NDLI: Real-world challenges and opportunities in degradation rate analysis for commercial PV systems

Content Provider	IEEE Xplore Digital Library
Author	Sauer, K.J.
Copyright Year	2011
Description	Author affiliation: Yingli Americas, San Francisco, CA, USA (Sauer, K.J.)
Abstract	Determining accurate annual system degradation rates from historical meteorological and production data is essential for improving the overall financial viability of photovoltaic (PV) systems. Such efforts can be quite challenging, however, as nearly every step in degradation analysis has the potential to contribute error to the resultant rates. The presence of scatter and "evental" noise (e.g., due to snow and inverter downtime events) in non-laboratory-grade data sets collected from commercial PV systems makes degradation analytics all the more challenging. A MATLAB® tool has been developed as part of an ongoing investigation into the sensitivities of annual system degradation rates to data qualification and filtration. In this study, a two year set of continuous meteorological and production data affected by each of the abovementioned issues is analyzed using this tool. An interpolative inverter efficiency function is used to convert AC to DC power. A PVUSA-related multiple regression-based power model employing module temperature data is used to derive time series data sets of DC power values normalized to an arbitrary set of conditions. A limited number of qualification and filtration configurations are simulated, including an experimental method. Linear least-squares fit and classical decomposition are used to extract degradation trends from the normalized DC power time series data sets derived for each simulated configuration. Preliminary results show how both the presence of irregular scatter and evental noise in continuous, raw data sets, as well as the type of qualification and filtration criteria employed, can influence the outputs of degradation analyses. Removal of this noisy data, however, can unfortunately result in missing weeks or, in extreme cases, months of data, thus compromising the ability to employ more advanced time series algorithms (e.g., classical decomposition) to normalized power time series data sets to yield degradation trends extracted from their seasonality and error counterparts. A tested experimental method sought to address the issue of missing data, but the method and results remain preliminary and premature. The chosen system will be continuously investigated to see if and how additional input data affects the resultant degradation rates, as well as any preliminary observations made herein on the sensitivity of those rates to data qualification and filtration.
Starting Page	003208
Ending Page	003212
File Size	934878
Page Count	5
File Format	PDF
ISBN	9781424499663
ISSN	01608371
e-ISBN	9781424499656
DOI	10.1109/PVSC.2011.6186622
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-06-19
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Inverters Time series analysis Data models Qualifications Degradation Filtration Snow
Content Type	Text
Resource Type	Article
Subject	Industrial and Manufacturing Engineering Control and Systems Engineering Electrical and Electronic Engineering

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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