Wind Turbine Signal Estimation via Variable Sampling Integration

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Solution Overview

Problem

Existing wind turbine power converters face challenges in accurately estimating electrical signal characteristics due to variable sampling intervals and frequencies, which can lead to noise issues and inefficiencies in feedback loop control, especially when implementing random or variable PWM techniques.

Innovation Solution

A method and apparatus for estimating wind turbine electrical signal characteristics by buffering sample values and corresponding variable sample times, integrating these values while adjusting the integration period to maximize the sum of time periods without exceeding the desired integration period, using a processor and memory to implement the method, and maintaining circular buffers to efficiently manage sample data.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If variable sampling intervals are used in wind turbine power converters, then adaptability to instantaneous operating conditions is improved, but measurement precision of electrical signal characteristics deteriorates

Engineering Contradiction:

Improveadaptability to instantaneous operating conditionsVSAvoidprecision of electrical signal characteristic estimation

Core Design Contradiction:

Adaptability or versatilityVSMeasurement precision

Solution Approach 1:

The patent implements dynamic sampling where the sampling interval varies based on instantaneous operating conditions. The controller adjusts sampling rates adaptively - using shorter intervals during transient conditions to capture rapid changes, and longer intervals during steady-state operation. This dynamic approach maintains measurement precision across varying conditions while improving adaptability to instantaneous operating states.

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The patent changes the sampling interval parameter dynamically based on operating conditions. By monitoring system state and adjusting the sampling period accordingly, the system optimizes the balance between capturing sufficient signal detail for accurate characteristic estimation and adapting to changing operating conditions. This parameter adjustment resolves the contradiction by making precision maintenance conditional on the sampling strategy.

Inventive Principle:

Principle #35Parameter changes

2Object-affected harmful factors

If random PWM techniques are implemented, then tonal noise is reduced, but control system stability deteriorates

Engineering Contradiction:

Improvetonal noiseVSAvoidfeedback loop control stability

Core Design Contradiction:

Object-affected harmful factorsVSStability of the object's composition

Solution Approach 1:

The patent employs periodic sampling at carefully selected frequencies that are synchronized with the PWM switching frequency. By using periodic action with specific frequency relationships, the system maintains stable feedback control while the random PWM technique continues to reduce tonal noise. The periodic measurement approach provides consistent control loop operation despite the random switching pattern.

Inventive Principle:

Principle #19Periodic action

Solution Approach 2:

The patent implements a feedback mechanism where electrical signal characteristics are continuously measured and used to adjust control parameters. This feedback loop compensates for the instability introduced by random PWM by dynamically adjusting control variables based on actual system response. The feedback ensures stability is maintained while allowing random PWM to reduce tonal noise.

Inventive Principle:

Principle #23Feedback

3Ease of manufacture

If fixed integration periods are used, then calculation simplicity is improved, but accuracy of characteristic estimation deteriorates under variable sampling

Engineering Contradiction:

Improvecalculation simplicityVSAvoidaccuracy of characteristic estimation

Core Design Contradiction:

Ease of manufactureVSMeasurement precision

Solution Approach 1:

The patent implements dynamic integration period adjustment where the integration period adapts to the sampling interval. When sampling intervals vary, the integration period is automatically adjusted to maintain an appropriate number of samples per integration cycle. This dynamic approach preserves calculation simplicity through automated adjustment while maintaining estimation accuracy under variable sampling conditions.

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The patent changes the integration period parameter based on the actual sampling interval used. By dynamically adjusting this parameter, the system maintains the relationship between sampling rate and integration period that is necessary for accurate characteristic estimation. This parameter change approach keeps calculations simple through systematic adjustment while ensuring accuracy is maintained.

Inventive Principle:

Principle #35Parameter changes

Data Source

PatentUS11143167B2Estimating a characteristic of a wind turbine electrical signal

Publication Date: 2021.10.12 VESTAS WIND SYSTEMS AS

AI summary

A method and apparatus for estimating a characteristic of a wind turbine electrical signal comprises buffering a sequence of sample values of the wind turbine electrical signal and a sequence of sample times corresponding with the sequence of sample values. The time periods represented by the sample times are variable. A sub-sequence of the buffered sample values to integrate is determined, based at least in part on a sum of the time periods. The characteristic is estimated by integrating the sample values in the sub-sequence.