Wind Farm Controller Pooling for Idle Resource Utilization
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Solution Overview
Problem
In wind farms, computing resources are underutilized and wasted due to non-operational wind turbines, which are either shut down for maintenance or component faults, leading to inefficiencies in processing time-critical data for optimal power output and load management.
Innovation Solution
A method to determine the status of wind turbines, identify available computing resources, and allocate computing tasks to these resources for parallel processing, ensuring that available resources are utilized effectively and efficiently, even when turbines are not operational.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If computing resources are dedicated solely to operational wind turbines, then computing reliability for active turbines is improved, but computing resource utilization deteriorates due to idle resources from non-operational turbines
Solution Approach 1:
The patent makes computing resources universal by allowing controllers from non-operational wind turbines to perform computing tasks for both their own turbine (when available) and other operational turbines. The controller serves multiple functions: local turbine control and farm-wide computing resource pooling, enabling resource sharing across the entire wind farm regardless of individual turbine operational status
Solution Approach 2:
The patent merges computing resources from multiple wind turbine controllers into a unified pool. Instead of isolated dedicated resources, controllers from operational and non-operational turbines are combined into a shared resource pool that can be dynamically allocated to any turbine needing computing capacity, maximizing overall utilization
2Measurement precision
If computing tasks are processed sequentially by individual controllers, then computing task accuracy is improved, but processing speed deteriorates due to lack of parallel processing capability
Solution Approach 1:
The patent segments computing tasks into independent units that can be distributed across multiple controllers for parallel processing. Each controller handles specific task segments while maintaining data integrity, allowing simultaneous execution of multiple computing operations across the wind farm without compromising individual task accuracy
Solution Approach 2:
The patent transitions from single-dimension sequential processing to multi-dimensional parallel processing by utilizing multiple controllers across different spatial locations in the wind farm. Tasks are distributed across the spatial dimension of the network, enabling concurrent execution while maintaining computational accuracy through coordinated processing
3Reliability
If all computing tasks are handled by operational turbine controllers, then task completion reliability is improved, but resource waste increases due to idle controllers from non-operational turbines
Solution Approach 1:
The patent recovers idle computing resources from non-operational turbines by making their controllers available for farm-wide task processing. Instead of discarding these resources when a turbine is offline, the system recovers and repurposes them to handle computing tasks for other operational turbines, eliminating waste while maintaining reliability
Data Source
AI summary
A method of managing computing tasks in a wind farm is provided. The method comprises determining the status of a plurality of wind turbines in the wind farm, determining available computing resources based on the status of the plurality of wind turbines, and allocating a portion of the computing tasks to the available computing resources for processing.