PERFORMANCE LOSS RATE ANALYSIS OF 1100 PHOTOVOLTAIC POWER PLANTS

PERFORMANCE LOSS RATE ANALYSIS OF 1100 PHOTOVOLTAIC POWER PLANTS

Bibliographic Details
Main Author: Xin, Arthur S.
Language:English
Published: Case Western Reserve University School of Graduate Studies / OhioLINK 2020
Subjects:
Computer Science
Performance Loss Rate
PLR
PV Power Plants
Photovoltaics
Online Access:http://rave.ohiolink.edu/etdc/view?acc_num=case1592483422090231
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spelling ndltd-OhioLink-oai-etd.ohiolink.edu-case15924834220902312021-08-03T07:15:21Z PERFORMANCE LOSS RATE ANALYSIS OF 1100 PHOTOVOLTAIC POWER PLANTS Xin, Arthur S. Computer Science Performance Loss Rate PLR PV Power Plants Photovoltaics Linear Performance Loss Rate (PLR) has been widely used in the photovoltaic (PV) community as a tool for modeling the degradation of PV modules over time. In the real-world commercial deployment of solar power, PV modules are manufactured by different companies to varying degrees of quality, deployed in a wide variety of locations, and undergo system damage and degradation. Since factors such as these will affect the performance of PV modules in different ways after data is already recorded, a linear model would not be fully able to effectively capture their lifetime performances. Many tools and models have been developed for specific lab tested PV systems, but have failed to generalize to large quantities of commercial powerplants. In this work, we introduce a new solar power plant analysis tool that uses a non-linear PLR method that better models the degradation of PV modules over their lifetime, and we will be testing our model on a population of 1100 commercial PV systems that have been operating for up to 6 years. In this dataset, the median adjusted R2 value of the Linear PLR method is 0.03, while the median adjusted R2 of a Segmented method is increased at 0.21. Decomposition by season can further increase the performance of both linear and segmented methods to median adjusted R2 values of 0.19 and 0.28, respectively. Comparing the metadata factors to the calculated PLR values can lead to insights regarding which factors contribute to the greatest change in PLR and degradation of PV systems. 2020-09-07 English text Case Western Reserve University School of Graduate Studies / OhioLINK http://rave.ohiolink.edu/etdc/view?acc_num=case1592483422090231 http://rave.ohiolink.edu/etdc/view?acc_num=case1592483422090231 unrestricted This thesis or dissertation is protected by copyright: all rights reserved. It may not be copied or redistributed beyond the terms of applicable copyright laws.
collection NDLTD
language English
sources NDLTD
topic Computer Science
Performance Loss Rate
PLR
PV Power Plants
Photovoltaics
spellingShingle Computer Science
Performance Loss Rate
PLR
PV Power Plants
Photovoltaics
Xin, Arthur S.
PERFORMANCE LOSS RATE ANALYSIS OF 1100 PHOTOVOLTAIC POWER PLANTS
author Xin, Arthur S.
author_facet Xin, Arthur S.
author_sort Xin, Arthur S.
title PERFORMANCE LOSS RATE ANALYSIS OF 1100 PHOTOVOLTAIC POWER PLANTS
title_short PERFORMANCE LOSS RATE ANALYSIS OF 1100 PHOTOVOLTAIC POWER PLANTS
title_full PERFORMANCE LOSS RATE ANALYSIS OF 1100 PHOTOVOLTAIC POWER PLANTS
title_fullStr PERFORMANCE LOSS RATE ANALYSIS OF 1100 PHOTOVOLTAIC POWER PLANTS
title_full_unstemmed PERFORMANCE LOSS RATE ANALYSIS OF 1100 PHOTOVOLTAIC POWER PLANTS
title_sort performance loss rate analysis of 1100 photovoltaic power plants
publisher Case Western Reserve University School of Graduate Studies / OhioLINK
publishDate 2020
url http://rave.ohiolink.edu/etdc/view?acc_num=case1592483422090231
work_keys_str_mv AT xinarthurs performancelossrateanalysisof1100photovoltaicpowerplants
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