Gas Turbine Heating Value Control for Lower Fuel
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Solution Overview
Problem
Gas turbines face challenges when using lower heating value fuels due to higher levels of inert compounds, which affect combustion efficiency and emissions.
Innovation Solution
A control system for gas turbines that includes a processor configured to receive signals from sensors and apply them to a heating value model to derive the fuel's heating value, enabling real-time control and improved efficiency and emission reduction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If lower heating value fuels are used, then fuel flexibility and adaptability are improved, but combustion efficiency and emissions performance deteriorate due to higher inert compounds
Solution Approach 1:
The system dynamically adjusts combustion parameters (air-fuel ratio, injection timing, combustion mode) based on real-time heating value measurements. By continuously changing operational parameters to match the actual fuel heating value, the system maintains optimal combustion efficiency across varying fuel qualities while preserving fuel flexibility.
Solution Approach 2:
The system implements a closed-loop feedback mechanism where heating value sensors provide real-time information about fuel quality, and the control system automatically adjusts combustion parameters accordingly. This feedback loop ensures that combustion efficiency is maintained despite variations in fuel heating value, resolving the contradiction between fuel flexibility and combustion efficiency.
2Adaptability or versatility
If lower heating value fuels are used, then fuel flexibility is improved, but emissions performance deteriorates
Solution Approach 1:
The system modifies combustion parameters such as excess air ratio, injection timing, and combustion temperature based on measured heating values. These parameter changes optimize the combustion process to minimize harmful emissions (NOx, CO, unburned hydrocarbons) while maintaining the ability to use various fuel types.
Solution Approach 2:
Real-time heating value measurements feed back to the control system, which automatically adjusts emissions-related parameters. This feedback mechanism ensures that emissions remain within acceptable limits across different fuel types, allowing the system to maintain both fuel flexibility and emissions performance.
3Productivity
If real-time heating value measurement is implemented, then combustion efficiency is improved, but system complexity increases
Solution Approach 1:
The system uses the gas turbine's existing sensors and control infrastructure to measure heating values and adjust combustion parameters. By leveraging already-present components (temperature sensors, pressure sensors, existing control algorithms), the system achieves real-time heating value measurement and control without adding significant complexity.
Solution Approach 2:
The control system performs multiple functions: it monitors existing combustion parameters, measures heating values, determines optimal combustion settings, and executes control actions. By making the control system multi-functional, the patent avoids adding separate dedicated hardware for heating value measurement, thereby reducing overall system complexity while maintaining combustion efficiency.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system effectively manages lower heating value fuels by deriving their heating values and adjusting operations, enhancing fuel flexibility, power production efficiency, and reducing emissions.
Implementation Method 1
A gas turbine engine combusts a mixture of fuel and air to generate hot combustion gases, which in turn drive one or more turbines
Data Source
AI summary
A control system for a gas turbine includes a controller. The controller includes a processor configured to receive a plurality of signals comprising a temperature signal, a pressure signal, a speed signal, a mass flow signal, or a combination thereof, from sensors disposed in the gas turbine system. The processor is further configured to apply the plurality of signals as input to a heating value model. The processor is also configured to execute the heating value model to derive a heating value for a fuel combusted by the gas turbine system. The processor is additionally configured to control operations of the gas turbine system based on the heating value for the fuel.