DOI: https://doi.org/10.15368/theses.2021.171
Available at: https://digitalcommons.calpoly.edu/theses/2585
Date of Award
12-2021
Degree Name
MS in Mechanical Engineering
Department/Program
Mechanical Engineering
College
College of Engineering
Advisor
Jacques Belanger
Advisor Department
Mechanical Engineering
Advisor College
College of Engineering
Abstract
The Gold Tree Solar Farm, designed by REC Solar, has a rated output power of 4.5 MW and began operation in 2018 to provide electricity to Cal Poly’s campus. Gold Tree Solar Farm site terrain consists of rolling hills and uneven slopes. The uneven typography results in interrow shading, requiring a modified tracking control algorithm to maximize power production. Predicting a utility solar field’s lifetime energy yield is a critical step in assessing project feasibility and calculating project revenue. The MATLAB-based predictive power model developed for this field overpredicted power in the middle of the day. The purpose of this thesis was to develop a point-in-time power routine to run through experimental data collected from the Gold Tree Solar Farm and compare different cell temperature and degradation models in an effort to correct this overprediction. Increasing cell temperature reduces power output of a solar panel, and an objective of this analysis was to find a model that accurately predicted cell temperature to calculate this loss. Seven cell temperature models were adjusted to fit the specifications of the Gold Tree Solar Farm and compared to thermocouple measurements from the field. Frequent partial shading, which results in thermal cycling, contributes to accelerated module degradation and power loss. Yearly and seasonal plant degradation rates driven by environmental factors such as temperature, UV radiation, and relative humidity were calculated and integrated into the predictive power model.