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Spectral Selectivity vs. Spectral Error: Shedding Light on ISO 9060:2018 - OTT Blog

martin.maly@otthydromet.com (Martin Maly) — Mon, 18 May 2026 11:36:24 GMT

In late 2018, the ISO 9060 standard for solar radiometers underwent a remarkable update that brought significant changes on the classification of solar radiation measurement quality. At first glance, ISO 9060:2018 appears to be mainly a renaming of radiometer classification launched in the original version from 1990. But, as often, the devil is in the details and still causing a lot of confusion within the solar industry. In this article, we shed light on the update and explain the difference between the spectral selectivity and the newly introduced spectral error.

But let’s start with the basics. ISO 9060 is titled ‘Solar energy – Specification and classification of instruments for measuring hemispherical solar and direct solar radiation’. It defines what a pyranometer is for measuring global horizontal or global tilted irradiance (GHI and GTI) and, when shaded, diffuse horizontal irradiance (DHI). It also defines what is a pyrheliometer for measuring direct normal irradiance (DNI).

More than a renaming

There are several changes in pyranometer specifications between ISO 9060:1990 and the latest update ISO 9060:2018. The 2018 version states that the newly introduced Class A is ‘roughly corresponding’ to 1990 Secondary Standard, Class B to First Class and Class C to Second Class. ‘Roughly’ is the correct term; the performance parameters, and testing requirements, differ between the 1990 and 2018. However, it is generally the case that in terms of the uncertainty of field irradiance measurements by ISO 9060 pyranometers:

ISO 9060:1990	ISO 9060:2018
–	Class C
Second Class	Spectrally Flat Class C
First Class	Spectrally Flat Class B
Secondary Standard	Spectrally Flat Class A

So far, so good. But the most difficult aspect to understand the changes between 1990 and 2018 versions of the ISO 9060 standard is the issue of spectral response/error/sensitivity/selectivity.

Broadly speaking, the 2018 update introduced a new parameter to characterize the spectral properties of a radiometer and how it reacts on different parts of light, more precisely photons with different wavelengths. Different to the Spectral Selectivity from the 1990 version, the Spectral Error considers the important fact that the composition of sunlight, the spectrum, varies depending on the time of day in a way more relevant for the application of solar measurements. That said, the new 2018 version reflects the actual wavelength range of sunlight much better than its predecessor. Additionally, by introducing the new Class C on the entry level, the standard now covers well-built photodiode radiometers, too, that have not been covered in the old version.

Let’s go more into detail now.

ISO 9060:1990: Spectral Selectivity

The ISO 9060 standard was written for solar energy purposes to specify the minimum performance requirements for pyranometers and pyrheliometers in three classifications.

The parameters specified are: response time, zero off-sets, non-stability, non-linearity, directional response (not applicable to pyrheliometers), spectral selectivity, temperature response and tilt response.

Depending upon the sky conditions, 97% to 99% of all the solar radiation (GHI) arriving at the Earth’s surface is the wavelength range from 300 nm to 3000 nm (0.3 µm to 3.0 µm). This is way more than what our eyes can see, regarding the range of visible light spanning from 380 nm to 800 nm.

Ideally, a solar energy radiometer should have a flat response over a wide spectral bandwidth, to measure all the available incoming solar energy independent of types of PV modules or solar collectors used.

The key wavelength range for photovoltaic materials is from 350 nm to 1500 nm (0.35 µm to 1.5 µm). In ISO 9060:1990 this ’flatness’ of response is defined as ‘spectral selectivity’, the deviation from the mean response within the range from 350 nm to 1500 nm.

The limits for pyranometers are, according to ISO 9060:1990:

Secondary Standard	± 3%
First Class	± 5%
Second Class	± 10%

To comply with this requirement, pyranometers usually have a ‘thermoelectric’ type detector with a black coating that absorbs the incoming radiation, heats up a thermopile, and converts the temperature rise into a small voltage. Therefore, the heating properties of the coating covering the detector are a key component to a radiometer’s quality. In the graph below, you can see the constant absorption properties of the Kipp & Zonen thermopile detectors in the range from 350 nm to 1500 nm. The spectral response of the coating is essential to build an accurate and reliable radiometer.

Photoelectric sensors, including silicon cells and photodiodes, have a limited and uneven spectral response that does not meet the spectral selectivity specifications for a pyranometer (or pyrheliometer) as defined by ISO 9060:1990; and thus, have to be described as a ‘Silicon Pyranometer’, or similar terminology.

The graphs below show a typical clear sky solar radiation spectrum at sea level and the response of an entry-level glass-dome thermopile pyranometer, such as the Kipp & Zonen CMP3 and SMP3 models. Also, for a typical silicon photodiode sensor, like the Kipp & Zonen SP Lite2 and RT1. The spectra are normalized to the peak/maximum being 100% for easy comparison.

All Kipp & Zonen CMP series and SMP series pyranometers, and the CM4 high temperature pyranometer, have a spectral selectivity of < 3%. These models all meet the ISO 9060:1990 Secondary Standard requirement in this respect.

Now, let’s jump back to the new standard.

ISO 9060:2018: Spectral Error

The updated Second Edition of ISO 9060 was published in November 2018.

The main update relates to spectral response, the change is from spectral selectivity of 1990 to ‘clear sky irradiance spectral error’ in 2018. With that, the authors of the standard took into consideration changing characteristics of the sunlight depending on the daytime and the weather. Another intention of this change is to permit certain types of photoelectric sensor, including well-designed silicon cells and photodiodes, to be classified as an entry-level ‘pyranometer’.

The 2018 standard should provide a better and much more realistic idea of the field measurement errors that can be expected due to the spectral response of a radiometer under various conditions. The relative air mass (thickness of the atmosphere) changes with the solar zenith angle. When the sun is low in the sky the direct beam comes through more atmosphere and the spectrum of the light changes.

Sun at Solar Zenith Angle of 0°	AM = 1
Sun at Solar Zenith Angle of 48.2°	AM = 1.5
Solar Zenith Angle of 85°	AM = 11.4

Obviously, the amount of air increases when the sun hangs low at the horizon. Thus, the geometrical relationship breaks down beyond Solar Zenith Angle of 85° which is equivalent to a setting sun.

Another phenomenon to be considered: the spectral shift

Traveling through the atmosphere, the spectrum of the sunlight changes. The short wavelengths (ultraviolet and blue) are absorbed and scattered and the spectrum shifts towards the longer wavelengths (red and infrared). This also happens with cloud cover, increasing concentration of aerosols and particulates in the atmosphere and decreasing visibility. Obviously, the fixed approach from the 1990 version does not reflect the reality and an update made perfect sense.

Calculation of the spectral error

To consider different sky and atmosphere conditions affecting the actual sunlight spectrum, nine different test spectra representing various atmospheric and daytime situations are evaluated relative to the reference spectrum from another standard, the IEC 60904-3 (2016). The test spectra are provided on the ISO website under ISO 9060 edition 2.

The spectral error is calculated by comparing the relative spectral response of the respective radiometer with the reference spectrum to the response for the test spectra. The spectral response is an individual attribute of a radiometer and a quality characteristic. For each test spectrum, an error is calculated that depends on the instrument’s reaction regarding the wavelength distribution. Out of the nine spectra, the biggest error defines the radiometer’s spectral error.

The limits for pyranometers are:

Class A	± 0.5% (0.1%)
Class B	± 1% (0.5%)
Class C	± 5% (1%)

Kipp & Zonen CMP series and SMP series pyranometers, and the CM4 high temperature pyranometer, meet the appropriate classification limits for spectral error Class A by a large margin. The spectral errors are <0.16%.

The meaning of Spectrally Flat

In addition, if the pyranometer has a spectral selectivity of less than 3% (guard bands 2%) in the wavelength range from 350 nm to 1500 nm (0.35 µm to 1.5 µm) it can be termed ‘Spectrally Flat’.

In effect, this is the criteria for a ISO 9060:1990 Secondary Standard pyranometer and it is more strict than the 1990 First Class and Second Class pyranometers limits.

Kipp & Zonen Pyranometer ISO 9060 Classifications

Kipp & Zonen CMP series and SMP series pyranometers, and the CM4 high temperature pyranometer meet the appropriate classification limits for spectral error and have a spectral selectivity of < 3%. So, they all meet the ISO 9060:2018 Spectrally Flat criteria.

ISO 9060:2018	Class C	Spectrally Flat Class C	Spectrally Flat Class B	Spectrally Flat Class A
ISO 9060:1990	Not allowed	Second Class	First Class	Secondary Standard
Performance	Lower	→	→	Higher
Passive pyranometers	SP Lite2 (Fast Response)	CM4 CMP3	CMP6	CMP10 CMP21 CMP22
Smart pyranometers	RT1	SMP3	SMP6	SMP10 SMP12 (new 2022) SMP22

Note: ISO 9060:2018 Class A pyranometers must be individually tested to ensure that their temperature and directional responses meet the requirements of the standard.

Learn more in our Standards Whitepaper

In solar energy there are a number of international standards to consider when it comes to PV plant operation and maintenance.We have summarized the most relevant ISO and IEC standards that apply to weather monitoring in a whitepaper. Download it here for free.

Soiling Sensor DustIQ: Firmware Update Improves Response and Handling - OTT Blog

martin.maly@otthydromet.com (Martin Maly) — Mon, 18 May 2026 11:32:22 GMT

The pioneering soiling monitoring system Kipp & Zonen DustIQ is becoming even better. From now on, OTT HydroMet provides the DustIQ with a new firmware that simplifies both handling and calibration. Active users can update to the new firmware, too. Read this article to learn how.

Better response to soiling with increased sensitivity

Measurements taken outdoor in various desert regions across the world show that the DustIQ underestimated the degree of transmission loss with its earlier factory calibration dust slopes. Those various sites report that the outdoor dust slope is a factor reaching from 1.8 and 2.6 higher than the factory calibration. Based on these reports, an average factor 2 is found. Independent research also confirms that the DustIQ with the earlier factory calibration dust slope is underestimating transmission loss.

Now, with the firmware update to version 22000 the factory calibration dust slope is corrected with this factor 2. For example, a sensor reading 98.5% soiling ratio (1.5% transmission loss) before the update will now show an increased soiling ratio output of 97.0% (3.0% transmission loss).

Easier and faster field calibration procedure

Field experiments have shown that an easier shorter field calibration procedure is possible while retaining the measurement quality. Condensing the calibration process to a simpler and shorter procedure now requires pushing the button twice and cleaning the entire DustIQ in one step instead of multiple steps that were needed before. The shorter procedure is easier to perform and mitigates risks of possible errors. Additionally, it saves time. Also, the required soiling ratio threshold of 5% is lowered to 3%. Tests have shown that this has a minimal impact on the accuracy of the field calibration.

Plain communication thanks to numerical error code display

Previously, the DustIQ reported with binary bits (0000 0000 0000 0000) to inform users of potential errors. To simplify readings, errors are now being displayed with numerical codes. With the new firmware, the DustIQ uses registers 26 and 27 with signed integers for communication.

Register 26 is used to display if the DustIQ is ready for field calibration, if something is missing, or if there is insufficient soiling or too low sunlight.

Register 27 is used to provide feedback once the field calibration is started. These are easy-to-read numerical codes such as 1, indicating successful calibration, or 1000, that shows there is too little sunlight for field calibration.

New tare function: offsetting a negative transmission loss

Negative transmission loss values sometimes happen when the clean baseline signal shifts due to differences in site conditions. The new tare procedure adjusts the baseline to remove the offset. The procedure is described in the instruction sheet. Additionally, it minimizes the DustIQ’s tiny temperature dependency when operating at temperatures different from the factory calibration (25°C).

When to calibrate, when to tare?

A site-specific calibration is used to further increase the quantitative accuracy of the DustIQ to match the soiling that settles on the modules at your site. Calibration can be performed when both sensors read greater than 3% soiling, the sky is clear, and irradiance is greater than 500 W m-2.

The tare procedure applies a correction for negative transmission loss values that occur due to differences in factory and field environments. The tare procedure can be performed any time the DustIQ is 100% clean and the sky is clear.

Example 1:

The DustIQ is reading greater than 3.0 % transmission loss (< 97.0 soiling ratio), there are clear skies, and irradiance is greater than 500 W m-2. The ‘Local Calibration’ can be performed, followed by the Tare procedure.

Example 2:

The DustIQ is reading 2.2 % transmission loss (< 97.8 soiling ratio), there are clear skies, and irradiance is greater than 500 W m-2. The ‘Local Calibration’ cannot be performed, and the tare procedure cannot be performed without cleaning. If cleaning is done to perform the tare procedure, the time required for soiling to reach 3.0% transmission loss will be reset. If no rain is expected, it is recommended to wait until the local calibration can be performed before proceeding with the tare procedure.

Example 3:

The DustIQ is reading 0.4 % transmission loss (< 99.6 soiling ratio), there are clear skies, and irradiance is greater than 500 W m-2. The ‘Local Calibration’ cannot be performed, and the tare procedure cannot be performed without cleaning. In this example, cleaning may not erase a significant amount of soiling time, and it is recommended to clean the DustIQ and perform the tare procedure.

Calibration button changes

The calibration button can now be used to initiate one of these three actions: Below they are listed how to activate:

Reset to factory configuration: Hold button 20s, communication settings will not be changed.
Start field calibration: Hold button 4s.
Start tare function: Press button 3 times.

Instructions & Software Download

The new firmware release is compatible with all versions of the DustIQ.
Directly download the instructions and firmware package by clicking on the buttons below.

Soiling Measurement is Included in IEC Standard 61724-1 - OTT Blog

Blog Team — Mon, 18 May 2026 11:26:52 GMT

For utility-scale PV plants the Performance Ratio (PR) is an important indicator of the efficiency of all the components used. Factors like solar irradiance, PV module temperature, module orientation, module cleanliness; all the way down the chain to cables, connectors, DC and AC power (inverter performance). All of these have their influences on the real energy output compared to the ideal maximum possible output that gives one the PR.

IEC 61724-1 published in March 2017 covers every aspect of Photovoltaic System Performance Monitoring for 3 classes; High Accuracy (A), Medium Accuracy (B) and Basic Accuracy (C). It is becoming the guideline for many EPC’s to plan plant monitoring and to prove that they comply with the recommendations set out.

Even though soiling loss was known to be a big influencer on power production it wasn’t included in the original 1998 version of the standard. But, it makes sense to take it into account as the first energy loss encountered in a PV system is caused by soiling on the module glass that prevents solar radiation (=energy) reaching the solar cells. Dust and dirt on the PV modules, and the associated loss of power production, was an important ‘unknown’ in PR calculation.

Important ‘unknown’ in PR calculation

Now, the 2017 standard includes soiling ratio (SR) measurement as mandatory for Class A monitoring if the soiling losses are expected to be > 2 % and optional for Classes B and C. The data should be recorded every minute and the minimum number of monitoring points is related to plant power capacity.

The technology and methodology described in the standard are based on the solutions available at the time when the document was being prepared, just before Kipp & Zonen launched DustIQ.

The described solutions have two identical PV devices, preferably PV modules identical to those in the array to be monitored and mounted in a similar way. One device is allowed to become dirty and is the ‘soiled reference’ and the other must be regularly kept free of soiling as the ‘clean reference’. The clean device must be heated to remove frozen precipitation (frost, etc.).

Extra equipment is needed to measure short-circuit current, maximum power and the PV device temperatures. One needs to calibrate the setup under a known condition, usually STC (Standard Test Conditions) before one can start taking actual measurements. Calibration shall be done at least annually.

The accuracy of the measurement relies on having detailed information about the PV devices used; temperature dependency of current, voltage and power; to name just a few. Another important factor is that soiling of the ‘clean reference’ device will significantly influence the SR calculation and will show a higher (=better) soiling ratio than it should. This is especially important in areas with fast soiling build-up where very frequent cleaning of the device might be needed. There are also sunlight response dependencies such that IEC 61724-1 states that it may be advisable to only use measurement data from 2 hours each side of solar noon.

To deal with these inherent drawbacks, purely optical and maintenance-free alternatives have been developed and brought to market. These new systems are smaller, lighter, simpler, more affordable and allow for multiple measurement points; including right in between the PV modules.

Soiling distribution is not uniform across a PV plant and being able to measure at several points in the park allows a soiling map to be created and enables outliers to be recognised, together with providing redundancy. Having the measurement point between PV modules makes sure that the soiling monitor receives the same soiling and the same cleaning as the modules around it.

The purely optical approach takes away the dependency on solar light for the soiling measurement; and current, power and temperature monitoring are not needed to calculate the SR. The Kipp & Zonen DustIQ with its Optical Soiling Measurement (OSM) technology measures every minute, 24/7, with or without sun. It is a simple 5-minute procedure to calibrate the DustIQ on site to suit the local dust profile.

Albedo measurement for bifacial PV modules - OTT Blog

Blog Team — Mon, 18 May 2026 11:09:53 GMT

Over the last year Kipp & Zonen has received a lot of questions about albedometers from customers working in the Solar Energy market. These came from engineers and researchers working with bifacial PV modules.

Bifacial simply means that the back of the PV module has a glass panel, instead of an opaque metallized backing, and can collect light and generate electricity from both sides. This does mean a different and more expensive cell and module construction but the price premium is reducing and is offset by the increased energy yield from the available sunlight. Bifacial modules are available in a conventional framed construction or as glass-on-glass modules, both with their own advantages.

Solar irradiance reflected by the ground can be captured by the underside of the modules, which are often mounted on single-axis trackers. Bifacial modules require more space between the arrays to allow direct beam and diffuse sky light to reach the ground and be scattered back to the modules.

Depending on the type and height of the modules, row-to-row spacing and how reflective the surface is (albedo) the energy gain can be from 10% to 25%. The number of manufacturers is growing and bifacial installations look sure to take off.

What is an albedometer and what does it measure?

Albedo is defined as the ratio of the diffuse reflection of solar radiation to the total incoming solar radiation, it is dimensionless and expressed as a number between 0 and 1. Where 0 is total absorption and 1 is total reflection. For example green grass has an albedo of around 0.25, dry desert sand about 0.4, whilst fresh clean snow is more than 0.8.

An albedometer is simply two similar pyranometers measuring simultaneously, one looking up and one looking down, either back-to-back or in a single housing. Historically albedometers were mounted horizontally and used in meteorological applications and climate research and to validate satellite data. An example is monitoring the increasing absorption of sunlight by polluted glaciers, heating the surface and speeding up melting.

With the upcoming growth in the application of bifacial modules, albedo measurement is also very interesting for the solar energy market, but tilted in the plane of array of the modules instead of horizontal. For tracked installations the albedometer is normally mounted on the support structure and moves with the modules.

For single-sided, monofficial, PV modules the albedo effect (ground reflected light reaching the panel) is often neglected unless the modules are at quite a high tilt angle but, even then, it is estimated and not measured. For bifacial modules the backside can contribute 10 to 25% to the total energy production, so the albedo of the surface must be taken into account.

Because bifacial modules are more expensive than standard types it is relevant to focus on the conditions required for optimal energy yield, such as:

The surface below and around the modules must have a high albedo
The surface must remain reflective and not degrade significantly with age and weather
Strong direct radiation from the sun to make use of the surface reflection effect
The row-to-row spacing of modules increased to allow more light to reach the surface
The height of the modules designed to allow more reflected light and reduce shading
Mounting systems that minimize the blockage of light reflecting into the back of the module

Our recommendation for albedo measurement in PV

To measure the incoming plane of array irradiance for performance ratio purposes the positioning of the pyranometers is generally well understood. However, for measuring the reflected radiation coming into the back of a module there are few guidelines. It is important to select the right location, where the pyranometer is parallel to the module and receives light representative of the array. It might not be coincident with the position of the POA pyranometer.

If the conditions affecting the amount of light reflected vary along a row, it may be necessary to average over two or more downwards-facing pyranometers. The local albedo is not a fixed number but dependent on solar angle and weather conditions, such as rain or frost on the surface.

It is important to make the reflected radiation measurement part of the continuous plant monitoring system along with the incoming POA and GHI irradiance. For site prospecting it can be interesting to measure the tilted albedo at different heights and/or angles and also horizontally, to compare with satellite data.

Double DustIQ

Soiling of the top surface of PV modules is the subject of much research and investigation. However, the back surface of a bifacial module will also get soiled and it will not be washed off by rain. There is currently little information about these soiling rates.

The answer, of course, is to have DustIQ soiling monitoring systems on the underside as well as on the topside!

PV Module IV Curve: A Definitive Guide to Understanding Solar Performance

divyamaria.sunil@otthydromet.com (Divya Maria Sunil) — Tue, 14 Apr 2026 11:12:33 GMT

A PV module IV curve is one of the most powerful tools available for understanding how a photovoltaic module actually performs under real‑world conditions. More than a theoretical plot, the IV (current-voltage) curve reveals how current and voltage interact — and whether measured output reflects true system health or hidden performance losses.

For solar engineers, O&M teams, EPCs, and asset owners, PV module IV curve analysis plays a critical role in performance validation, fault detection, commissioning assurance, and long‑term reliability.

This guide explains what a PV module IV curve is, how to interpret it, what it reveals about system behavior, and why accurate environmental measurement is essential for meaningful analysis.

What is a PV module IV curve?

A PV module IV curve (current–voltage curve) is a graphical representation of the electrical behaviour of a photovoltaic module under illumination. Often referred to as the current–voltage (IV) curve, this measurement is a cornerstone of solar performance diagnostics across the PV system lifecycle.

The characteristic shape of a PV module IV curve arises from physical processes inside the solar cell. When sunlight is absorbed by the semiconductor material, electron–hole pairs are generated and separated by the internal electric field, creating current flow. At low voltages, current is primarily limited by internal resistive effects. As voltage increases, charge carrier recombination processes increasingly limit the available current, causing output current to decrease until it reaches zero at the open‑circuit voltage.

It plots:

Current (I) on the vertical axis
Voltage (V) on the horizontal axis

PV Module IV Curve

The curve is generated by sweeping the electrical load from open‑circuit to short-circuit conditions, or vice versa, and recording all possible operating points.

Under standard test conditions (STC) — 1000 W/m² irradiance, 25 °C cell temperature, AM 1.5 spectrum — the IV curve defines the module’s rated electrical characteristics. In the field, IV curves shift continuously as irradiance, temperature, and operating conditions change.

Because of this sensitivity, IV curves are widely used not only in module manufacturing and certification, but also during commissioning and targeted operational diagnostics.

Key parameters of a PV module IV curve

Understanding a PV module IV curve begins with four defining points:

Open‑circuit voltage (Voc) – The maximum voltage when no current flows.
Voc is highly temperature‑dependent and provides insight into cell behavior, long-term degradation, and electrical integrity.

Short‑circuit current (Isc) – The maximum current is produced when voltage is zero.
Isc is directly proportional to irradiance and is often used to assess how much usable sunlight reaches the module.
Maximum power point (MPP) – The point where the product of voltage and current is highest: Pmax = Vmp × Imp. This is the operating target for inverters and maximum power point tracking (MPPT) algorithms.
Fill factor (FF) – A dimensionless quality metric: FF = Pmax / (Voc × Isc) . Typical values: High‑quality crystalline silicon modules: 70–85%. A reduced fill factor often signals resistive losses, mismatch, or early degradation. Two internal electrical characteristics strongly influence fill factor: series resistance and shunt resistance. Series resistance arises from contacts, interconnects, and semiconductor material, and should be as low as possible to minimize power losses. Shunt resistance results from unintended current paths caused by material defects and should be as high as possible. Increases in series resistance or decreases in shunt resistance reduce fill factor and overall module efficiency.

IV-Curve-Fill-Factor

How environmental conditions shape the PV module IV curve

A PV module IV curve is not static. Its shape and position shift continuously with environmental conditions.

Irradiance effects

Primarily affect Isc
Lower irradiance compresses the curve vertically
Shape remains similar if measurement is accurate

Iv IV Curve - Irradiance

Temperature effects

Primarily affect Voc

Higher temperatures reduce voltage and power output

Soiling and shading

Introduce distortions in curve shape

Activate bypass diodes

Reduce fill factor and power output

Because IV curves are so sensitive, accurate irradiance and temperature measurement is essential for correct interpretation. Without reliable environmental data, it becomes difficult to distinguish between true performance issues and normal operating variation.

Degradation

Primarily affects Pmax and fill factor

Caused by environmental factors and electrical loading, etc.

IV Curve - Degradation

What a PV module IV curve reveals about system performance

Beyond basic definitions, PV module IV curve analysis enables deeper diagnostics that are not always visible in aggregated KPIs such as energy yield or performance ratio alone.

IV curve analysis supports:

Identification of soiling losses not evident in production data

Detection of partial shading and mismatch

Early warning of degradation trends

Validation of commissioning quality

Differentiation between environmental effects and true faults

In fleet‑scale systems, population‑level IV analysis helps isolate underperforming modules before yield losses escalate.

Common PV module IV curve defects and what they indicate

Common PV Module IV Curve Signatures	Likely Cause	Performance Impact
Low Isc	Soiling, shading, reduced irradiance	Reduced power output
Low Voc	High temperature, cell damage	Voltage clipping
Rounded knee (low FF)	Series resistance, degradation	Lower Pmax
Stepped curve	Bypass diode activation	Intermittent losses
Compressed voltage leg	Cell mismatch, microcracks	Long‑term degradation

These patterns are widely documented across field diagnostics literature.Under non‑uniform soiling or partial shading, losses in maximum power (Pmax) are not necessarily proportional to reductions in short‑circuit current (Isc). In these cases, relying on Isc‑based indicators alone can underestimate true power losses, making full IV curve analysis essential for accurate assessment.

Watch: PV module IV curve behaviour in real‑world conditions

The following field demonstration shows how IV curves behave under real operating conditions and why environmental correction is critical for interpretation.

Best practices for accurate PV module IV curve measurement

Reliable IV curve analysis requires:

Stable irradiance conditions, typically above 600 W/m²

Simultaneous measurement of irradiance and temperature

Normalisation to reference conditions for meaningful comparison

Traceable sensor calibration to minimise uncertainty

Without accurate environmental data, IV curves risk being misinterpreted — leading to false diagnostics or masking real performance issues.

Why measurement quality determines IV curve confidence

A PV module IV curve is only as trustworthy as the measurements behind it.

Sensor drift, angular mismatch, or poor temperature correction can distort the curve — making normal behaviour appear as underperformance or concealing genuine system issues. For this reason, measurement traceability, calibration discipline, and uncertainty awareness are foundational to credible IV curve analysis.

Reference‑grade irradiance measurement and well‑maintained sensors help ensure that IV curves support confident, data‑driven decisions rather than assumptions.

Applying IV Curve Analysis at Scale

As PV portfolios grow in size and complexity, the value of IV curve analysis extends beyond individual modules or one‑off diagnostics. Applied at scale, IV curves enable consistent performance assessment across strings, arrays, and entire fleets—supporting earlier detection of systemic issues, clearer differentiation between environmental effects and true faults, and more confident long‑term performance tracking. By combining IV curve data with accurate, traceable environmental measurements, teams can move from isolated troubleshooting toward repeatable, fleet‑level insight that supports operational decisions throughout the PV system lifecycle. In this context, IV curves serve not only as diagnostic tools, but also as a foundation for more detailed electrical performance modeling over time.

Population‑level analysis – Comparing IV curves across large module populations helps identify systematic issues that may not be visible at string or inverter level.

Bifacial module considerations – Rear‑side irradiance influences Isc and curve shape, requiring careful measurement of both front and rear plane‑of‑array conditions.

IV curves and performance ratio (PR) – IV curves complement PR analysis by explaining why performance changes occur, rather than only how much output changes.

Put IV Curve Insight into Practice

Understanding a PV module IV curve is the first step. Applying it consistently—across modules, strings, and entire portfolios—requires accurate measurement, reliable interpretation, and confidence in the data behind every curve.

Explore practical guidance and tools that help teams move from IV curve understanding to repeatable, data‑driven performance assessment.

Soiling Measurement for Capacity Testing in Utility‑Scale Solar

divyamaria.sunil@otthydromet.com (Divya Maria Sunil) — Tue, 14 Apr 2026 10:45:12 GMT

Why Measurement Strategy Matters More Than Ever

Executive Summary

Soiling is a well‑established cause of energy loss in photovoltaic (PV) systems. Less widely recognized is its impact during capacity and performance testing, where even small losses can have contractual and financial consequences.

Field research presented at the IEEE Photovoltaic Specialists Conference shows that soiling losses of just 1–2% can influence capacity testing outcomes in utility‑scale solar plants. The research also highlights a recurring issue: soiling is often measured too late to be useful during commissioning.

This page explains why early, accurate soiling measurement is essential for reducing performance risk, supporting defensible capacity testing, and enabling confident decision‑making across the solar project lifecycle.

What Is Soiling in Solar PV Systems?

Soiling refers to the accumulation of dust, dirt, pollen, agricultural residue, and other airborne particles on the surface of PV modules. These particles reduce light transmission through the module glass, resulting in measurable power losses.

The magnitude of soiling losses varies depending on:

Local climate and precipitation patterns

Land use and nearby activities such as farming or construction

Wind direction and seasonal effects

Cleaning frequency and site accessibility

While soiling is commonly addressed during operation, its effect during commissioning and capacity testing is often underestimated.

Why Soiling Measurement for Capacity Testing Requires a Different Strategy

Utility‑scale PV projects must demonstrate performance compliance before reaching milestones such as substantial completion. Capacity testing is commonly used to validate system output, often following standards such as ASTM E2848 or evolving international methods.

Capacity tests allow only limited total losses. Under these conditions, even modest unexplained losses can cause a test to fail.

Field data shows that soiling losses of 1–2%, when combined with normal measurement uncertainty, can push a technically sound system outside acceptable performance limits, leading to:

Delays in project completion

Disputes between developers, EPCs, and asset owners

Unplanned cleaning or retesting costs

Increased uncertainty for financiers and investors

When capacity tests fail due to unexplained losses, the consequences extend beyond technical troubleshooting. Delays at this stage can trigger contractual disputes between developers, EPCs, asset owners, and third‑party engineers—particularly around responsibility for cleaning, loss compensation, and test acceptance criteria.

In many projects, the treatment of soiling during capacity testing is not fully defined in contracts prior to construction. This can lead to last‑minute negotiations, unplanned cleaning activities, or repeat testing campaigns, all of which increase cost and schedule risk. By contrast, projects that incorporate defensible soiling measurement strategies early in the construction timeline are better positioned to manage these risks transparently and efficiently.

Accurate soiling data does not eliminate commercial discussions—but it provides a shared, objective basis for them.

Soiling in the Context of Capacity Testing Standards

Capacity testing in utility‑scale solar is typically performed within tightly defined frameworks, such as ASTM E2848 in the United States and evolving international methods including IEC 61724‑1. These methodologies are designed to validate system performance against modeled expectations within narrow uncertainty bands.

Under these standards, total allowable losses are limited. When soiling losses are not explicitly measured—or cannot be defensibly quantified—they are effectively treated as unexplained performance degradation. Even small unaccounted losses in the range of 1–2% can therefore cause a capacity test to fall outside acceptable limits, despite the system being fundamentally sound.

This is why soiling measurement for capacity testing must be approached differently than long‑term operational monitoring. Measurement strategies that are sufficient for O&M reporting may not provide data of adequate timing, resolution, or representativeness for commissioning and performance validation. Early, standards‑aligned measurement planning is essential to ensure that environmental losses can be confidently distinguished from system‑related issues during formal testing.

The Hidden Risk: Soiling Is Often Measured Too Late

Most utility‑scale solar plants include soiling sensors as part of the meteorological station. These sensors are designed primarily for long‑term operational monitoring, not commissioning.

As a result, they are often installed after PV modules have already been exposed to environmental conditions for weeks or months.

This creates a mismatch:

Modules have accumulated soiling

Sensors begin from a clean state

Because the sensors do not share the same exposure history as the modules, their data cannot reliably quantify soiling losses during capacity testing.

Common Workarounds and Their Limitations

When representative soiling data is unavailable, project teams often rely on:

Visual inspection or photographs

Pre‑ and post‑cleaning electrical measurements

Negotiated assumptions about acceptable losses

These approaches introduce subjectivity, cost, and delay. Research indicates that many of these challenges can be avoided through earlier measurement planning.

Measure Soiling from Day One: A Proactive Strategy

Field research consistently points to a simple recommendation:

Soiling sensors should be deployed concurrently with PV module installation.

Installing sensors at the same time as modules ensures identical environmental exposure throughout construction and commissioning. This enables:

Reliable compensation of soiling losses during capacity testing

Early identification of excessive soiling

Data‑driven cleaning decisions

Reduced contractual ambiguity

Importantly, this approach does not require early SCADA integration. Sensors can be installed and left unpowered during construction because it does not require any calibration, allowing natural soiling accumulation.

A Common Misconception: SCADA Integration Is Not Required Early

A frequent barrier to early soiling sensor deployment is the assumption that sensors must be powered, logged, and integrated into SCADA systems from the moment they are installed. Field research shows this is not the case.

For capacity testing, the most critical requirement is that soiling sensors share the same exposure history as PV modules. Sensors can be installed concurrently with module deployment and left unpowered during construction. During this time, they naturally accumulate dust and are cleaned by rainfall in the same way as the modules.

Once commissioning approaches, the sensors can be activated and immediately provide representative soiling loss data—without requiring months of prior logging. This simple shift in deployment strategy removes a major practical obstacle to early soiling measurement and enables more reliable compensation of soiling losses during testing.

What Makes a Soiling Sensor Suitable for Capacity Testing?

Research identifies four requirements for sensors used during construction and commissioning:

Calibration‑free operation – Allows immediate installation without delaying project schedules.

High sensitivity at low loss levels – Capacity testing requires resolution below 1%, with sensitivity to changes under 0.5%.

Ease of deployment – Sensors must be compact, robust, and suitable for construction environments.

Cost‑effective scalability – Soiling varies across large sites; distributed measurement improves confidence.

These principles align with Kipp & Zonen’s long‑standing focus on measurement accuracy, robustness, and traceability.

With Atonometrics now part of the Kipp & Zonen portfolio, optical soiling measurement is integrated into a broader, bankable solar measurement framework.

Field Evidence: Soiling Is Spatially Variable

Field data from a ~100 MW utility‑scale PV plant shows that soiling is rarely uniform across a site. Measurements revealed:

Rapid accumulation during nearby agricultural activity

Losses reaching several percent within weeks

Clear spatial variation depending on location and wind exposure

These results demonstrate that assuming uniform soiling across a utility‑scale site can materially misrepresent actual performance during capacity testing, reinforcing the need for distributed soiling measurement, rather than relying on a single sensor to represent an entire plant.

Linking Soiling Data to Capacity Test Outcomes

Across multiple capacity testing campaigns, field measurements showed a clear relationship between:

Reductions in soiling losses (from rainfall or cleaning)

Improvements in measured capacity test ratios

This demonstrates the value of soiling data in distinguishing environmental effects from system‑related issues during performance validation.

Understanding the Limits of Soiling Measurement

While optical soiling sensors accurately measure transmission losses, they do not capture all electrical loss mechanisms. Non‑uniform soiling patterns can lead to additional power losses that require complementary diagnostics.

Soiling measurement should therefore be part of a comprehensive performance assessment strategy, not a standalone metric.

From Reactive Testing to Proactive Performance Assurance

Soiling has traditionally been treated as an operational issue. Research now shows it should also be considered a commissioning and project‑delivery risk.

Early soiling measurement strategies complement broader solar resource and irradiance measurement practices, helping ensure consistency between commissioning data, long‑term performance monitoring, and bankability assessments across the project lifecycle.

At Kipp & Zonen, accurate measurement is not just about data — it is about enabling confident, defensible decisions across the full lifecycle of a solar asset.

Contact us to learn how early, accurate soiling measurement can reduce performance risk and support confident capacity testing in your utility‑scale solar projects.

Webinar: How to Process and Interpret Soiling Data - Kipp & Zonen Blog

Kipp & Zonen Blog Team — Mon, 13 Apr 2026 12:38:29 GMT

PV modules perform best when they are clean. When contamination collects on the surface of modules, sunlight is blocked from reaching the PV cell, thus reducing the amount of electricity generated. This performance loss is described by the transmission loss and the soiling ratio.

The Kipp & Zonen DustIQ is a unique optical instrument for accurately measuring the soiling ratio of PV modules, providing information required to keep PV installations operating effectively.

In our recent webinar, Sajad Badalkhani, Service Manager Europe at OTT HydroMet, introduces the phenomenon of soiling and the measurement principles of the DustIQ. He also explains how to process and interpret the readings. Watch the recording below.

What is PV Soiling?

PV soiling is the accumulation of solid material on the surface of a PV module.

When dirt and particulate matter collect on a PV device, it both absorbs and scatters incident light. This has a major effect on energy yield. Alongside high temperatures, soiling is one of the primary causes of PV output degradation and is known to account for losses of three to four percent of global PV production.

PV soiling can result from many sources, including mineral dust, bird droppings, organic growth (such as lichen, fungi and mosses), pollen, engine exhaust and agricultural emissions. The rate at which these materials accumulate depends on many factors, including properties of the dust and PV module surfaces, as well as climate-related factors such as wind, rain, temperature, irradiance and humidity. PV module orientation can also have a significant effect. Interpreting and understanding regional soiling losses depends on careful consideration of all these factors.

The impact of soiling is generally described in two quantities:

Soiling Ratio (SR): The ratio of the actual power output of a soiled PV array to the power output that would be expected if the array were clean.
Transmission Loss (TL) or Soiling Level (SL): Fractional power loss due to soiling given by 1-SR.

For example, if a PV array were soiled to the point that it produced 5% less power than its clean state, the soiling ratio would be 95%, while the transmission loss would be 5%.1

There are two common methods for measuring the soiling ratio of a PV array.

One method is to set up two reference PV devices and allow one to soil naturally (at the same rate as the rest of the array) while keeping one clean. Despite being common, this method produces an instantaneous value of the soiling ratio, with uncertainties of the measurement, in particular, due to misalignment between the two reference devices and also due to the angle-dependence of scattering by soiling. This method also requires that one of the reference devices is perpetually cleaned.

The other method is to use an optical measurement device such as DustIQ. Optical systems work by producing an infrared light pulse from inside the module – i.e., from underneath the soiled surface – and measuring the portion that reflects and scatters back. Using a calibration constant, this measurement can then be converted into a soiling ratio measurement which is completely independent of the angle of incidence.

Ensuring Reliable Data Collection

There are several factors that have an influence on the reliability of soiling measurements.

Location and Number of Sensors

IC61724 sets out recommendations for the number of soiling sensors to be used for a given AC system size in megawatts1 However, this is something of a rule of thumb. It is possible to have significant variations in soiling profiles between sensors when following these recommendations, especially where there are variations in ground textures or wind speed and direction.

The best practice is always to observe the site and check if it can be divided into different “dust regions” – each of these regions should be monitored, ideally by a centrally located sensor.

Installation, Commissioning and Maintenance

DustIQ can be placed anywhere on an array – at the top, side or bottom of a PV module. However, we advise installing it vertically: soiling typically varies most in the vertical direction, so horizontal installation can be less effective at getting the full picture.

We also recommend investigating electrical protection. DustIQ is equipped with features to ensure it remains electrically protected in the field – however it is always a good idea to provide external protection as well.

Make sure to check and validate the Modbus input register values, to ensure a reliable commissioning process.

To best utilize your soiling data, it is essential to consider the following factors:

Sampling frequency: Soiling is a slow phenomenon, so even sampling just once per day can provide useful results. However, we recommend sampling every 15 minutes for better insight.
Environmental parameters: Local environments dictate soiling conditions, so having data on environmental parameters – such as weather – can provide a much better understanding of soiling.
Local calibration: DustIQ is calibrated in the lab using a standard dust sample. The properties of dust and particulate matter can vary greatly – thus, DustIQ must also be locally calibrated at least once.
Taring: “Taring” is the process of compensating for the zero offset of data. This should be carried out regularly to prevent drift over time – we recommend doing so each time your modules are cleaned.

Processing Data to Maximize Findings

Proper data handling is essential in order to optimize the utility of your DustIQ data. Follow these steps for easy-to-interpret data:

1. Reject outliers.

This means removing any data points which are unrealistic.

2. Linearly interpolate missing data.

3. Select solar noon values.

Working with solar noon values minimizes the effects of “daily transients” due to frost and dew and also minimizes the effects of angle-of-incidence variation throughout the day. We recommend selecting data gathered from 12-2 pm.

4. Average over solar noon data.

5. Apply zero-offset compensation/taring.

If your DustIQ is not routinely tared, it is essential to compensate for zero offset during data processing. Though it is best to tare data when cleaning is carried out, it is possible to address this even if you are not cleaning your PV modules by considering “environmental cleaning conditions.” Incorporating weather data enables you to tare soiling measurement data according to specific environmental factors.

6. Smooth data with a moving-average filter.

Following these simple steps ensures you can convert any unclear noisy measurements into usable and simple-to-interpret soiling data, revealing trends and enabling efficient maintenance.

In 2022, we released a new DustIQ firmware update that simplifies local calibration and taring and improves the sensitivity of measurements.

To learn more about processing data from DustIQ, watch the webinar above or get in touch with our experts with any questions.

Class A Pyranometers: Choosing the Right Type for Your PV Plant - Kipp & Zonen Blog

martin.maly@otthydromet.com (Martin Maly) — Mon, 13 Apr 2026 12:37:19 GMT

To ensure top performance of solar PV installations, leading irradiance measurement instrumentation is required for both site assessment and resource monitoring. The quality of pyranometers and pyrheliometers is defined by the international standard ISO 9060. Within its highest Class A, OTT HydroMet manufactures three different smart pyranometers under their Kipp & Zonen brand.

Below we provide an overview on the international standard ISO 9060 and our Class A certified Kipp & Zonen pyranometers. But let’s start with the standard itself.

Introduction: What is ISO 9060

ISO, an acronym for the International Organization for Standardization, brings together global experts to develop and publish standards for varying industries. In 1990, ISO released ISO 9060 for the classification and specification if instruments measuring hemispherical and direct solar radiation. The 2018 update also included new classifications (Class A, B, and C) and changed the spectral response parameter from spectral selectivity to spectral error.

If you’d like to learn more about the changes to the original ISO 9060 with the release of the 2018 version, check the article Spectral Selectivity vs. Spectral Error: Shedding Light on ISO 9060:2018.

Kipp & Zonen Pyranometers

Following the international standard ISO 9060, only the most accurate instruments pyranometers are rated certified as Class A. Still, there are is a variety of pyranometers to choose from. OTT HydroMet’s comprehensive portfolio of premium environmental monitoring equipment includes three pyranometer models that fulfill the high requirements of Class A: the Kipp & Zonen SMP10, the SMP12, and the SMP22.

Similarities Across the SMP Series

Let’s start with the similarities: The Kipp & Zonen SMP range of smart pyranometers is based on the proven technology of the analogue CMP series, but has a micro-processor, memory, and firmware that makes them digital and faster. All SMP pyranometers are ‘Spectrally Flat’ according to ISO 9060, which means they provide a steady response across the solar spectrum. In technical terms, spectrally flat pyranometers have a spectral selectivity of less than 3% (guard bands 2%) in the wavelength range from 350 nm to 1500 nm (0.35 µm to 1.5 µm).

All SMP pyranometers communicate via Modbus RTU, which makes it a very convenient choice for easy SCADA integration.

Standard 5 Year Warranty

Engineers and technicians around the world appreciate the long lifetime of Kipp & Zonen pyranometers, which usually exceeds 10 years significantly. That’s why we trust in our products and grant a five year warranty – that is more than double the standard warranty of other goods – for all CMP and SMP pyranometers.

OTT HydroMet offers three different Class A smart pyranometers under the product brand Kipp & Zonen:

SMP10

SMP12

SMP22

SMP10: Our Proven Best-seller

On PV plants around the world, whenever you spot a yellow cable, chances are high to find a Kipp & Zonen SMP10. With over 65,000 manufactured devices, the SMP10 is the most sold instrument from OTT HydroMet’s product brand Kipp & Zonen. It is used for reliable and accurate measurement of the incoming sunlight including specific components such as GHI, PoA, DHI, albedo, or others. The SMP10 is a spectrally flat Class A pyranometer and has an internal desiccant that will last for at least 10 years if the housing is not opened. This minimizes maintenance significantly. The SMP10 is available in two versions; both communicate via RS485 Modbus RTU and one analogue output, as version V (0 to 1 V) or A (4 to 20 mA).

SMP12: Kipp & Zonen’s Most Innovative Pyranometer Yet

The new SMP12 is a fast response spectrally flat Class A pyranometer combining solid-state dome heating, no moving parts, and best-in-class surge protection to maximize accuracy and minimize maintenance. Thanks to its smaller detector and tailored firmware, the SMP12 reacts quicker than any other SMP model. Additionally, it features integrated sensors to monitor the tilt angle in pitch and roll as well as and internal humidity, which enables maximum control on remote operation.

SMP22: The World’s Most Accurate Smart Pyranometer

Users who expect the highest possible accuracy choose the SMP22. Meteorologists and climate researchers rely on the SMP22 and its analogue brother, the CMP22. Both are used around the globe as part of the Baseline Surface Radiation Network (BSRN). The SMP22 shares all class-leading characteristics of the CMP22, in addition to the advantages of a smart pyranometer, including temperature compensation over a large range. A 10 K thermistor internal temperature sensor is standard, a Pt-100 sensor is optional. The SMP22 is available in two versions; both communicate via RS485 Modbus RTU and one analogue output, as version V (0 to 1 V) or A (4 to 20 mA). In recent years, there is a growing demand for the SMP22 on large utility-scale PV plants, too.

Overview

This table gives an overview which pyranometer is the appropriate one for your purpose.

	SMP10	SMP12	SMP22
Spectrally Flat Class A (ISO 9060:2018)	✅	✅	✅
Integrated heater	-	✅	-
Fast Response Time (ISO 9060:2018)	-	✅	-
Response time (63%)	< 0.7 s	< 0.15 s	< 0.7 s
Communication via RS485 Modbus RTU	✅	✅	✅
Analogue output available (A- and V- versions)	✅	-	✅
Tilt angle monitoring	-	✅	-
Internal humidity monitoring	-	✅	-
Zero offset A // thermal radiation (at 200 W/m²)	< 7 W/m²	< 1 W/m²	< 3 W/m²
Zero offset B // temperature change (5 K/h)	< 2 W/m²	< 1.5 W/m²	< 1 W/m²
Directional response (up to 80° with 1000W/m² beam)	< 10 W/m²	< 10 W/m²	< 5 W/m²
Temperature response (-40 °C to +70 °C)	< 2%	< 2%	< 0.3%

Are you interested in learning more? You can find the technical specifications and more details of the three models above and other Kipp & Zonen pyranometers in the Pyranometer brochure. Download the brochure by clicking on the button below. Further questions? Our team of researchers and technical experts is happy to help.

Podcast: Analog or Smart Sensor? Choosing the Right Instrument - Kipp & Zonen Blog

martin.maly@otthydromet.com (Martin Maly) — Mon, 13 Apr 2026 12:35:23 GMT

Food for geeks! Most measurement instruments are either analog or smart. This applies to our Kipp & Zonen portfolio for solar irradiance monitoring, too. But which one to choose for which application?

In this episode of OTT CAST, we welcome Sajad Badalkhani, an experienced technical expert for solar monitoring instruments. We discuss the technical differences between analog and smart sensors and who they are designed for. Sajad explains the concept of the Modbus protocol and introduces the SMP12, an ISO 9060:2018 Class A pyranometer with integrated heating and built-in sensors for remote monitoring of humidity and tilt angle.

Tune in and learn about:

Pros and cons of analog and smart sensors, as the CMP and SMP series
Introducing the Modbus protocol
Next level monitoring with the new Kipp & Zonen SMP12

In case the embedded player does not appear, listen to the episode on Buzzsprout via this link.

How to Choose the Right Sun Tracker? - Kipp & Zonen Blog

martin.maly@otthydromet.com (Martin Maly) — Mon, 13 Apr 2026 12:33:50 GMT

A complete measurement of solar irradiance includes global (GHI), direct (DNI), and diffuse (DHI or DIF) radiation. To accomplish this, a high-quality solar monitoring station typically comprises an automatic sun tracker fitted with instruments to measure these components individually. Depending on the application, long-wave radiation and reflected short-wave radiation may be added to provide the total radiation balance. This is especially relevant for meteorological and climatological observations. Furthermore, ultraviolet radiation and other measurements may also be taken.

For most applications it is not only the momentary value of the parameter being measured that is important. Variations in the amount of energy received over a period of time, and the effects to be expected as a result, are extremely important. It is usual to measure and record meteorological parameters during the diurnal cycle (daily course) in order to make predictions about the future weather conditions.

RaZON+

SOLYS2

SOLYS Gear Drive

Three models, choose the right sun tracker for your application

To keep all instruments aligned with the solar orbit, automatic sun trackers follow the path of the sun. OTT HydroMet offers three different models under the product brand Kipp & Zonen:

RaZON+

ALL-IN-ONE Solar Monitoring System that provides global (GHI), direct (DNI) and diffuse (DHI) irradiance and can be expanded to a full weather station with third party sensors. GPS and data logging are integrated. Customer friendly interface and anti-soiling design to reduce maintenance.

Applications: It is a perfect fit for small meteorological stations, used in temperate climates. Ideal for solar energy resource mapping, Concentrated Solar Power (CSP), Concentrated Photovoltaics (CPV) and tracking PV site prospecting. Continuous power plant monitoring.

SOLYS2

Versatile sun tracking solution, a wide range of radiometers can be mounted. The integrated GPS automatically configures location and time. Solar position and status monitoring information are available via the communication ports.

Applications: For use in harsher climates and to carry multiple instruments. Meteorology, climatology and BSRN stations. Solar energy site prospecting and plant monitoring.

SOLYS Gear Drive

High-end sun tracker for all weather conditions and locations. It builds on the features of the SOLYS2 and has enhanced capabilities that make it suitable for use with heavy loads and in the harshest climates, such as polar conditions.

Applications: Designed for use in extreme climates; very hot, very cold and high wind speeds. Can carry a large number of instruments and heavy loads. Ideal for many scientific research purposes.

Overview

This table gives an overview which sun tracker is the appropriate one for your purpose.

	RaZON+	SOLYS2	SOLYS Gear Drive
Best price/performance ratio	✅	✅	✅
Easy transportable, low weight	✅	-	-
Low power	✅	-	-
Integrated measurement / calculation of GHI, DNI, DIF	✅	-	-
Anti-soiling radiometer design	✅	-	-
Allows fitting of non Kipp & Zonen radiometers	-	✅	✅
Other instruments can be loaded	-	✅ up to 20 kg	✅ up to 80 kg
Operates under extreme cold conditions (< -20 °C)	-	✅ (AC power only)	✅ (AC power only)
Sun sensor for active tracking	-	✅ optional	✅
Daily uncertainty GHI	2%	1 to 2%	1 to 2%
Daily uncertainty DNI	2%	1%	1%
Baseline Surface Radiation Network (BSRN) compatible	-	✅	✅

Are you interested in learning more? You can find the technical specifications and more details on the Sun Tracker Comparison. Further questions? Our team of researchers and technical experts is happy to help.

Blog - K&Z

Spectral Selectivity vs. Spectral Error: Shedding Light on ISO 9060:2018 - OTT Blog

More than a renaming

ISO 9060:1990

ISO 9060:2018

ISO 9060:1990: Spectral Selectivity

ISO 9060:2018: Spectral Error

Another phenomenon to be considered: the spectral shift

Calculation of the spectral error

The meaning of Spectrally Flat

Kipp & Zonen Pyranometer ISO 9060 Classifications

Learn more in our Standards Whitepaper

Soiling Sensor DustIQ: Firmware Update Improves Response and Handling - OTT Blog

Better response to soiling with increased sensitivity

Easier and faster field calibration procedure

Plain communication thanks to numerical error code display

New tare function: offsetting a negative transmission loss

When to calibrate, when to tare?

Example 1:

Example 2:

Example 3:

Calibration button changes

Instructions & Software Download

Soiling Measurement is Included in IEC Standard 61724-1 - OTT Blog

Important ‘unknown’ in PR calculation

Albedo measurement for bifacial PV modules - OTT Blog

What is an albedometer and what does it measure?

Our recommendation for albedo measurement in PV

Double DustIQ

PV Module IV Curve: A Definitive Guide to Understanding Solar Performance

What is a PV module IV curve?

Key parameters of a PV module IV curve

How environmental conditions shape the PV module IV curve

Irradiance effects

Temperature effects

Soiling and shading

Degradation

What a PV module IV curve reveals about system performance

Common PV module IV curve defects and what they indicate

Watch: PV module IV curve behaviour in real‑world conditions

Best practices for accurate PV module IV curve measurement

Why measurement quality determines IV curve confidence

Applying IV Curve Analysis at Scale

Put IV Curve Insight into Practice

Soiling Measurement for Capacity Testing in Utility‑Scale Solar

Why Measurement Strategy Matters More Than Ever

Executive Summary

What Is Soiling in Solar PV Systems?

Why Soiling Measurement for Capacity Testing Requires a Different Strategy

Soiling in the Context of Capacity Testing Standards

The Hidden Risk: Soiling Is Often Measured Too Late

Common Workarounds and Their Limitations

Measure Soiling from Day One: A Proactive Strategy

A Common Misconception: SCADA Integration Is Not Required Early

What Makes a Soiling Sensor Suitable for Capacity Testing?

Field Evidence: Soiling Is Spatially Variable

Linking Soiling Data to Capacity Test Outcomes

Understanding the Limits of Soiling Measurement

From Reactive Testing to Proactive Performance Assurance

Webinar: How to Process and Interpret Soiling Data - Kipp & Zonen Blog

What is PV Soiling?

Ensuring Reliable Data Collection

Location and Number of Sensors

Installation, Commissioning and Maintenance

Processing Data to Maximize Findings

Class A Pyranometers: Choosing the Right Type for Your PV Plant - Kipp & Zonen Blog

Introduction: What is ISO 9060

Kipp & Zonen Pyranometers

Similarities Across the SMP Series

Standard 5 Year Warranty

SMP12: Kipp & Zonen’s Most Innovative Pyranometer Yet

SMP22: The World’s Most Accurate Smart Pyranometer

Overview

Further reading & listening

Podcast: Analog or Smart Sensor? Choosing the Right Instrument - Kipp & Zonen Blog

Further reading

How to Choose the Right Sun Tracker? - Kipp & Zonen Blog

Three models, choose the right sun tracker for your application

RaZON+

SOLYS2