twoaxistracking - a python package for simulating self-shading of two-axis tracking solar collectors.

Area of Science:

• Renewable Energy Systems
• Solar Energy Engineering
• Computational Modeling

Background:

• Self-shading in two-axis tracking solar collector fields can reduce annual incident irradiation by 1% to 6%.
• Accurate estimation of shading losses is critical for reliable solar project yield predictions and financial viability.
• Existing methods for simulating shading may lack flexibility in handling complex field configurations.

Purpose of the Study:

• To introduce a free and open-source Python package, `twoaxistracking`, for simulating self-shading in two-axis tracking solar collector fields.
• To provide a robust and efficient method for calculating shading losses, improving the accuracy of energy yield estimates.
• To offer a tool that addresses limitations of previous shading calculation methods in solar energy modeling.

Main Methods:

• Development of a Python package implementing a novel mathematical formulation for self-shading calculation.
• The method accounts for arbitrary collector aperture geometries and distinguishes between total and active areas.
• Incorporation of features to handle sloped ground, varying collector heights, and optimized computation by skipping high solar elevation angles.

Main Results:

• The `twoaxistracking` package enables precise simulation of self-shading in diverse two-axis tracking solar collector configurations.
• The implemented method offers significant improvements over prior approaches by handling complex geometries and terrain.
• Computational efficiency is enhanced through optimized calculation strategies, reducing simulation time.

Conclusions:

• The `twoaxistracking` Python package provides an accurate and efficient solution for simulating self-shading in solar energy systems.
• Accurate shading analysis using this tool can lead to more reliable energy yield predictions and better financial planning for solar projects.
• The package's flexibility and performance make it a valuable resource for researchers and engineers in the solar energy field.