Multi-Rotor Wind Turbine Control via Central MPC
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Solution Overview
Problem
Multi-rotor wind turbine systems face challenges in optimizing power production due to differences in operational conditions and coupling between wind turbine modules, as existing control strategies often treat each module individually without accounting for these factors.
Innovation Solution
A control system comprising local controllers to achieve local control objectives and a central model predictive control (MPC) routine to calculate these objectives, ensuring optimized operation while considering multiple inputs and outputs, thereby addressing instability issues related to the natural tower frequencies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If each wind turbine module is controlled individually to optimize local performance, then local optimization is improved, but coupling effects between modules and differences in operational conditions are not accounted for
Solution Approach 1:
The control system is segmented into a central controller that calculates local control objectives using MPC, and local controllers that execute these objectives at each wind turbine module. This segmentation allows the central controller to consider system-wide coupling effects while local controllers optimize individual module performance, resolving the contradiction between local optimization and system-wide adaptability.
Solution Approach 2:
The central controller acts as an intermediary between the overall system state and individual module controllers. It receives system-wide operational data, calculates appropriate local control objectives using MPC that accounts for coupling effects, and transmits these objectives to local controllers, thereby enabling both local optimization and system-wide adaptability.
2Stability of the object's composition
If model predictive control (MPC) is used to calculate local control objectives, then system stability is improved by avoiding limitations from natural tower frequencies, but control system complexity increases
Solution Approach 1:
The patent replaces traditional mechanical control approaches with model predictive control (MPC), a computational control method. Instead of relying on mechanical system characteristics and natural frequencies, MPC uses mathematical models and optimization algorithms to calculate control objectives, thereby improving stability without being constrained by mechanical limitations while accepting increased computational complexity.
3Productivity
If a central controller uses MIMO control routine to calculate local control objectives, then overall system performance is optimized considering multiple inputs and outputs, but control algorithm complexity increases
Solution Approach 1:
The central controller implements a universal MIMO (Multiple Inputs, Multiple Outputs) control routine that can handle multiple operational parameters and control objectives simultaneously. This multi-functional approach allows the controller to optimize overall system performance by considering various inputs (wind conditions, module states, coupling effects) and outputs (power production, stability, efficiency) within a single control framework, accepting increased algorithmic complexity for comprehensive optimization.
Data Source
AI summary
The present invention relates to control of a wind turbine system comprising a plurality of wind turbine modules mounted to a common support structure, i.e. to control of a multi-rotor wind turbine system. The invention discloses a control system for a multi-rotor wind turbine system which comprises local controllers operable to control the wind turbine modules in accordance with local control objectives and a central controller configured to monitor the operation of the wind turbine system and based thereon calculate the local control objectives. The central controller is implemented as a model predictive controller (MPC).