| Description |
1 online resource ([9] p.) : col. ill. |
| Series |
NREL/CP ; 5200-53712 |
|
Conference paper (National Renewable Energy Laboratory (U.S.)) ; 5200-53712
|
| System Details |
Full text available via Internet in .pdf format. Adobe Acrobat Reader required. |
| Note |
Title from PDF title screen (viewed Aug. 27, 2012). |
|
"April 2012." |
|
"To be presented at the 2012 World Renewable Energy Forum Denver, Colorado May 13-17, 2012." |
| Bibliography |
Includes bibliographical references (p. 6). |
| Summary |
The ability to accurately predict power delivery over the course of time is of vital importance to the growth of the photovoltaic (PV) industry. Important cost drivers include the efficiency with which sunlight is converted into power, how this relationship changes over time, and the uncertainty in this prediction. An accurate quantification of power decline over time, also known as degradation rate, is essential to all stakeholders - utility companies, integrators, investors, and researchers alike. In this paper we use a statistical approach based on historical data to quantify degradation rates, discern trends and quantify risks related to measurement uncertainties, number of measurements and methodologies. |
| Funding |
DE-AC36-08GO28308 |
| Subject |
Photovoltaic power systems.
|
|
Photovoltaic power generation.
|
|
Electric power-plants -- Efficiency.
|
| Added Author |
Kurtz, S. R.
|
|
National Renewable Energy Laboratory (U.S.)
|
|
World Renewable Energy Forum (2012 : Denver, Colo.)
|
| Gpo Item No. |
0430-P-04 (online) |
| Sudoc No. |
E 9.17:NREL/CP-5200-53712 |
|
