Self-tuning WEC controller for changing sea states
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Solution Overview
Problem
Current wave energy converter (WEC) control systems face challenges in efficiently capturing electrical power in changing sea-states due to the difficulty in implementing accurate real-time wave prediction and state-estimation procedures, especially in short-crested wave fields where plane-wave approximations are inadequate.
Innovation Solution
A self-tuning control law that adjusts motor torques of a three degree-of-freedom wave energy converter using a frequency-domain estimate of the current sea-state, relying on an identified model of device intrinsic impedance to maximize electrical power capture, allowing for adaptation to changing sea-states and device impedance over time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If accurate real-time wave prediction and state-estimation procedures are used, then power capture optimization is improved, but device complexity and computational requirements increase significantly
Solution Approach 1:
The controller automatically identifies device impedance characteristics and tunes its own control parameters without external intervention. The system performs self-diagnosis and self-optimization by monitoring its own response to wave inputs and adjusting control gains accordingly, eliminating the need for complex external tuning mechanisms
Solution Approach 2:
The system continuously monitors WEC platform motion, motor energy output, and sea state conditions, then uses this feedback to dynamically adjust control parameters. The controller compares actual performance with target performance and modifies control actions in real-time to optimize power capture while adapting to changing conditions
2Productivity
If prediction-based control strategies are implemented, then power capture is improved, but reliability decreases due to difficulties in short-crested wave fields
Solution Approach 1:
The control system transitions from static pre-defined control parameters to dynamic adaptive parameters that continuously evolve with changing sea states. The controller adjusts its characteristics in real-time based on current wave conditions and device response, maintaining optimal performance across varying operational environments
Solution Approach 2:
The system modifies control parameters such as controller gains and torque commands based on identified device impedance and observed sea state conditions. By changing control parameters dynamically rather than using fixed values, the system adapts to different wave conditions and maintains reliable power capture across diverse operational scenarios
3Measurement precision
If accurate device impedance modeling is performed, then control precision is improved, but measurement and computational requirements increase
Solution Approach 1:
The system performs preliminary identification of device impedance characteristics during initial operation or calm sea states before transitioning to active power capture mode. This preliminary characterization establishes baseline parameters that are then refined through continuous adaptation, reducing the measurement burden during high-power operation
Solution Approach 2:
The system replaces complex direct measurement methods with computational estimation techniques. By using mathematical models and observed system responses to infer impedance characteristics, the system achieves accurate impedance knowledge without requiring complex physical measurement apparatus or intrusive sensing
Data Source
AI summary
Systems and methods for a WEC controller that uses a self-tuning proportional-integral control law prescribing motor torques to maximize electrical power generation and automatically tune the controller to maximize power absorption. In an embodiment, the controller may be part of any resonant WEC system. The control law relies upon an identified model of device intrinsic impedance to generate a frequency-domain estimate of the wave-induced excitation force and measurements of device velocities. The control law was tested in irregular sea-states that evolved over hours (a rapid, but realistic time-scale) and that changed instantly (an unrealistic scenario to evaluate controller response).