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.

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In the framework of the H2020 SERENDI‐PV project, it is aspired to tackle challenges in photovoltaic (PV) modeling and yield simulations, that are emerging today, on four interrelated aspects: i) improved modeling of loss/degradation mechanisms, ii) improved modeling of bifacial PV, floating PV, and building integrated photovoltaics systems, iii) solar resource and uncertainties modeling, and iv) financial risks modeling. As groundwork for this effort, a comprehensive 8‐month study is carried out, the results of which are presented in this article. The study has two parts and main objectives: i) a comprehensive survey addressed to multiple stakeholders, to identify and assess today's “best practices” and needs of the PV industry on PV energy yield simulations; ii) a multi‐model multi‐case benchmarking and evaluation study, i.e., of eight state‐of‐the‐art tools/software for PV energy yield simulations of seven real‐life PV systems addressing diverse “scenarios” (different climates, site characteristics, PV typologies, and technologies).

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