Wind Turbine Auxiliary Load Control for Real-Time Power Optimization

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Solution Overview

Problem

Existing wind turbine systems lack an efficient method to optimize auxiliary loads based on real-time operational usage, leading to suboptimal performance and increased energy losses.

Innovation Solution

A system and method that tracks real-time operational usage of auxiliary loads in wind turbines, allowing for online estimation and optimization of power consumption. This involves using a controller to monitor and adjust auxiliary loads based on operational parameters and market conditions.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If auxiliary loads operate continuously to maintain all functionalities, then reliability is improved, but energy consumption increases

Engineering Contradiction:
Improvefunctional reliabilityVSAvoidauxiliary power consumption
Core Design Contradiction:
ReliabilityVSUse of energy by moving object

Solution Approach 1:

The system dynamically adjusts auxiliary load operation based on real-time monitoring of operational usage and environmental conditions. Non-critical auxiliary loads are selectively deactivated when conditions permit, while critical loads maintain operation to ensure functional reliability. This dynamic adaptation resolves the contradiction by making the system flexible rather than static in its power consumption patterns.

Inventive Principle:
Principle #15Dynamics

Solution Approach 2:

The control system changes operational parameters of auxiliary loads based on monitored conditions including operational usage thresholds, environmental parameters, and power availability. By adjusting parameters such as load activation status, power allocation, and operational timing, the system optimizes the balance between maintaining reliability and reducing energy consumption.

Inventive Principle:
Principle #35Parameter changes

2Loss of energy

If auxiliary loads are optimized to reduce energy consumption, then energy efficiency is improved, but functional reliability may deteriorate

Engineering Contradiction:
Improveenergy loss reductionVSAvoidfunctional reliability
Core Design Contradiction:
Loss of energyVSReliability

Solution Approach 1:

The system applies different operational strategies to different auxiliary loads based on their criticality and functional importance. Critical loads receive priority power allocation and maintain higher reliability standards, while non-critical loads are subject to greater optimization and energy reduction measures. This localized differentiation resolves the contradiction by applying appropriate quality levels to different system components.

Inventive Principle:
Principle #3Local quality

Solution Approach 2:

The control system continuously monitors operational usage, system performance, and functional status of auxiliary loads, using this feedback to adjust power allocation and operational decisions in real-time. This closed-loop feedback mechanism ensures that energy optimization does not compromise critical functions, as the system adapts based on actual system needs and performance data.

Inventive Principle:
Principle #23Feedback

3Productivity

If real-time tracking of operational usage is implemented, then optimization capability is improved, but system complexity increases

Engineering Contradiction:
Improveoptimization capabilityVSAvoidcontrol system complexity
Core Design Contradiction:
ProductivityVSDevice complexity

Solution Approach 1:

The control system integrates multiple functions including operational usage tracking, environmental parameter monitoring, power consumption optimization, and load management into a single multi-functional platform. This universal approach reduces overall system complexity by consolidating control functions rather than implementing separate specialized systems for each function.

Inventive Principle:
Principle #6Universality (Multi-functionality)

Solution Approach 2:

The system performs self-monitoring and self-optimization of auxiliary load operation based on tracked operational usage and monitored conditions. By enabling the system to automatically track its own operational parameters and make optimization decisions without external intervention, the complexity burden is shifted from external control infrastructure to the system's own control architecture, reducing overall system complexity.

Inventive Principle:
Principle #25Self-service

Data Source

PatentEP3851670B1System and method for optimizing auxiliary loads based on operational usage
Publication Date: 2025.04.23 GENERAL ELECTRIC RENOVABLES ESPANA SL
  • EP3851670B1 patent drawingFigure 1
  • EP3851670B1 patent drawingFigure 2
  • EP3851670B1 patent drawingFigure 3

AI summary

A method for optimizing auxiliary loads of a wind farm having a plurality of wind turbines includes tracking, via a farm-level controller of the wind farm, operational usage for one or more auxiliary components of at least one of the wind turbines in the wind farm as the operational usage for the one or more auxiliary components induces a load on the auxiliary component(s). The method also includes determining, via the farm-level controller, a power consumption of the load induced on the one or more auxiliary components based on the operational usage. Further, the method includes receiving, via the farm-level controller, at least one additional parameter of the wind farm. Moreover, the method includes implementing, via the farm-level controller, a control command for one or more of the one or more auxiliary components based on the power consumption and the at least one additional parameter.