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A tuning routine to correct systematic influences in reference PV systems' power outputs
Australian National University.ORCID iD: 0000-0001-8197-5181
Australian National University.ORCID iD: 0000-0002-9465-3453
Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Solid State Physics. (Built Environment Energy Systems Group)ORCID iD: 1-6586-4932
Australian National University.ORCID iD: 0000-0003-3966-3058
2017 (English)In: Solar Energy, ISSN 0038-092X, E-ISSN 1471-1257, Vol. 157C, 1082-1094 p.Article in journal (Refereed) Published
Abstract [en]

Power output measurements from PV systems are subject to a wide variety of systematic external and internal influences, such as shading, soiling, degradation, module and inverter quality issues and other system-level losses. All of these influences upon PV power measurements make the use of PV power output datasets for higher-level analysis problematic, particularly in their use as reference PV systems for estimating the power of a regional portfolio. To address these issues, we present a three-step method. Firstly, a parameterisation and quality control of power measurements is performed, which also corrects for consistent inefficiencies by a loss factor LF. Secondly, the detection of systematic de-ratings affecting PV system power output differently for each time step of the day (predominantly due to shading) together with the implementation of a subsequent “re-rating” of the power output measurements in a process referred to as tuning. The pivotal element of this approach is a 30-day running 90th percentile of the clear-sky index for photovoltaics kpv and the computation of a daily de-rating profile. Lastly, high kpv related variance in the early morning and evening is detected and filtered. Whilst these three methods are independent of each other, we suggest applying them in combination following the same order as in our paper. Cross-validations of these methods demonstrate significant improvements to the PV power measurement profiles, particularly in their use as reference PV systems for upscaling approaches. The RMSE falls from 0.174 to 0.09 W/Wp, rRMSE from 46.5% to 21.9%, MAPE from 47.9% to 20.8% and the correlation r increases from 0.767 to 0.919. Hence, we report overall improvements to RMSE, rRMSE, MAPE and r by 48%, 53%, 57% and 20%, respectively

Place, publisher, year, edition, pages
Elsevier, 2017. Vol. 157C, 1082-1094 p.
Keyword [en]
PV power measurements, Quality Control, PV tuning, Upscaling
National Category
Energy Systems
Research subject
Engineering Science
Identifiers
URN: urn:nbn:se:uu:diva-332234DOI: 10.1016/j.solener.2017.09.001OAI: oai:DiVA.org:uu-332234DiVA: diva2:1152568
Available from: 2017-10-25 Created: 2017-10-25 Last updated: 2017-10-25

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Publisher's full texthttps://doi.org/10.1016/j.solener.2017.09.001

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