Wind Farm Controller Predicting Wind Velocity for Power Stability
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Solution Overview
Problem
Wind turbine generators introduce significant output power fluctuations due to weather conditions, posing challenges for grid voltage and frequency maintenance, particularly when a large number of turbines are connected, as existing solutions like power curve limiting and battery-based systems are costly or inefficient.
Innovation Solution
A controller system for a windfarm that includes anemometers to measure wind direction and speed, local controllers to transmit data, and a central controller to predict wind velocity variations and adjust output power of wind turbine generators through rotation frequency and pitch control, ensuring constant output power by limiting power curves or storing energy as rotation energy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Stability of the object's composition
If power curve limiting is used to suppress output fluctuations, then output power stability is improved, but energy loss increases
Solution Approach 1:
The system performs preliminary action by predicting future wind velocity variations using anemometer data and weather forecasts before they affect turbine output. This allows proactive adjustment of turbine operation to prevent output fluctuations rather than reacting to them, thereby maintaining stability without energy-wasting limitations.
Solution Approach 2:
The system implements feedback by continuously monitoring actual output deviations from the target value and using this information to adjust turbine control commands. The central controller receives operation information from local controllers and computes variation in output power to generate corrective commands, creating a closed-loop control system that maintains stability efficiently.
2Stability of the object's composition
If battery-based systems are used to stabilize output, then output power stability is improved, but system cost increases
Solution Approach 1:
The system applies self-service by utilizing the rotational kinetic energy already present in the turbine blades and rotor as an energy buffer. By controlling rotation frequency, the system can store excess energy when wind is strong and release it when wind is weak, providing stabilization without requiring external battery systems or additional infrastructure.
Solution Approach 2:
The system changes operational parameters by adjusting rotation frequency and pitch angle dynamically based on predicted wind conditions. This allows the turbine to operate at optimal points across a range of conditions, maintaining stable output through parameter optimization rather than through costly energy storage or curtailment mechanisms.
3Stability of the object's composition
If pitch control and rotation frequency control are used to suppress fluctuations, then output power stability is improved, but control complexity increases
Solution Approach 1:
The control system is segmented into hierarchical levels: a central controller that performs high-level prediction and coordination, and local controllers at each turbine that execute specific control commands. This segmentation distributes computational complexity while maintaining centralized optimization, making the overall system manageable despite its sophisticated control requirements.
Solution Approach 2:
The communication network acts as an intermediary between the central controller and local controllers, enabling coordinated control without requiring direct complex interactions between all system components. This intermediary layer simplifies the control architecture by standardizing information exchange and command transmission across the wind farm.
Data Source
AI summary
In a controller for a windfarm including a plurality of wind turbine generators controllable in rotation frequency and pith of blades of the wind turbine generators, coupled to a grid through a transmission line, an anemometer is provided to each wind turbine generator to transmits wind direction and wind speed data to a central controller which process the wind direction and wind speed data to transmit an output command each wind turbine generator. The central controller predicts, on the basis of the wind speed detected by the upstream wind turbine generator, variation in wind speed at other wind turbine generators to control the output of the windfarm. The output power may be limited or charging energy as rotation energy of blades and discharging the rotation energy as output power in addition to a battery unit for averaging.