LAPSE:2023.30024v1
Published Article
LAPSE:2023.30024v1
Adaptive Extremum Seeking Control of Urban Area Wind Turbines
Felix Dietrich, Steffen Borchers-Tigasson, Till Naumann, Horst Schulte
April 14, 2023
Abstract
Maximum-power point tracking of wind turbines is a challenging issue considering fast changing wind conditions of urban areas. For this purpose, an adaptive control approach that is fast and robust is required. Conventional approaches based on simple step perturbations and subsequent observation, however, are difficult to design and too slow for the demanding wind conditions of urban areas including gusts and turbulence. In this paper, an extremum seeking control scheme to the recently developed wind turbine MOWEA (Modulare Windenergieanlagen GmbH) is proposed and successfully applied. To this end, a comprehensive aero-electromechanical model of the wind turbine under study including basic control is formulated. Next, the extremum seeking control scheme is adapted to the system. Several aspects to increase adaptation speed are highlighted, including a novel phase compensation. Finally, a validation of the proposed approach is performed considering real wind data, thus demonstrating its fast and robust adaptability. The proposed control scheme is computationally efficient and can be easily implemented on the existing onboard electronics.
Keywords
adaptive control, control of renewable energy resources, extremum seeking control
Suggested Citation
Dietrich F, Borchers-Tigasson S, Naumann T, Schulte H. Adaptive Extremum Seeking Control of Urban Area Wind Turbines. (2023). LAPSE:2023.30024v1
Author Affiliations
Dietrich F: Automation and Intelligent Systems Group/Control Engineering Group, Faculty 1: School of Engineering—Energy and Information, University of Applied Sciences (HTW) Berlin, 12459 Berlin, Germany
Borchers-Tigasson S: Automation and Intelligent Systems Group/Control Engineering Group, Faculty 1: School of Engineering—Energy and Information, University of Applied Sciences (HTW) Berlin, 12459 Berlin, Germany
Naumann T: MOWEA—Modulare Windenergieanlagen GmbH, Storkower Str. 115A, 10407 Berlin, Germany
Schulte H: Automation and Intelligent Systems Group/Control Engineering Group, Faculty 1: School of Engineering—Energy and Information, University of Applied Sciences (HTW) Berlin, 12459 Berlin, Germany
Journal Name
Energies
Volume
14
Issue
5
First Page
1356
Year
2021
Publication Date
2021-03-02
ISSN
1996-1073
Version Comments
Original Submission
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PII: en14051356, Publication Type: Journal Article
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LAPSE:2023.30024v1
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https://doi.org/10.3390/en14051356
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