QCPV: A quality control algorithm for distributed photovoltaic array power output
•We note the absence of a standard method for quality controlling solar PV data.•We present a two-part approach to parameterize and quality control PV power output.•The parameterization captures system specific metadata (tilt, azimuth, loss factor).•The quality control routine applies system specifi...
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| Published in | Solar energy Vol. 143; pp. 120 - 131 |
|---|---|
| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
New York
Elsevier Ltd
01.02.2017
Pergamon Press Inc |
| Subjects | |
| Online Access | Get full text |
| ISSN | 0038-092X 1471-1257 |
| DOI | 10.1016/j.solener.2016.12.053 |
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| Abstract | •We note the absence of a standard method for quality controlling solar PV data.•We present a two-part approach to parameterize and quality control PV power output.•The parameterization captures system specific metadata (tilt, azimuth, loss factor).•The quality control routine applies system specific and across system checks.
Distributed PV power output measurements and their metadata are subject to significant errors and uncertainty. However, no standard mechanism for quality controlling these data is currently available within the literature. For this purpose, we present a two part approach to parameterize PV system metadata and quality control their power output measurements. These methods are based on open-source solver routines and require only one exogenous input (ambient temperature), and therefore are widely applicable. The method allows for PV array orientation to be determined to within ∼4°. Furthermore a loss factor LF is derived which captures overall PV system losses and correctly detects a mean degradation of the modules of ∼0.5% per annum over time. The central routine, entitled QCPV, imposes system specific limits on the measured data mainly through the use of the extraterrestrial irradiance and the clear sky index for photovoltaics kpv. It also enables, amongst other things, the detection of cloud enhancement events and spurious power output reporting through the application of across systems statistics. |
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| AbstractList | •We note the absence of a standard method for quality controlling solar PV data.•We present a two-part approach to parameterize and quality control PV power output.•The parameterization captures system specific metadata (tilt, azimuth, loss factor).•The quality control routine applies system specific and across system checks.
Distributed PV power output measurements and their metadata are subject to significant errors and uncertainty. However, no standard mechanism for quality controlling these data is currently available within the literature. For this purpose, we present a two part approach to parameterize PV system metadata and quality control their power output measurements. These methods are based on open-source solver routines and require only one exogenous input (ambient temperature), and therefore are widely applicable. The method allows for PV array orientation to be determined to within ∼4°. Furthermore a loss factor LF is derived which captures overall PV system losses and correctly detects a mean degradation of the modules of ∼0.5% per annum over time. The central routine, entitled QCPV, imposes system specific limits on the measured data mainly through the use of the extraterrestrial irradiance and the clear sky index for photovoltaics kpv. It also enables, amongst other things, the detection of cloud enhancement events and spurious power output reporting through the application of across systems statistics. Distributed PV power output measurements and their metadata are subject to significant errors and uncertainty. However, no standard mechanism for quality controlling these data is currently available within the literature. For this purpose, we present a two part approach to parameterize PV system metadata and quality control their power output measurements. These methods are based on open-source solver routines and require only one exogenous input (ambient temperature), and therefore are widely applicable. The method allows for PV array orientation to be determined to within ∼4°. Furthermore a loss factor LF is derived which captures overall PV system losses and correctly detects a mean degradation of the modules of ∼0.5% per annum over time. The central routine, entitled QCPV, imposes system specific limits on the measured data mainly through the use of the extraterrestrial irradiance and the clear sky index for photovoltaics k^sub pv^. It also enables, amongst other things, the detection of cloud enhancement events and spurious power output reporting through the application of across systems statistics. |
| Author | Killinger, Sven Müller, Björn Engerer, Nicholas |
| Author_xml | – sequence: 1 givenname: Sven surname: Killinger fullname: Killinger, Sven organization: Fraunhofer Institute for Solar Energy Systems ISE, 79110 Freiburg, Germany – sequence: 2 givenname: Nicholas surname: Engerer fullname: Engerer, Nicholas email: nicholas.engerer@anu.edu.au organization: Fenner School of Environment and Society, The Australian National University, Canberra, Australia – sequence: 3 givenname: Björn surname: Müller fullname: Müller, Björn organization: Fraunhofer Institute for Solar Energy Systems ISE, 79110 Freiburg, Germany |
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| SubjectTerms | Distributed photovoltaics Electric power Measurement Metadata Output Parameterization of metadata Power output Quality control Solar energy |
| Title | QCPV: A quality control algorithm for distributed photovoltaic array power output |
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