Improving the efficiency of renewable energy assets by optimizing the matching of supply and demand using a smart control algorithm

Bachelor thesis (2022)

Authors

P.M. de Bekker Electrical Engineering, Mathematics and Computer Science

Contributors

Valentin Robu Algorithmics - EEMCS (supervisor 1)
S.A. Cremers Electrical Engineering, Mathematics and Computer Science (supervisor 1)
Jérémie Decouchant Data-Intensive Systems - EEMCS (supervisor 2)
Faculty
Electrical Engineering, Mathematics and Computer Science
Copyright: © 2022 Philippe de Bekker
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Published Date

23-06-2022

Language

English

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Faculty

Electrical Engineering, Mathematics and Computer Science

Abstract

Given the fundamental profit gained by renewable energy assets in climate control, existing control algorithms are urged to be improved to match power supply and demand optimally. This paper explores various designed cases that lead toward an enhanced definition of a control algorithm with optimized behaviour. The core of improvement is exploiting future knowledge, which can be realized by current state-of-the-art forecasting techniques, to effectively store and trade energy.
Based on several thousands of simulations of energy communities in the UK, the proposed smart control algorithm has demonstrated a robust performance and gained notable additional profit in theoretical and practical scenarios using probable data.