Solar Panels

Power Optimization for the 4.5 MW Gold Tree Solar Array

Cal Poly’s Gold Tree Solar Array suffers from interrow shading, an issue that can devastate a solar plant’s power output. The array can control panel tilt angles to avoid such shading, but the current control parameters fail to do so properly, and the problem is made worse by highly skewed topography. Since trial-and-error testing on the site itself is unfeasible, we used site measurements and first principles to construct a functioning model of the array and its power output in MATLAB. This continuing work, upon fulfilling its ultimate objectives, will provide a fast and convenient tool to test tracking parameters for eventual power optimization.

GOLD Tree power optimization

This project was a continuation of the work done by previous SURP students to help improve the performance of the Gold Tree Solar Farm. Specifically this year we worked on helping to create a model to predict the power output at any given time based on weather conditions.

Optimization of Backtracking Parameters in the Cal Poly Goldtree Solar Farm

The 4.5 MW Cal Poly Goldtree Solar Farm is the largest solar array in the CSU system. It generates up to 25% of the university’s yearly power. However, it currently faces an issue of shading. During some mornings and evenings, solar panels will cast shade on other panels which will decimate the performance of any module that is shaded. Backtracking is a technique that combats this by sub-optimally tracking the sun until the sun is high enough in the sky so that no shade will be cast on any modules. Due to the uneven terrain of the solar farm, this is a difficult technique to perfect. The goal of this project is to investigate and identify the areas where there is significant power loss due to row-to-row shading, then adjust the current backtracking algorithm such that performance is improved.

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