Solar Energy Generation Forecasting and Power Output Optimization of Utility Scale Solar Field

<p>The optimization of photovoltaic (PV) power generation system requires an accurate system performance model capable of validating the PV system optimization design. Currently, many commercial PV system modeling programs are available, but those programs are not able to model PV systems on a distorted ground level. Furthermore, they were not designed to optimize PV systems that are already installed. To solve these types of problems, this thesis proposes an optimization method using model simulations and a MATLAB-based PV system performance model. The optimization method is particularly designed to address partial shading issues often encountered in PV system installed on distorted ground. The MATLAB-based model was validated using the data collected from the Cal Poly Gold Tree Solar Field. It was able to predict the system performance with 96.4 to 99.6 percent accuracy. The optimization method utilizes the backtracking algorithm already installed in the system and the pitch distance to control the angle of the tracker and reduces solar panels partial shading on the adjacent row to improve system output. With pitch distances reduced in the backtracking algorithm between 2.5 meters and 3 meters, the inverter with inter-row shading can expect a 10.4 percent to 28.9 percent increase in power production. The implementation and calibration of this optimization method in the field this spring was delayed due to COVID-19. The field implementation is now expected to start this summer.</p>

Name thesis:degree_name

MS in Mechanical Engineering

Discipline thesis:degree_discipline

Mechanical Engineering

Year dc:date.available

2020

Author dc:creator

• Kim, Byungyu

Contributors dc:contributor

• Jacques Belanger
• Mechanical Engineering
• College of Engineering

• Solar Energy
• Optimization
• Backtracking

Identifier

10.15368/theses.2020.55

OAI identifier oai:identifier

oai:digitalcommons.calpoly.edu:theses-3648