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Multi-Objective Wind Farm Controller Optimization with Combined Thrust and Yaw Control using Koopman Model Predictive Control

Dittmer, Antje and Sharan, Bindu and Werner, Herbert (2023) Multi-Objective Wind Farm Controller Optimization with Combined Thrust and Yaw Control using Koopman Model Predictive Control. Wind Energy Science Conference, 2023-05-23 - 2023-05-26, Glasgow, Schottland.

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Abstract

A novel approach to wind farm control, leveraging the Koopman framework for non-linear system identification, is shown to be an efficient way to derive a pareto-optimal farm control algorithm. The objective in both wind turbine and farm control is to minimize the levelized cost of energy (LCoE) via control settings that optimize a combination of power, mechanical loads and actuator criteria subject to actuator constraints, [1,2]. Power criteria are the minimization of the difference to grid power refences and the minimization of the power standard deviation. Load criteria ensure the minimization of mechanical damage equivalent loads on tower and blades. Including actuator criteria, i.e. penalizing actuator outputs and rates, ensures that the wear on the actuators is minimized. There are three actuators available per turbine: With the turbine yaw, the angle between turbine rotor and wind direction is set, typically setting the turbine rotor perpendicular to the main wind direction. For thrust control, the generator torque is used to maximize the power yield at below rated wind and the blade pitch for keeping the power constant at above rated wind and to ensure structural integrity. Two approaches to collaborative farm control are axial induction control (AIC) and wake redirection control (WRC): In AIC, the generator torque and blade pitch angles are varied from individual optimal setting to change the axial induction or thrust coefficient. In WRC, the wake of upstream wind turbines is redirected away from downstream wind turbines, often via yawing the upstream turbine. Both approaches have shown to yield promising results. However, there are relatively few investigations into combining thrust and yaw control for optimal farm yield. The main contributions of the presented work are: The WFSim environment [3] is leveraged to demonstrate the power gain possible with WRC. Physically motivated Koopman lifting functions and dynamic mode decomposition are then shown to be well suited for modelling the dynamics between the two control inputs, yaw and thrust, and the overall farm output. This is an extension of the Koopman models for AIC presented in [4]. The resulting linear model is then shown to provide a good basis for model predictive control using combined AIC and WRC with the goal to minimize the difference between grid reference power while minimizing actuator energy as well as keeping the yaw angle as small as possible, as larger yaw misalignment, while resulting in overall power increase, also increase the mechanical loads on the turbine.

Item URL in elib:https://elib.dlr.de/195581/
Document Type:Conference or Workshop Item (Speech)
Title:Multi-Objective Wind Farm Controller Optimization with Combined Thrust and Yaw Control using Koopman Model Predictive Control
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Dittmer, AntjeUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Sharan, BinduUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Werner, HerbertUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Date:25 May 2023
Refereed publication:No
Open Access:Yes
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Status:Published
Keywords:Wind farm control, Koopman, Axial induction control, Wake redirection control
Event Title:Wind Energy Science Conference
Event Location:Glasgow, Schottland
Event Type:international Conference
Event Start Date:23 May 2023
Event End Date:26 May 2023
HGF - Research field:Energy
HGF - Program:Materials and Technologies for the Energy Transition
HGF - Program Themes:Photovoltaics and Wind Energy
DLR - Research area:Energy
DLR - Program:E SW - Solar and Wind Energy
DLR - Research theme (Project):E - Wind Energy
Location: Braunschweig
Institutes and Institutions:Institute of Flight Systems > Rotorcraft
Institute of Flight Systems
Deposited By: Dittmer, Antje
Deposited On:28 Sep 2023 08:46
Last Modified:24 Apr 2024 20:56

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