Multi-Rotor Wind Turbine MPC Control Under Module Constraints
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Solution Overview
Problem
Multi-rotor wind turbine systems face challenges in controlling multiple rotors in a robust and simple manner, particularly in ensuring optimized performance and structural integrity across different support structure constructions.
Innovation Solution
A control system for a multi-rotor wind turbine system that employs local model predictive control (MPC) routines for each wind turbine module, coordinated by a central controller. This system allows for optimized operation of individual modules based on current operational states and operational constraints, ensuring safe and efficient operation regardless of the type of wind turbine system or support structure design.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a multi-rotor wind turbine system uses local controllers for each wind turbine module, then the control system can optimize individual module performance, but the complexity of coordinating multiple controllers increases
Solution Approach 1:
The control system is segmented into independent local controllers for each wind turbine module, where each controller autonomously optimizes its module's performance using local measurements and a cost function. This segmentation allows parallel operation of multiple controllers without requiring complex inter-coordination, resolving the contradiction by enabling individual optimization while maintaining control simplicity through modular independence.
2Adaptability or versatility
If the local controller is designed to work with different support structure constructions, then the adaptability of the control system increases, but the complexity of ensuring robust operation across variations increases
Solution Approach 1:
The local controller is designed as a universal control solution that can be applied to any wind turbine module regardless of the specific support structure construction. The controller achieves this universality by relying solely on local measurements from its own module and using a cost function that adapts to different configurations without requiring knowledge of the overall system architecture, thereby enabling broad adaptability while maintaining simple, robust operation.
3Manufacturing precision
If the MPC routine uses current operational state for optimization, then the control precision improves, but the computational requirements increase
Solution Approach 1:
The MPC routine uses only local operational state measurements from the individual wind turbine module to compute the cost function and determine optimal control actions. This local quality approach allows the controller to achieve precise optimization for its specific module without requiring system-wide state information, thereby improving control precision while minimizing computational energy consumption by processing only locally available data.
Data Source
AI summary
Control of a multi-rotor wind turbine system. A local controller is arranged for each wind turbine module and implementing a local model predictive control (MPC) routine. A central controller is arranged to determine a set of operational constraints of the wind turbine modules. Based on a current operational state of the wind turbine module and the set of operational constraints, one or more predicted operational trajectories are calculated and used for controlling the wind turbine module.


