SAT-136 Analysis of Metrics and Performance Assessment of Photovoltaic Systems

Saturday, October 13, 2012: 4:40 PM
Hall 4E/F (WSCC)
Uriel Rosas , Mechanical and Aerospace Engineering, San Jose State University, San Jose, CA
James Mokri , Mechanical and Aerospace Engineering, San Jose State University, San Jose, CA
Harikrishna Patadiya , Mechanical and Aerospace Engineering, San Jose State University, San Jose, CA
Mark Lahlouh , Mechanical and Aerospace Engineering, San Jose State University, San Jose, CA
Quochuy Le , Mechanical and Aerospace Engineering, San Jose State University, San Jose, CA
David Twining , Electrical Engineering, San Jose State University, San Jose, CA
Owners of existing photovoltaic (PV) solar energy systems are typically interested in the system short-term and long-term performance as input to operation and maintenance decisions. Performance metrics and methods to calculate the metrics are used by the industry for various purposes and it is difficult for the owner to know which metric is appropriate for which purpose. Defined methods would enable quick identification of actual performance that deviated from expected performance. In general, performance assessment is the process of measuring or monitoring actual performance and comparing to expected performance. The purpose of this presentation is to report our efforts in improving the energy generation performance of existing PV systems. Operating data is used to calculate expected performance using actual weather and AC power output. Data for the use of this project is obtained from three systems having DC ratings of 191 kW, 400 kW, and 500 kW. Data is gathered by direct power measurements, on-line live site, and access to monitoring system and weather data, respectively. We have two primary expectations for our performance assessments of existing systems 1. Monitoring of a specific PV system to identify degraded performance and need for maintenance based on condition, and 2. Outline effective assessment metrics and associated calculation methods considering factors such as level-of-effort to perform the assessment and the value of the assessment. We are also pursuing to improve a PV array performance model using regression analysis and automating the process.