Wind Turbine Control Load Shedding by Task Service Level
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Wind energy installations face challenges in optimizing the use of processing resources, leading to either excessive idle capacity or insufficient capacity to handle critical tasks, resulting in increased costs and potential operational risks.
Innovation Solution
A method that identifies critical processing resource requiring tasks, defines minimum acceptable service levels, and implements actions to reduce processing resource consumption while maintaining service levels, prioritizing tasks to ensure critical operations are not compromised.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the processing capacity of the processing resources is dimensioned to handle a significant number of tasks simultaneously, then sufficient processing capacity is available for critical tasks, but significant idle processing capacity exists for most of the time, increasing costs
Solution Approach 1:
The system dynamically adjusts the execution of processing tasks based on real-time processing load monitoring. When the processing load exceeds a threshold, non-critical tasks are postponed or executed with reduced priority, allowing the processing capacity to be dynamically reallocated to critical tasks. This dynamic approach eliminates the need for permanently dimensioned excess capacity while ensuring reliability when needed.
Solution Approach 2:
The system changes the operational parameters of processing tasks based on current system conditions. By monitoring processing load and adjusting task execution parameters (such as execution timing, priority, or detail level), the system optimizes the use of processing capacity. This allows the same processing resource to handle varying workloads efficiently without requiring permanent over-provisioning.
2Loss of energy
If the processing resources are dimensioned with a significantly smaller processing capacity, then costs are reduced, but critical tasks may not be performed due to lack of processing capacity, impacting operation
Solution Approach 1:
The system continuously monitors the processing load and uses this feedback to make real-time decisions about task execution. When processing capacity becomes available, previously postponed critical tasks are rescheduled for execution. This feedback mechanism ensures that even with smaller processing resources, critical tasks are reliably executed when capacity permits, maintaining operational reliability without requiring large permanent capacity.
Solution Approach 2:
The system identifies and prioritizes critical tasks in advance, creating a structured approach to task execution. By pre-defining which tasks are critical and establishing execution priorities, the system ensures that when processing capacity is available, the most important tasks are executed first. This preliminary classification guarantees reliability for critical functions even under constrained resource conditions.
3Productivity
If multiple processing resource requiring tasks are executed simultaneously with high processing capacity, then all tasks are completed with high service level, but processing resource consumption increases significantly
Solution Approach 1:
The system applies partial action by executing only the necessary portion of processing tasks at any given time based on current processing load. Instead of always executing all tasks at full service level, the system dynamically determines the appropriate level of task execution. When processing load is high, non-critical tasks may be executed with reduced priority or postponed, reducing processing resource consumption while still maintaining adequate productivity for critical functions.
Data Source
Figure 1
Figure 2~3
Figure 4
AI summary
A method and a system for optimising use of a processing resource in a wind energy installation (1) is disclosed. A plurality of processing resource requiring tasks related to control of the wind energy installation (1) are identified. For each processing resource requiring task, a minimum acceptable service level related to the task, and at least one action which causes a decrease in processing resource consumption related to the task while ensuring that the minimum acceptable service level is met, are defined. The processing resource requiring tasks are ranked, so as to create a prioritized list (10) of processing resource requiring tasks. In the case that a monitored processing load level exceeds a first threshold level, at least one of the processing resource requiring tasks is selected in accordance with the prioritized list (10), and least one of the actions defined for the at least one selected task is performed.