Analytical Improvements in PV Degradation Rate Determination

PDF Version Also Available for Download.

Description

As photovoltaic (PV) penetration of the power grid increases, it becomes vital to know how decreased power output may affect cost over time. In order to predict power delivery, the decline or degradation rates must be determined accurately. For non-spectrally corrected data several complete seasonal cycles (typically 3-5 years) are required to obtain reasonably accurate degradation rates. In a rapidly evolving industry such a time span is often unacceptable and the need exists to determine degradation rates accurately in a shorter period of time. Occurrence of outliers and data shifts are two examples of analytical problems leading to greater uncertainty ... continued below

Physical Description

9 p.

Creation Information

Jordan, D. C. & Kurtz, S. R. February 1, 2011.

Context

This article is part of the collection entitled: Office of Scientific & Technical Information Technical Reports and was provided by UNT Libraries Government Documents Department to Digital Library, a digital repository hosted by the UNT Libraries. More information about this article can be viewed below.

Who

People and organizations associated with either the creation of this article or its content.

Publisher

Provided By

UNT Libraries Government Documents Department

Serving as both a federal and a state depository library, the UNT Libraries Government Documents Department maintains millions of items in a variety of formats. The department is a member of the FDLP Content Partnerships Program and an Affiliated Archive of the National Archives.

Contact Us

What

Descriptive information to help identify this article. Follow the links below to find similar items on the Digital Library.

Description

As photovoltaic (PV) penetration of the power grid increases, it becomes vital to know how decreased power output may affect cost over time. In order to predict power delivery, the decline or degradation rates must be determined accurately. For non-spectrally corrected data several complete seasonal cycles (typically 3-5 years) are required to obtain reasonably accurate degradation rates. In a rapidly evolving industry such a time span is often unacceptable and the need exists to determine degradation rates accurately in a shorter period of time. Occurrence of outliers and data shifts are two examples of analytical problems leading to greater uncertainty and therefore to longer observation times. In this paper we compare three methodologies of data analysis for robustness in the presence of outliers, data shifts and shorter measurement time periods.

Physical Description

9 p.

Source

  • 35th IEEE Photovoltaic Specialists Conference (PVSC '10), 20-25 June 2010, Honolulu, Hawaii

Language

Item Type

Identifier

Unique identifying numbers for this article in the Digital Library or other systems.

  • Report No.: NREL/CP-5200-47596
  • Grant Number: AC36-08GO28308
  • Office of Scientific & Technical Information Report Number: 1007345
  • Archival Resource Key: ark:/67531/metadc835590

Collections

This article is part of the following collection of related materials.

Office of Scientific & Technical Information Technical Reports

What responsibilities do I have when using this article?

When

Dates and time periods associated with this article.

Creation Date

  • February 1, 2011

Added to The UNT Digital Library

  • May 19, 2016, 3:16 p.m.

Description Last Updated

  • April 6, 2017, 3:25 p.m.

Usage Statistics

When was this article last used?

Yesterday: 0
Past 30 days: 0
Total Uses: 7

Interact With This Article

Here are some suggestions for what to do next.

Start Reading

PDF Version Also Available for Download.

Citations, Rights, Re-Use

Jordan, D. C. & Kurtz, S. R. Analytical Improvements in PV Degradation Rate Determination, article, February 1, 2011; Golden, Colorado. (digital.library.unt.edu/ark:/67531/metadc835590/: accessed August 19, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.