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Blind photovoltaic modeling intercomparison: A multidimensional data analysis and lessons learned
The Photovoltaic (PV) Performance Modeling Collaborative (PVPMC) organized a blind PV performance modeling intercomparison to allow PV modelers to blindly test their models and modeling ability against real system data. Measured weather and irradiance data were provided along with detailed descriptions of PV systems from two locations (Albuquerque, New Mexico, USA, and Roskilde, Denmark). Participants were asked to simulate the plane-of-array irradiance, module temperature, and DC power output from six systems and submit their results to Sandia for processing. The results showed overall median mean bias (i.e., the average error per participant) of 0.6% in annual irradiation and −3.3% in annual energy yield. While most PV performance modeling results seem to exhibit higher precision and accuracy as compared to an earlier blind PV modeling study in 2010, human errors, modeling skills, and derates were found to still cause significant errors in the estimates.
Blind photovoltaic modeling intercomparison: A multidimensional data analysis and lessons learned
The Photovoltaic (PV) Performance Modeling Collaborative (PVPMC) organized a blind PV performance modeling intercomparison to allow PV modelers to blindly test their models and modeling ability against real system data. Measured weather and irradiance data were provided along with detailed descriptions of PV systems from two locations (Albuquerque, New Mexico, USA, and Roskilde, Denmark). Participants were asked to simulate the plane-of-array irradiance, module temperature, and DC power output from six systems and submit their results to Sandia for processing. The results showed overall median mean bias (i.e., the average error per participant) of 0.6% in annual irradiation and −3.3% in annual energy yield. While most PV performance modeling results seem to exhibit higher precision and accuracy as compared to an earlier blind PV modeling study in 2010, human errors, modeling skills, and derates were found to still cause significant errors in the estimates.
Blind photovoltaic modeling intercomparison: A multidimensional data analysis and lessons learned
Theristis, Marios (Autor:in) / Riedel‐Lyngskær, Nicholas (Autor:in) / Stein, Joshua S. (Autor:in) / Deville, Lelia (Autor:in) / Micheli, Leonardo (Autor:in) / Driesse, Anton (Autor:in) / Hobbs, William B. (Autor:in) / Ovaitt, Silvana (Autor:in) / Daxini, Rajiv (Autor:in) / Barrie, David (Autor:in)
01.01.2023
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
DDC:
690
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