System Modeling and Performance Database Development

Maintaining awareness of the current status of photovoltaic system performance is a critical element in monitoring, communicating and validating program progress, especially in supporting the goals of the Solar America Initiative. This effort requires an ongoing collection and analysis of field data from state-of-the-art photovoltaic (PV) systems as well the assessment of current modeling capabilities to predict future performance of these systems. This paper examines benchmarked field data from a grid-tied residential system and existing models to assess the input parameter requirements, computation architecture, and output results associated with the models ’ features. In addition to illustrating the path from benchmarking to supplying information for direct program support and modeling, several lessons learned regarding the application of models has been documented. 1. Objectives The objective of this work is to support the continuing development of a suite of analysis, modeling, and benchmarking tools that are needed for the program’s planning, technology evaluation, and decision-making. This includes field data collection to populate an accessible database of component and system cost, performance and reliability data to interface with complementary model algorithm development work. 2. Technical Approach To collect and populate a database of actual field performance with PV systems requires access to qualified data. A Sandia/DOE partnership with Arizona Public Service (APS) provides access to field performance data from a grid-tied residential system in the APS service territory. A separate paper/poster (Field Experience of Tucson Electric Power) and reference [1] provides documentation for utility and commercial applications as well. A representative sample of existing system performance models were examined in the context of this system to assess ease of use, input requirements, computational methods and features, and output results. The residential system for this work was installed by APS at the Challenger Learning Center in Peoria, AZ [1]. APS monitors the system performance and provided data for this work