Event-Based Wind Turbine Control System for Grid Stability
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Solution Overview
Problem
The integration of wind power into large-scale power grids is challenging due to the instability of wind turbine generators, which fluctuate with wind conditions, making it difficult to ensure stable and controllable power production. Existing solutions, such as meteorological modeling and fuzzy control systems, face complexity in accurately predicting and managing these fluctuations.
Innovation Solution
A control system that analyzes event data using conditional rules, allowing for optimized control of wind turbine parameters without requiring precise modeling of the power generator-grid system. This system includes a predictive event controller that adjusts parameters based on predefined and adaptive event conditions, using evaluation weights and analysis methods like fuzzy logic and statistical analysis to anticipate and mitigate power fluctuations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If meteorological modeling is used to predict power production changes, then power output prediction capability is improved, but system complexity increases due to the complex combination of external and internal influences
Solution Approach 1:
The patent extracts only the necessary event data from the complex system, focusing on specific predefined events and their associated data rather than attempting to model all external and internal influences. This selective extraction simplifies the system while maintaining prediction capability.
Solution Approach 2:
The patent segments the complex power system into discrete events with specific conditions and data requirements. By dividing the continuous complex system into separate event-based units, each with its own data collection and analysis rules, the overall system complexity is reduced while maintaining comprehensive monitoring capability.
2Measurement precision
If comprehensive system modeling is attempted to capture all influences, then prediction accuracy is improved, but the difficulty of detecting and measuring increases
Solution Approach 1:
The patent applies partial action by collecting and analyzing only the specific event data necessary for power production control, rather than attempting to measure and model all system parameters. This selective approach reduces measurement difficulty while maintaining sufficient accuracy for control purposes.
3Reliability
If existing SCADA systems are extensively redesigned to improve control, then control effectiveness is improved, but implementation complexity and cost increase
Solution Approach 1:
The patent applies preliminary action by defining event conditions, data collection requirements, and analysis rules in advance before implementation. This pre-planning allows the system to be deployed on existing SCADA infrastructure without extensive redesign, as the event-based framework can be overlaid on current systems.
Solution Approach 2:
The event-based control system is designed to be universal and compatible with existing SCADA systems. By creating a layered event analysis framework that can operate on top of various underlying systems, the solution improves control effectiveness without requiring extensive redesign of existing infrastructure.
Data Source
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AI summary
The present invention relates to a control system comprising a control interface between one or more wind turbine generators and a power grid, where the wind turbine generators are coupled to the power grid and contribute to the power production of the grid. The control interface is arranged to receive a set of event data. In embodiments, the set of event data may be any data available to a SCADA system. The set of event data is analysed in terms of predetermined event rules comprising at least one predefined event condition and a set of adaptive event conditions. Based on the analysis an event output is provided in order to control a parameter of the one or more wind turbine generators. In embodiments, the control system may be implemented in, or in connection with a SCADA system, moreover, the event output may be based on fuzzy logic, a neural network or statistical analysis.