Dynamic Wind Turbine Profile Management for Weather Damage Prevention
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current wind farm management systems are inefficient due to manual configuration requirements and inadequate detection of unfavorable weather conditions, leading to potential damage from thunderstorms, microbursts, and icing, as master wind turbines are not optimally placed to assess turbulence and promptly shut down slave turbines.
Innovation Solution
A method and system that dynamically analyze operating parameters, including historical and real-time data, to change the turbine profile of wind turbines from slave to master or vice versa, allowing for automatic configuration and strategic placement of master wind turbines to accurately detect weather conditions and shut down slave turbines during unfavorable weather.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual configuration of master and slave wind turbines is used, then the system can be set up with basic functionality, but the configuration may be incorrect leading to severe damage and requires complete user knowledge of wind farm location
Solution Approach 1:
The system automatically determines the optimal master-slave configuration by analyzing operational parameters and weather data without requiring manual user input. The controller autonomously identifies which turbines should serve as master turbines based on their locations and performance characteristics, eliminating the need for users to have complete knowledge of wind farm geography and reducing configuration errors.
Solution Approach 2:
The master-slave configuration is not fixed but dynamically adjusted based on changing operational conditions. The system continuously monitors weather parameters, turbine performance, and environmental conditions to optimize the assignment of master and slave roles, allowing the configuration to adapt to varying wind patterns, storm conditions, and turbine availability.
2Measurement precision
If master wind turbines are not optimally placed, then the system structure is simpler, but the detection of turbulence and unfavorable weather conditions is inaccurate and delayed
Solution Approach 1:
The system performs preliminary analysis of operational parameters, historical weather data, and turbine locations to pre-determine the optimal placement of master turbines before adverse weather conditions occur. This advance preparation ensures that master turbines are strategically positioned to detect turbulence and weather changes in critical directions, enabling prompt shutdown responses.
Solution Approach 2:
The system continuously monitors weather conditions, turbulence detection accuracy, and shutdown response times to provide feedback on master turbine performance. This feedback loop allows the system to identify and correct suboptimal master turbine placements, improving detection precision while managing configuration complexity through data-driven optimization.
3Productivity
If automatic dynamic profile changing is implemented, then the management efficiency is improved and damage from adverse weather is reduced, but the system complexity increases
Solution Approach 1:
The controller performs multiple functions including monitoring operational parameters, analyzing weather conditions, determining optimal turbine configurations, and executing shutdown commands. By consolidating these diverse functions into a single multi-functional control system, the patent improves management efficiency while managing overall system complexity through functional integration rather than proliferation of separate components.
Solution Approach 2:
The system replaces manual mechanical configuration and monitoring with automated electronic control and data analysis. The controller uses software algorithms to analyze operational parameters and automatically adjust turbine profiles, substituting complex manual procedures with streamlined electronic automation that improves efficiency while the complexity is managed through software rather than physical reconfiguration.
Data Source
Figure 1
Figure 2
Figure 3
AI summary
A method 200 of managing a wind farm (301) is disclosed. The method 200 comprises analyzing operating parameters associated with the wind farm (301). The wind farm (301) comprises a plurality of wind turbines (362, 364, 366, 368) having a turbine profile. The turbine profile is one of a master profile and a slave profile. The operating parameters comprise historical operational data and real-time operational data associated with the wind farm (301). The method includes determining at least one wind turbine (366) in the slave profile whose turbine profile needs to be changed based on the operating parameters and dynamically changing the turbine profile of the at least one wind turbine (366) from the slave profile to the master profile.