal Value}” into the PvSystem details.Albedo_Percent will be approximately equal to zero for dark surfaces that absorb all of the light incident. Albedo_Percent will be approximately equal to 100 for light surfaces that reflect all of the light incident. Both simulation models use a default value of 17%.
You can request SolarAnywhere satellite based albedo data at your location by including Albedo_Unitless as an OutputField or AverageAlbedo as a SummaryOutputField in your simulation request. You can learn more about SolarAnywhere albedo data by visiting this page of the SolarAnywhere website.
Additionally, Table 2 provides examples of albedo values for various types of ground surface. Additional information on possible values for albedo can be found at the Sandia National Laboratories website.
You can request SolarAnywhere satellite based albedo data at your location by including Albedo_Unitless as an OutputField or AverageAlbedo as a SummaryOutputField in your simulation request. You can learn more about SolarAnywhere albedo data by visiting this page of the SolarAnywhere website.
Additionally, Table 2 provides examples of albedo values for various types of ground surface. Additional information on possible values for albedo can be found at the Sandia National Laboratories website.
Surface Type  Ranges for Albedo 

Fresh snow cover  75% to 95% 
Sandy soil  15% to 40% 
Meadows and fields  12% to 30% 
Densely built up areas  15% to 25% 
Dark, cultivated soil  7% to 10% 
PV Systems
Both of the SolarAnywhere solar simulation models (CprPVForm or pvlib) require the client to define one or multiple PvSystem(s). A PvSystem is made up of modules and inverters that are wired together in specific configurations. The PvSystem will output power at the point of interconnection (to the electric grid or to energy storage). The Solar Simulations API models the amount of power that this PvSystem is outputting. The PvSystem components will define how the PV simulation model calculates alternating current (AC) power and AC energy from the irradiance and weather data. PvSystem(s) modules output direct current (DC), which is then converted to AC by the inverter. See sections on Inverter, PV Modules and Array Configuration for more information on how these specific inputs impact the simulation.
Inverters
Inverter is a PvSystem component. Each is wired to a set of PV modules and converts the DC output of the module into AC power. Both of the SolarAnywhere solar simulation models (CprPVForm or pvlib) require that the client pass information about the number (Count), maximum rated power (MaxPowerOutputAC_kW) and rated efficiency (EfficiencyRating_Percent) for each inverter. For a mapping of inverter models to necessary input ratings, see the CEC inverter list.
PV Modules
PvModule is a component of a PvSystem. Each PV module converts incident irradiance under the ambient weather into DC output, which the inverter then converts to AC power.
Both SolarAnywhere solar simulation models (CprPVForm or pvlib) require that the client pass information about the number (Count) and rating of the PV modules. You will need to specify the performance test conditions AC rating (PtcRating_kW) of the PV modules and the nameplate DC rating (NameplateDCRating_kW). The CprPVForm simulation model will utilize the PtcRating_kW while the pvlib model will utilize the NameplateDCRating_kW.
If desired, you can also specify the module temperature rating (PowerTemperatureCoefficient_PercentPerDegreeC). If the client leaves this blank, the pvlib simulation model uses a default of 0.37%/°C and CprPVForm uses a default value of 0.40%/°C. For a mapping of PV modules to necessary input ratings, see the CEC module list.
Both SolarAnywhere solar simulation models (CprPVForm or pvlib) require that the client pass information about the number (Count) and rating of the PV modules. You will need to specify the performance test conditions AC rating (PtcRating_kW) of the PV modules and the nameplate DC rating (NameplateDCRating_kW). The CprPVForm simulation model will utilize the PtcRating_kW while the pvlib model will utilize the NameplateDCRating_kW.
If desired, you can also specify the module temperature rating (PowerTemperatureCoefficient_PercentPerDegreeC). If the client leaves this blank, the pvlib simulation model uses a default of 0.37%/°C and CprPVForm uses a default value of 0.40%/°C. For a mapping of PV modules to necessary input ratings, see the CEC module list.
Nameplate Rating
The nameplate DC rating of a solar panel is a PvModule component and describes the maximum rated output of the PV module under industry standard test conditions (STC). Standard test conditions are defined as 1,000 W/m2 of solar irradiance, an air mass of 1.5, and an operating cell temperature of 25°C. STC conditions are generally more ideal than what might happen in realworld conditions – for example, on most days except for a few clear spring or summer days, the solar insolation will be less than 1000 W/m2 and module temperature might be higher than 25°C. STC rating also does not account for the effect of wind speed and module height above ground. The SolarAnywhere pvlib solar simulation model uses Nameplate (STC) rating to account for PV module performance.
The module nameplate rating is a PvModule element. To specify the Nameplate or STC rating, insert NameplateDCRating_kW =”{Integer Value}” into the PvModule details.
The module nameplate rating is a PvModule element. To specify the Nameplate or STC rating, insert NameplateDCRating_kW =”{Integer Value}” into the PvModule details.
PTC Rating
The performance test conditions (PTC) DC rating of a solar panel is a PvModule component and describes the maximum rated output of the PV module when operating in an environment with 1,000 W/m2 of solar irradiance, an air mass of 1.5, and an ambient temperature of 20°C at 10 meters above ground level with a wind speed of 1 meter per second. Additionally, the operating cell temperature is raised to 45°C in PTC tests.
PTC are considered more representative of realworld operating conditions. The SolarAnywhere CprPVForm solar simulations model uses PTC rating to account for PV module performance.
The module PTC rating is a PvModule element. To specify the PTC rating, insert PtcRating_kW =”{Integer Value}” into the PvModule details.
The module PTC rating is a PvModule element. To specify the PTC rating, insert PtcRating_kW =”{Integer Value}” into the PvModule details.
Power Temperature Coefficient
The power temperature coefficient is a PvModule component and quantifies the effect of module operating temperature on the AC power output of the system. As the cell temperature increases, the power output of the module decreases. Manufacturers of PV modules usually provide this value in the module’s data sheet.
To specify power temperature coefficient, insert PowerTemperatureCoefficient_PercentPerDegreeC = "{Decimal Value}” into the PvModule details. If not specified, the SolarAnywhere pvlib simulation model uses a default power temperature coefficient of 0.37%/°C and CprPVForm uses a default value of 0.40%/°C. Table 3 demonstrates common power temperature coefficients associated with different PV module types.
Module Type  Temperature Coefficient 

Standard PV (crystalline Silicon)  0.37%/°C 
Premium (crystalline Silicon)  0.35%/°C 
Thin Film  0.32%/°C 
Array Configuration
The ArrayConfiguration is a component of a PvSystem that defines how the system is installed. The ArrayConfiguration elements are important to the simulation model as they help determine the incident irradiance on the plane of the PV module array, and can have a significant impact on the simulation accuracy. The SolarAnywhere solar simulation models (CprPVForm or pvlib) require that the client pass information about the tilt angle from horizontal (Tilt_Degrees) and azimuth angle (Azimuth_Degrees) in which each set of PV modules is installed. For residential systems, the tilt angle often is specified by the roof pitch. The azimuth angle is a reference to the Cardinal Direction that the array of PV modules is facing. The simulation modeIs use 180degrees as South reference (90degrees is East and 270degrees is West). The client can also specify the type of tracking system on which the PV modules are mounted (Tracking), the rotation limit of the tracker (TrackingRotationLimit_Degrees), the number of rows of modules (ModuleRowCount) and the relative module row spacing (RelativeRowSpacing).
Tracking
The SolarAnywhere solar simulation models (CprPVForm or pvlib) support fixed and singleaxis tracking PV systems. Additionally, CprPVForm can support dualaxis tracking PV systems and pvlib can support singleaxis tracking systems with backtracking capabilities. If a single or dualaxis tracking type is specified, the simulation model calculates the rotation angle that minimizes the angle of incidence throughout the day. The angle of incidence is defined as the angle between a line that is normal to the module surface and a line drawn on a straight path from the sun to the module surface.
Fixed Tilt
Fixed Tilt
 Supported by: pvlib and CprPVForm power models.
 Fixed tilt arrays do not track the sun to minimize the angle of incidence.
 When defining a fixed tilt array, specify the following in the ArrayConfiguration details:
 Tracking=“Fixed”
 The array surface tilt parameter: Tilt_Degrees
 The array surface azimuth angle: Azimuth_Degrees

 Supported by: pvlib and CprPVForm power models.
 Singleaxis trackers move along a single axis of rotation. Singleaxis trackers can be classified as horizontal, tilted, or vertical based on the tilt angle of the rotation axis with respect to horizontal.
 Horizontalaxis trackers are most common in commercial and utilityscale systems. Horizontal tracking arrays are usually oriented NorthSouth with modules that rotate from East to West throughout the day, limited by the tracking rotation limit.
 When defining a singleaxis tracking array, specify the following in the ArrayConfiguration details:
 Tracking=“SingleAxis”
 The array axis of rotation tilt parameter: Tilt_Degrees
 The array axis of rotation azimuth angle: Azimuth_Degrees
 The tracking rotation limit: TrackingRotationLimit_Degrees
 Supported by: pvlib power model.
 As tracking PV systems move to maximize exposure to solar irradiance, adjacent PV panels can partially shade each other across part of the module when the sun is low in the sky (i.e. the morning and evening hours). This effect, known as selfshading or rowonrow shading can decrease the output of a solar PV system by creating electrical mismatch losses. Backtracking is a tracking technology that operates singleaxis trackers at a tilt or rotation angle other than the “ideal” rotation to minimize the effect of interrow shading. The pvlib power model can model singleaxis energy systems with backtracking technology.
 When defining a singleaxis tracking array with backtracking, specify the following in the ArrayConfiguration details:
 Tracking=“SingleAxisWithBacktracking”
 The array axis of rotation azimuth angle: Azimuth_Degrees
 The tracking rotation limit: TrackingRotationLimit_Degrees
 Supported by: CprPVForm power model.
 DualAxis trackers can move along two axes of rotation (EastWest and NorthSouth). This allows them to always maintain a 0° angle of incidence, which maximizes the solar radiation hitting the solar panels. Unlike with singleaxis trackers, no tracking limit is placed on the rotation in the azimuth direction.
 When defining a dualaxis tracking array, specify the following in the ArrayConfiguration details:
 Tracking=“DualAxis”
 The tracking rotation limit: TrackingRotationLimit_Degrees
Tracking Rotation Limit
The tracking rotation limit is the rotational limit in degrees for single axis tracking systems. It is possible to use values between 0 and 90, which represent half the full range of motion of the tracker. For example, a value of 60 means the tracker can move +/60 degrees around the axis of rotation for an overall range of 120 degrees. To specify tracking rotation limit, insert TrackingRotationLimit_Degrees =“{Integer Value}”, into the ArrayConfiguration details.
Module Row Count
Module row count is the total number of rows in each PV array. As shown in figure 1, this value will correspond to the number of PV strings in parallel within an array. This parameter is used by both SolarAnywhere solar simulation models (CprPVForm or pvlib) to model the effect of rowtorow shading. To specify module row count, insert ModuleRowCount = "{Integer Value}” into the ArrayConfiguration details.
Relative Row Spacing/Ground Coverage Ratio
Relative row spacing is the inverse of the ground coverage ratio (GCR) and can be calculated as the ratio of rowtorow pitch to array length. A lower GCR (higher relative row spacing) means wider row spacing and a higher GCR means narrower row spacing. Typical utility scale PV systems have GCRs in the range of 0.3 to 0.6. This parameter is also used by both SolarAnywhere solar simulation models (CprPVForm or pvlib) to model the effects of rowtorow shading. The default value of relative row spacing used in both simulation models is 3, which is equal to a GCR of 0.3. To specify row spacing, insert RelativeRowSpacing = "{Decimal Value}” into the ArrayConfiguration details.
Energy Site Simulation
SolarAnywhere Solar Simulation Models
Clean Power Research offers two energy simulation models: pvlib and CprPVForm. Visit the introduction page for more detail on these models.
Table 4 outlines their capabilities and limitations.
CprPVForm  pvlib  

General Derate Percent  Default: 85%  Default: 86% 
Module Rating  PTC Rating  STC Rating 
Module Power Temperature Coefficient  Default: 0.40%/°C  Default: 0.37%/°C 
Tracking types  FixedAxis, Single Axis, TwoAxis  FixedAxis, Single Axis, Single Axis with Backtracking 
Reflection Losses  No  Yes 
Nearobject shading  Yes  Yes 
Rowonrow shading  Yes  Yes 
Snow Losses  No  Yes 
Soiling Losses  No  Yes 
Temperature Modeling
The pvlib solar simulation model in SolarAnywhere uses the Faiman temperature model to calculate PV module temperature. The Faiman model implements the empirical heat loss factor model described in the original publication: “Faiman, D. (2008). “Assessing the outdoor operating temperature of photovoltaic modules.” Progress in Photovoltaics 16(4): 307315.”
The Faiman model was adopted in the IEC 618532 and IEC 618533 standards published by the International Electrotechnical Commission (IEC) in 2018. When using the pvlib energy simulation model in the SolarAnywhere API, the Faiman model implements SolarAnywhere ambient temperature and wind speed data to determine PV module/cell temperature.
The following assumptions are used internally in the Faiman temperature model and cannot be modified by the user:
The Faiman model was adopted in the IEC 618532 and IEC 618533 standards published by the International Electrotechnical Commission (IEC) in 2018. When using the pvlib energy simulation model in the SolarAnywhere API, the Faiman model implements SolarAnywhere ambient temperature and wind speed data to determine PV module/cell temperature.
The following assumptions are used internally in the Faiman temperature model and cannot be modified by the user:
Internal parameters  Definition  Default value in pvlib 

u0  Combined heat loss factor coefficient. The default value was determined by Faiman for 7 silicon modules. [W/m^2C]  25.0 
u1  Combined heat loss factor influenced by wind. The default value was determined by Faiman for 7 silicon modules. [W/m^2 C (m/s)]  6.84 
Module (DC) and Inverter (AC) Modeling
The pvlib solar simulation model in SolarAnywhere uses NREL PVWatts as the core simulation engine for PV module and inverter modeling. The PVWatts model has been used extensively by solar project developers and financiers for PV performance assessment and is also supported by the System Advisor Model (SAM).
PVWatts makes internal assumptions about module and inverter characteristics, enabling energy simulations API users to accurately model any PV system type and configuration with just a few basic inputs about their energy site.
The following assumptions are used internally in the pvlib implementation of PVWatts DC and AC models and cannot be modified by the user:
PVWatts makes internal assumptions about module and inverter characteristics, enabling energy simulations API users to accurately model any PV system type and configuration with just a few basic inputs about their energy site.
The following assumptions are used internally in the pvlib implementation of PVWatts DC and AC models and cannot be modified by the user:
Internal parameters  Definition  Default value in pvlib 

T_ref  Cell reference temperature for DC modeling. [Celsius]  25.0 
Eta_inv_ref  Reference inverter efficiency. [Unitless]  0.9637 
Near Object Shading Losses
MonthlyPercentSolarResource
The MonthlyPercentSolarResource shading model can be applied when using either of the available SolarAnywhere solar simulation models. This shading model applies monthly solar access percentage derate factors to hourly simulation outputs to account for the effect of shading on PV system production.
The solar access percentage can be calculated as the ratio of incident solar energy on the shaded PV panel to the incident solar energy on the unobstructed PV panel. It is the opposite of the shading percentage. For example, an array with 10% shading would have a solar access of 90%. If monthly shading percentages are not specified, 100% solar access (0% shading) is assumed for all months.
Monthly solar access percentages are PvSystems elements and can be specified at the time of creating an energy site using the Clean Power Research simulation API.
ShadeSimulator
The ShadeSimulator model can only be applied using the SolarAnywhere CprPVForm solar simulations model. The ShadeSimulator model uses information about obstructions surrounding the PV system to modify simulated output. Obstructions can be objects such as trees or adjacent buildings that shade the PV system at certain times of day.
Specifying obstructions for the ShadeSimuator model requires an input combination of azimuth, elevation, and opacity for each obstruction in relation to the position of the PV system. The distance and height of shadowcasting objects can be calculated using a site plan and sun path diagram or shading analysis software coupled with digital photography. The azimuths of the obstructions can be calculated directly from the site plan or sketch. The opacity or transmission factor specifies the amount of solar radiation passing through the shading objects.
The azimuths, elevations, and opacities of solar obstructions are PvSystems elements and can be specified at the time of creating an energy site using the Clean Power Research simulation API.
The shade simulator uses the azimuths, elevations, and opacities of the obstructions to generate a digital elevation model (DEM). This is an internal, threedimensional model of the obstructions surrounding the PV system that is used to modify simulation outputs based on the time of day.
The MonthlyPercentSolarResource shading model can be applied when using either of the available SolarAnywhere solar simulation models. This shading model applies monthly solar access percentage derate factors to hourly simulation outputs to account for the effect of shading on PV system production.
The solar access percentage can be calculated as the ratio of incident solar energy on the shaded PV panel to the incident solar energy on the unobstructed PV panel. It is the opposite of the shading percentage. For example, an array with 10% shading would have a solar access of 90%. If monthly shading percentages are not specified, 100% solar access (0% shading) is assumed for all months.
Monthly solar access percentages are PvSystems elements and can be specified at the time of creating an energy site using the Clean Power Research simulation API.
ShadeSimulator
The ShadeSimulator model can only be applied using the SolarAnywhere CprPVForm solar simulations model. The ShadeSimulator model uses information about obstructions surrounding the PV system to modify simulated output. Obstructions can be objects such as trees or adjacent buildings that shade the PV system at certain times of day.
Specifying obstructions for the ShadeSimuator model requires an input combination of azimuth, elevation, and opacity for each obstruction in relation to the position of the PV system. The distance and height of shadowcasting objects can be calculated using a site plan and sun path diagram or shading analysis software coupled with digital photography. The azimuths of the obstructions can be calculated directly from the site plan or sketch. The opacity or transmission factor specifies the amount of solar radiation passing through the shading objects.
The azimuths, elevations, and opacities of solar obstructions are PvSystems elements and can be specified at the time of creating an energy site using the Clean Power Research simulation API.
The shade simulator uses the azimuths, elevations, and opacities of the obstructions to generate a digital elevation model (DEM). This is an internal, threedimensional model of the obstructions surrounding the PV system that is used to modify simulation outputs based on the time of day.
Snow Losses
Accumulated snow can reduce the energy output of a solar PV system by obstructing the sunlight available for energy conversion. PV energy losses due to snow—commonly referred to as “snow losses”—vary widely between locations. Modeling the uncertainty that results from snow losses can be complex, as several factors can affect the rate of snow accumulation and shedding. The local climate and the PV system’s configuration (such as the system tilt and tracking type) can impact the magnitude of energy losses.
The pvlib solar simulation model in SolarAnywhere uses the snow loss model developed and validated by NREL. pvlib leverages SolarAnywhere snow depth and ambient temperature data as well as user provided energy site configuration(s) to calculate sitespecific snow loss estimates. Because snow loss calculations are based on accumulated snow, the snow loss model will consider snow depth and ambient temperature data for 6 months prior to the start time specified in your simulation request. To learn more about the snow loss model, refer to the original publications: “Marion, B.; Schaefer, R.; Caine, H.; Sanchez, G. (2013). ‘Measured and modeled photovoltaic system energy losses from snow for Colorado and Wisconsin locations.’ Solar Energy 97; pp.112121” and “Ryberg, D; Freeman, J. (2017). “Integration, Validation, and Application of a PV Snow Coverage Model in SAM” NREL Technical Report NREL/TP6A2068705.”
The input parameters and default values used in the Snow Loss model are as follows:
Improving the accuracy of P50/P90 loss estimates with timeseries modeling can reduce the uncertainty in reported energy estimates. This helps project owners minimize financial and operational risk to their solar project. To learn more about snow loss modeling with SolarAnywhere timeseries weather data, see the blog and snowlosses resource page.
The pvlib solar simulation model in SolarAnywhere uses the snow loss model developed and validated by NREL. pvlib leverages SolarAnywhere snow depth and ambient temperature data as well as user provided energy site configuration(s) to calculate sitespecific snow loss estimates. Because snow loss calculations are based on accumulated snow, the snow loss model will consider snow depth and ambient temperature data for 6 months prior to the start time specified in your simulation request. To learn more about the snow loss model, refer to the original publications: “Marion, B.; Schaefer, R.; Caine, H.; Sanchez, G. (2013). ‘Measured and modeled photovoltaic system energy losses from snow for Colorado and Wisconsin locations.’ Solar Energy 97; pp.112121” and “Ryberg, D; Freeman, J. (2017). “Integration, Validation, and Application of a PV Snow Coverage Model in SAM” NREL Technical Report NREL/TP6A2068705.”
The input parameters and default values used in the Snow Loss model are as follows:
Internal parameters  Definition  Default value in pvlib  Can be specified by the user 

Initial_coverage  Fraction of row’s slant height that is covered with snow at the beginning of the simulation. [Unitless]  0  No 
threshold_snowfall  Hourly snowfall above which snow coverage is set to the row’s slant height. [cm/hr]  1.0  Yes 
can_slide_coefficient  Coefficient to determine if snow can slide given irradiance and air temperature. [W/(m^2 C)]  80  Yes 
slide_amount_coefficient  Coefficient to determine fraction of snow that slides off in one hour. The default indicates value in tenths of a module’s slant height. [Unitless]  0.197  Yes 
Soiling Losses
Accumulated dirt can reduce the energy output of a solar PV system by obstructing the sunlight available for energy conversion. PV energy losses due to module soiling—commonly referred to as “soiling losses”—vary widely by location. The local climate and PV system configuration (such as the system tilt and tracking type) can impact the magnitude of soiling related energy losses.
The pvlib solar simulation model in SolarAnywhere uses the soiling loss model developed and validated by Humboldt State University (HSU). Pvlib leverages SolarAnywhere precipitation and particulate matter data as well as user provided energy site configuration(s) to calculate sitespecific soiling loss estimates. Because soiling loss calculations are based on accumulated dirt, the soiling loss model will consider precipitation and particulate matter data for 6 months prior to the start time specified in the simulation request. To learn more about the soiling loss model, refer to the original publication: M. Coello and L. Boyle, “Simple Model For Predicting Time Series Soiling of Photovoltaic Panels,” in IEEE Journal of Photovoltaics. doi: 10.1109/JPHOTOV.2019.2919628”
The input parameters and default values used in the Soiling Loss model are as follows:
To learn more about soiling loss modeling with SolarAnywhere timeseries weather data, see the blog and soiling loss resource page.
The pvlib solar simulation model in SolarAnywhere uses the soiling loss model developed and validated by Humboldt State University (HSU). Pvlib leverages SolarAnywhere precipitation and particulate matter data as well as user provided energy site configuration(s) to calculate sitespecific soiling loss estimates. Because soiling loss calculations are based on accumulated dirt, the soiling loss model will consider precipitation and particulate matter data for 6 months prior to the start time specified in the simulation request. To learn more about the soiling loss model, refer to the original publication: M. Coello and L. Boyle, “Simple Model For Predicting Time Series Soiling of Photovoltaic Panels,” in IEEE Journal of Photovoltaics. doi: 10.1109/JPHOTOV.2019.2919628”
The input parameters and default values used in the Soiling Loss model are as follows:
Internal parameters  Definition  Default value in pvlib  Can be specified by the user 

cleaning_threshold  Amount of rain in an accumulation period needed to clean the PV modules. [mm]  6  Yes 
depo_veloc  Deposition or settling velocity of particulates. [m/s]  Particulate Matter 2.5: 0.0009, Particulate Matter 10: 0.004  No 
rain_accum_period  Period for accumulating rainfall to check against cleaning_threshold. [hours]  24 (It is recommended that rain_accum_period be between 1 hour and 24 hours.) 
Yes 
Reflection Losses
The angle of incidence (AOI) is defined as the angle between a line that is normal to the module surface and a line drawn on a straight path from the sun to the module surface. When the AOI is greater than zero, there are optical losses due to increased reflections from the module materials. To quantify reflection losses, an angle of incidence modifier (IAM loss factor) is calculated using an IAM model and is defined as the ratio of nonnormal to normal incidence transmitted light after deducting the reflected portion of each component.
The pvlib solar simulation model in SolarAnywhere uses the Physical IAM model to quantify reflection losses. The Physical IAM model determines the fraction of light transmitted through the airglass interface as a function of AOI and models the attenuation in the glazing layer. To learn more about the Physical IAM model, see the original publication: “W. De Soto et al., “Improvement and validation of a model for photovoltaic array performance”, Solar Energy, vol 80, pp. 7888, 2006.” The following assumptions are used internally for the Physical IAM model and cannot be modified by the user:
The pvlib solar simulation model in SolarAnywhere uses the Physical IAM model to quantify reflection losses. The Physical IAM model determines the fraction of light transmitted through the airglass interface as a function of AOI and models the attenuation in the glazing layer. To learn more about the Physical IAM model, see the original publication: “W. De Soto et al., “Improvement and validation of a model for photovoltaic array performance”, Solar Energy, vol 80, pp. 7888, 2006.” The following assumptions are used internally for the Physical IAM model and cannot be modified by the user:
Internal parameters  Definition  Default value in pvlib 

n  The effective index of refraction. [Unitless]  1.526 for glass 
K  The glazing extinction coefficient. [1/m]  4.0 
L  The glazing thickness. [m]  0.002 (2 mm) 
Selfshading losses
Selfshading losses (also known as rowtorow shading losses) occur when adjacent PV rows partially shade each other, blocking direct irradiance from reaching parts of the shaded module. At steep tilt and low sun elevation (i.e., morning and evening hours), interrow shading creates cell to cell electrical mismatch in modules with a conventional cell layout, resulting in severe nonlinear power loss.
To determine losses due to rowtorow shading the pvlib and CprPVForm solar simulation models in SolarAnywhereSolarAnywhere implement a simplistic model based on first principle solar geometry. The model has been described in “Richard Perez, Ronald Stewart (1985) ‘Solar Irradiance Conversion Models’, ASRC, State University of New York Albany”.
Even when the sun is high in the sky, a row’s view of the sky dome will be partially blocked by the row in front. This causes a reduction in the diffuse irradiance incident on the module. The pvlib model also implements the diffuse selfshading model described in “D. Passias and B. Källbäck, ‘Shading effects in rows of solar cell panels’, Solar Cells, Volume 11, Pages 281291. 1984. DOI: 10.1016/03796787(84)900176”, to estimate the fraction of sky diffuse irradiance that is blocked by the row in front.
To determine losses due to rowtorow shading the pvlib and CprPVForm solar simulation models in SolarAnywhereSolarAnywhere implement a simplistic model based on first principle solar geometry. The model has been described in “Richard Perez, Ronald Stewart (1985) ‘Solar Irradiance Conversion Models’, ASRC, State University of New York Albany”.
Even when the sun is high in the sky, a row’s view of the sky dome will be partially blocked by the row in front. This causes a reduction in the diffuse irradiance incident on the module. The pvlib model also implements the diffuse selfshading model described in “D. Passias and B. Källbäck, ‘Shading effects in rows of solar cell panels’, Solar Cells, Volume 11, Pages 281291. 1984. DOI: 10.1016/03796787(84)900176”, to estimate the fraction of sky diffuse irradiance that is blocked by the row in front.
Timestamps
The simulation request timestamps indicate the start and end period for which the client wishes to return data. Timestamps are absolute and follow the ISO 8601 convention. For example, if the client wishes to request data from January 1, 2020 at 11:00 AM Pacific Standard Time to January 2, 2020 at 12:00 PM Eastern Standard Time:
 StartTime ="20200101T11:00:0008:00"
 EndTime="20200102T12:00:0005:00"
Irradiance and Weather Data
In energy simulation requests you can also request SolarAnywhere irradiance and weather data output fields. To see a list of all of the irradiance and weather data output field options, you can visit this page of our documentation.
Simulation Output Fields
When included in a simulation request the following output fields and summary output fields will be generated based on the inputs specified when creating an energy site:
 PlaneOfArrayIrradiance_WattsPerMeterSquared:The irradiance incident on the plane of the array (POA) based on the sun’s position, the module spacing, the module orientation (azimuth), tracking (if applicable), shading and ground surface albedo. POAI is modeled using the Perez transposition model.
 PowerAC_kW:The modeled power output of the PV system based on the total available plane of array irradiance, weather conditions, shading, array configuration, and module and inverter characteristics.
 PowerDC_kW:The modeled power output of the PV modules based on the total available plane of array irradiance, weather conditions, shading, array configuration, and module characteristics.
 EnergyAC_kWh: The modeled energy output of the PV system based on the total available plane of array irradiance, weather conditions, shading, array configuration, and module and inverter characteristics.
 ClearSkyPowerAC_kW: The modeled power output of the PV system based on the total available clear sky plane of array irradiance, weather conditions, shading, array configuration, and module and inverter characteristics. The clear sky irradiance is the irradiance calculated assuming there are no clouds present.
 ClearSkyEnergyAC_kWh:The modeled energy output of the PV system based on the total available clear sky plane of array irradiance, weather conditions, shading, array configuration, and module and inverter characteristics. The clear sky irradiance is the irradiance calculated assuming there are no clouds present.
 PVModuleTemperature_DegreesC: The modeled operating temperature of the PV modules based on the ambient temperature and wind speed as well as the PV module characteristics.
 SnowLossesDC_kW:* The modeled DC power output losses in kW due to snow accumulation on the PV module surface. See the snow losses definition above for more information on the snow loss model.
 SnowLossesDC_Percent:* The percentage of total DC power output lost due to snow accumulation on the PV module surfaces. See the snow losses definition above for more information on the snow loss model.
 SoilingLossesDC_kW:* The modeled DC power output losses in kW due to dirt accumulation on the PV module surface. See the soiling losses definition above for more information on the soiling loss model.
 SoilingLossesDC_Percent* The percentage of total DC power output lost due to dirt accumulation on the PV module surfaces. See the soiling losses definition above for more information on the soiling loss model.
 TotalEnergy: Total modeled energy output of the PV system (summed to calendar month and year) based on the total available plane of array irradiance, weather conditions, shading, array configuration, and module and inverter characteristics over the period of measure specified by the request StartTime and EndTime. Units of kWh.
 TotalSnowLosses:* Total DC power output (summed to calendar month and year) lost due to snow accumulation on the PV module surfaces over the period of measure specified by the request StartTime and EndTime. Units of kW.
 AveragePercentSnowLosses:* Mean percentage of total DC power output (averaged to calendar month and year) lost due to snow accumulation on the PV module surfaces over the period of measure specified by the request StartTime and EndTime.
 TotalSoilingLosses:* Total DC power output (summed to calendar month and year) lost due to dirt accumulation on the PV module surfaces over the period of measure specified by the request StartTime and EndTime. Units of kW.
 AveragePercentSoilingLosses:* Mean percentage of total DC power output (averaged to calendar month and year) lost due to dirt accumulation on the PV module surfaces over the period of measure specified by the request StartTime and EndTime.
What’s Next?