JMP Applications in Photovoltaic Reliability (Presentation) [electronic resource].
- Washington, D.C. : United States. Dept. of Energy, 2011.
Oak Ridge, Tenn. : Distributed by the Office of Scientific and Technical Information, U.S. Dept. of Energy.
- Physical Description:
- 43 pages : digital, PDF file
- Additional Creators:
- National Renewable Energy Laboratory (U.S.), United States. Department of Energy, and United States. Department of Energy. Office of Scientific and Technical Information
- Restrictions on Access:
- Free-to-read Unrestricted online access
- The ability to accurately predict power delivery over the course of time is of vital importance to the growth of the photovoltaic (PV) industry. Two key cost drivers are the efficiency with which sunlight is converted into power and secondly how this relationship develops over time. The accurate knowledge of power decline over time, also known as degradation rates, is essential and important to all stakeholders?utility companies, integrators, investors, and scientist alike. Outdoor testing plays a vital part in quantifying degradation rates of different technologies in various climates. Due to seasonal changes, however, several complete cycles (typically 3-5 years) need to be completed traditionally 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 more accurately in a shorter period of time. Advanced time series modeling such as ARIMA (Autoregressive Integrated Moving Average) modeling can be utilized to decrease the required time span and is compared with some non-linear modeling. In addition, it will be demonstrated how the JMP 9 map feature was used to reveal important technological trends by climate.
- Report Numbers:
- E 1.99:nrel/pr-5200-51126
- Other Subject(s):
- Published through SciTech Connect.
Presented at the JMP Discovery Summit 2011, 13-16 September 2011, Denver, Colorado.
Jordan, D.; Gotwalt, C.
- Funding Information:
View MARC record | catkey: 14795417