Editing Pyranometer (section)

==== Usage ====
[[File:Thermopile pyranometer as part of MeteoStation.jpg|thumb|left|Thermopile pyranometer as part of a meteorological station]]
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Thermopile pyranometers are frequently used in [[meteorology]], [[climatology]], [[climate change (general concept)|climate change]] research, [[building engineering physics]], [[photovoltaic system]]s, and monitoring of [[photovoltaic power stations]].

The solar energy industry, in a 2017 standard, IEC 61724-1:2017,<ref>[https://webstore.iec.ch/publication/33622 IEC 61724-1:2017]</ref> has defined the type and number of pyranometers that should be used depending on the size and category of solar power plant. That norm advises to install thermopile pyranometers horizontally (GHI, Global Horizontal Irradiation), and to install photovoltaic pyranometers in the plane of PV modules (POA, Plane Of Array) to enhance accuracy in Performance Ratio calculation.

To use the data measured by a pyranometer (horizontal or in-plane), quality assessment (QA) of the raw measured data is necessary.<ref>{{Cite web |date=25 Mar 2022 |title=Growing Pain #3: On-site measurements in large-scale solar |url=https://solargis.com/resources/blog/best-practices/growing-pain-3-on-site-measurements-in-large-scale-solar }}</ref> This is because the pyranometer measurements typically suffer from environment-induced errors but also handling and neglect errors, such as:

* Pollution of the glass dome (e.g. deposition of atmospheric dust, bird droppings, snowfall), which reduces the measured irradiance
* Issues with positioning, resulting in measurements in a different plane (i.e. not horizontal or in-plane with PV modules) than expected 
* Data logger errors resulting in e.g. static values, oscillations, or data capped to a certain value
* Reflections and shading from the surrounding objects resulting in inaccurate measurements (i.e. not corresponding to solar irradiance)
* Calibration issues of the instrument, leading to measurement errors, offset, or drift over time
* Dew, snow, or frost on the glass dome on lower-end pyranometers not equipped with heating units

Each of the above issues appears as a specific pattern in the measured time series. Thanks to this, the issues can be identified, the erroneous records flagged, and excluded from the dataset. The methods employed for data QA can be either manual, relying on an expert to identify the patterns, or automated, where an algorithm does the job. As many of the patterns are complex, not easily described, and require a particular context, manual QA is very common. A specialist software with suitable tools is required to perform the QA.

After the QA procedure, the remaining ‘clean’ dataset reflects the solar irradiance at the measurement site to within the uncertainty of measurement of the instrument. The ‘clean’ measured dataset can be optionally enhanced with data from a satellite-based solar irradiance model. This data is available globally for a much longer time period (typically decades into the past) than the data measured by the pyranometer. The satellite model data can be correlated (or site adapted) to the pyranometer-measured data to produce a dataset with a long time period of data accurate for the specific site, with a defined uncertainty. Such data can be used to perform bankable solar resource studies or produce [[Solar irradiance#Solar potential maps|Solar potential maps]]. 

For monitoring of operational PV power plants, pyranometers play an essential role in verifying the solar irradiance available at any given time or over a certain time period. Due to weather variability, redundancy, and the spatial scale of contemporary solar plants (above 100MWp), multiple pyranometers are installed to provide accurate solar irradiation for each section of the PV power plant. IEC 61724-1:2017<ref>{{Cite web |title=IEC 61724-1:2017 {{!}} IEC |url=https://webstore.iec.ch/en/publication/33622 |access-date=2024-09-04 |website=webstore.iec.ch}}</ref> international standard for example calls for at least 4 Class A thermopile pyranometers to be installed at 100MWp PV power plant at all times.

Solar measurements that were QA’d could be used to derive Key Performance Indicators (KPI) such as Performance ratio* - metrics used in asset health monitoring or various contractual scenarios relating to energy produced (billing) or asset management (i.e. O&M). In these calculations, the measured sum of in-plane irradiation over a certain period is used as the determinant to which normalized produced PV electricity is compared to. Due to the difficulty of obtaining reliable in-plane measurements, especially in operational power plants, Energy Performance Index is increasingly being used instead of the older Performance ratio metric.