Control & Software

Distribution of the electricity grid of a tiny house community

Bachelor thesis (2021)

Authors

P.E.M. Van Santvliet Electrical Engineering, Mathematics and Computer Science
A.M. Rozendaal Electrical Engineering, Mathematics and Computer Science

Contributors

P.P. Vergara Barrios Intelligent Electrical Power Grids - EEMCS (supervisor 1)
Faculty
Electrical Engineering, Mathematics and Computer Science
Copyright: © 2021 Pieter Van Santvliet, Aart Rozendaal
Control Software Artificial neural networks Model predictive control Microgrids Tiny house Community
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Published Date

30-06-2021

Language

English

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Faculty

Electrical Engineering, Mathematics and Computer Science

Abstract

This thesis shows the detailed design of the control and software of a DC microgrid of a tiny house community on the roof of a high-rise building in the city of Rotterdam in the Netherlands, consisting of twelve tiny houses powered by solar and wind energy. This thesis is part of a project with two other subgroups, focusing on the microgrid design and the powerline communication.

First, an introduction to the problem is given together with a description of the tiny house community. After that, the general program of requirements is presented, as well as the requirements of this subgroup. Next, an artificial neural network design is presented, which is used to forecast solar and wind generation and energy demand. The designed dense neural network resulted in predictions with mean errors of 10.11%, 12.56%, and 6.95% as a fraction of the maximum value for solar generation, wind generation, and energy demand, respectively. The predictions functioned as an input for the model predictive controller, which used them to place restrictions on appliances in the community when necessary, to reduce dependency on the main power grid of Rotterdam. Using a mathematical optimization algorithm, a simulation of one year showed that the controller could reduce the grid dependency up to 25%, compared to simulating without the controller. The conclusion summarises the achieved results, discusses whether the requirements are met, and considers possible future works.