Gas Turbine Probabilistic Control for Firing Temperature Variation

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Solution Overview

Problem

Existing gas turbine control systems face challenges in accurately estimating and controlling unmeasured parameters like firing temperature, leading to inefficiencies and variations across machines due to measurement uncertainties and component variations, resulting in reduced performance and increased emissions.

Innovation Solution

A probabilistic control system that adjusts gas turbine power output and operating conditions based on measured emissions and ambient conditions, using a computing device to command each turbine to a base load level, adjust power output to match a scaled value, and refine operating conditions using an emissions scale factor to minimize firing temperature variation.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If design margins are used to accommodate worst-case operational boundaries, then reliability is improved, but productivity deteriorates due to reduced performance at many operating conditions

Engineering Contradiction:

ImprovereliabilityVSAvoidperformance

Core Design Contradiction:

ReliabilityVSProductivity

Solution Approach 1:

The system implements feedback control by measuring actual emissions and power output, comparing them to nominal values, and using the differences (adjusted by scale factors) to iteratively refine operating conditions. This closed-loop feedback mechanism allows the system to maintain reliability while optimizing performance, eliminating the need for conservative design margins.

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The system dynamically adjusts operating parameters (such as fuel flow, air flow, valve positions) based on measured deviations from nominal emissions and power output. By changing these parameters in real-time based on actual conditions, the system achieves both high reliability and optimal performance across varying operating conditions.

Inventive Principle:

Principle #35Parameter changes

2Measurement precision

If unmeasured parameters are indirectly controlled using measured parameters, then measurement precision is improved, but reliability deteriorates due to uncertainty in indirect parameter values

Engineering Contradiction:

Improvemeasurement precisionVSAvoidreliability

Core Design Contradiction:

Measurement precisionVSReliability

Solution Approach 1:

The system uses feedback control to continuously measure actual emissions and power output, compare them to expected nominal values, and adjust operating conditions to minimize deviations. This feedback mechanism compensates for uncertainties in indirect parameter estimation, improving both measurement precision and reliability simultaneously.

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The system replaces direct physical measurement of difficult-to-measure parameters (like firing temperature) with an alternative approach using emissions measurements and computational models. By substituting the measurement mechanism and using iterative refinement based on scale factors, the system achieves reliable estimation without direct sensing.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

3Reliability

If probabilistic control with scale factors is used to reduce firing temperature variation, then manufacturing precision deteriorates due to component variations, but reliability improves through reduced machine-to-machine variation

Engineering Contradiction:

ImprovereliabilityVSAvoidfiring temperature variation

Core Design Contradiction:

ReliabilityVSManufacturing precision

Solution Approach 1:

The system introduces scale factors as adjustable parameters that are determined through iterative testing and refinement. These scale factors modify the relationship between control inputs and actual emissions/power output, compensating for manufacturing variations. By changing these parameters based on measured performance, the system achieves consistent reliability across machines with different manufacturing tolerances.

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The system transitions from static, fixed control parameters to dynamic, adaptive parameters that are continuously refined based on measured emissions and power output. The scale factors are not fixed but are updated through iterative processes, allowing the control system to adapt to manufacturing variations and achieve consistent performance across different machines.

Inventive Principle:

Principle #15Dynamics

Data Source

PatentUS9882454B2Application of combined probabilistic control in gas turbine tuning for power output-emissions parameters with scaling factor, related control systems, computer program products and methods

Publication Date: 2018.01.30 GE INFRASTRUCTURE TECH LLC

AI summary

Various embodiments include a system having: at least one computing device configured to tune a set of gas turbines (GTs) by performing actions including: commanding each GT in the set of GTs to a base load level, based upon a measured ambient condition for each GT; commanding each GT in the set of GTs to adjust a respective power output to match a scaled power output value equal to a fraction of a difference between the respective power output and a nominal power output value, and measuring an actual emissions value for each GT during the adjusting of the respective power output; and adjusting an operating condition of each GT in the set of GTs based upon a difference between the respective measured actual emissions value, a nominal emissions value at the ambient condition and a nominal emissions value at the ambient condition.