Automatic PV system design using LiDAR data shadow analysis

Master thesis (2017)

Authors

J. Bronkhorst Electrical Engineering, Mathematics and Computer Science

Contributors

O. Isabella (mentor)
Faculty
Electrical Engineering, Mathematics and Computer Science, Electrical Engineering, Mathematics and Computer Science
Copyright: © 2017 Joris Bronkhorst
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Published Date

12-09-2017

Language

English

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Faculty

Electrical Engineering, Mathematics and Computer Science

Abstract

The amount of photovoltaic (PV) systems in the world is growing rapidly. The designing process is however still old fashioned and mostly done by hand. Creating a method to automatically design these PV systems can help to stimulate this growing market even further. In this thesis a research is done
into the development of an automatic PV system design algorithm.

The research consists of two main parts. A section related to panel placement and a section related to the inverter choice. Strategies were developed for both parts and that resulted in several prototype algorithms. These algorithms were tested to see if these algorithms have practical potential. The panel placement algorithms are divided into two categories: maximum panel placement and finite panel placement. Development of these categories was done for both flat and pitched roof sections. The shading caused by surrounding obstacles was taken into account to find the most optimal positions to place the panels. A grading system for the panel layout was developed to ensure that preferred layouts
are found. The shading caused by the surrounding obstacles was also used to determine the type of inverter is that optimal for certain panel configurations.

A proof concept was conducted for the developed algorithms by testing algorithms on real roofs and comparing the results with PV system designs that were made manually. The designs were compared with each other in terms of predicted PV system performance, the layout and the duration of the designing process.

It was demonstrated that the finite panel placement algorithm produced PV systems with an average performance difference of about - 0.83 % with a standard deviation of 5.26 %, compared to the manual designs. The maximum panel placement algorithm took an average of 2.7 minutes with a standard
deviation of 2.1 minutes. The finite panel placement algorithm took on average 3.8 minutes with a standard deviation of 5.5 minutes. Both of which can be considered as being significantly faster than making a manual design.

For a PV system with many panels and several string inverters, algorithms were developed that predict the optimal configuration of the strings. It also predicts the total performance losses that occur when panels are connected in series. These algorithms can help to determine the optimal type of inverter and how to optimally configure separate panel strings in large systems. The algorithms work
based on initial tests, but not enough testing has been done to be conclusive.

The work done in this thesis can be used as a stepping stone for further development of automatic PV systems design algorithms. The panel placement algorithms and the inverter algorithms can be developed further into a complete automatic PV system design algorithm.