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Exploration of Sensor Systems for Increasing the Accuracy of Photovoltaic Modeling Application to the TEP/AZRISE Solar Test Yard
Author
Dzurick, MatthewIssue Date
2018Advisor
Simmons-Potter, Kelly
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The University of Arizona.Rights
Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction, presentation (such as public display or performance) of protected items is prohibited except with permission of the author.Abstract
The TEP/AzRISE (Tucson Electric Power/Arizona Research Institute for Solar Energy) solar test yard is a test-bed for multiple installations of various grid-tied photovoltaic (PV) modules and associated data collection systems that is located on the TEP campus in Tucson, AZ. Modules installed at the test yard are instrumented and data related to module/string power production and local field conditions are continuously collected. Additional data acquisition has been implemented via SOFIE (Smart Solar Field) which is a movable unit that has been recently serving as a primary data acquisition system at the TEP/AzRISE solar test yard. SOFIE has the capability to measure DNI (Direct Normal Irradiance), DHI (Diffuse Horizontal Irradiance), GHI (Global Horizontal Irradiance), POA (Plane of Array) Irradiance, wind velocity, wind direction, ambient temperature, and back of panel temperature. The measurement capabilities of SOFIE greatly enhance the sheer volume of data that is collected at the TEP/AzRISE solar test yard and serves to complement and confirm data acquisition systems that are already in place. In this thesis, experimental and modeling efforts to determine the impact of field-condition data fidelity and accelerated-aging test data availability on the accuracy of predictive PV power generation models will be examined. As such, a number of topics will be discussed and explored. These include the deployment of both SOFIE and an additional solar panel string at the test yard, the update of the test yard data acquisition system which now automatically transports data to the University of Arizona UAPV servers, thus greatly improving data accessibility, and modeling methods for PV power prediction. Additionally, the impact of test yard and laboratory data on the accuracy of PV power forecasting models will be examined and discussed. Finally, overarching conclusions and work remaining for future investigation will be presented.Type
textElectronic Thesis
Degree Name
M.S.Degree Level
mastersDegree Program
Graduate CollegeElectrical & Computer Engineering