Wind Farm Data Buffering for Low-Burden Turbine Collection
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Solution Overview
Problem
Existing wind turbine data collection systems face challenges in efficiently managing and processing large volumes of sensor data, particularly in scenarios where wired connections are impractical, leading to high costs and unreliable data transfer over wireless systems, and often require computationally expensive operations to be performed on wind turbines with limited processing capabilities.
Innovation Solution
A method and system where a wind farm server collects and buffers data from multiple wind turbines, allowing for decoupling of data consumers from the turbines, enabling bulk sensor data to be transmitted to a server for processing and subsequent request-based delivery to client systems, thereby offloading processing to more capable systems and simplifying maintenance and expansion using standard hardware.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Power
If data collection and processing operations are performed directly on wind turbines, then data processing capability is improved, but device complexity and processing burden on wind turbines increases
Solution Approach 1:
The patent extracts data processing operations from the wind turbine system and relocates them to a separate server system. The wind turbine controller only performs minimal data collection and transmission, while the server handles bulk data processing, storage, and client requests. This separation reduces the processing burden on wind turbines while maintaining overall system capability.
Solution Approach 2:
The patent introduces a server as an intermediary between wind turbines and client systems. The server acts as a mediator that receives data from turbines, processes it, stores it in a database, and serves client requests. This intermediary handles the computational complexity, allowing wind turbines to remain simple data sources.
2Reliability
If wired connections are used for data transfer, then data transfer reliability and bandwidth are improved, but installation complexity and cost increases
Solution Approach 1:
The patent makes the communication system universal by supporting multiple connection types (wired and wireless). The server is configured to accept data from turbines via various communication protocols and connection methods, allowing the system to adapt to different installation scenarios without requiring separate systems for wired versus wireless deployments.
3Ease of manufacture
If wireless communication systems are used for data transfer, then installation complexity is reduced, but data transfer cost and reliability deteriorates
Solution Approach 1:
The server acts as a robust intermediary that can implement data validation, error handling, and retry logic for wireless communications. It buffers incoming data, manages communication protocols, and ensures data integrity even when wireless connections are unreliable, thereby compensating for the inherent limitations of wireless systems.
Solution Approach 2:
The server implements buffering mechanisms that cushion against data loss or transmission failures. Data is queued and managed in buffers, allowing the system to handle intermittent wireless connectivity issues without losing critical information, thus improving effective reliability despite using wireless communication.
4Adaptability or versatility
If multiple client systems access wind turbine data simultaneously, then data accessibility is improved, but processing burden on wind turbines increases
Solution Approach 1:
The patent extracts all client-facing processing operations from the wind turbine system. The turbine controller only collects and transmits raw data, while the server handles multiple client connections, data queries, processing, and response generation. This allows multiple clients to access data simultaneously without increasing the burden on turbines.
Solution Approach 2:
The server serves as an intermediary that manages multiple client systems. It receives data from turbines once, stores it centrally, and then serves multiple clients' data requests independently. This eliminates the need for turbines to handle multiple client connections and processing operations, maintaining simplicity while enabling versatile data access.
Data Source
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AI summary
A method, controller, wind turbine, and computer program product are disclosed for collecting data from wind turbines in a wind farm. An example method generally includes receiving, from a client device, a subscription request identifying a plurality of data points to collect from a set of wind turbines. A wind farm server establishes a client interface with the client device. The wind farm server receives data points form the plurality of wind turbines and buffers the identified collected data points from the set of wind turbines in a data repository. Through the client interface, the wind farm server receives a request for data points collected from at least one wind turbine over a specified time period, and responsive to the request, transmits the requested data points to the client device. The wind farm server also may push collected data points from wind turbines to a data analysis system.