Gas Turbine Performance Software – Autonomous Tuning

To improve the performance of your gas turbine, there are several key strategies aimed at increasing efficiency, output and operational reliability.

• Improved design and materials: Engineers can work on designs that emphasize faster starts and quicker ramp-ups by implementing upgrades to the turbine technology.
• Digital Solutions: Several companies offer digital solutions to optimize gas turbine operations, including advanced solutions with AI/ML technology, physics-based modeling, and digital twins. GE Vernova's Autonomous Tuning, a gas turbine performance software is an example of this.
• Temperature and Humidity Control: are an important factor for performance. Since turbines use air, changes in mass flow or density of air impacts performance. Controlling ambient temperature is crucial to improve output and heat rate. If in a humid area, controlling the air emerging from the combustion inlet is important for efficiency and emissions.
• Fuel Type Optimization: ensures the fuel quality and suitability for the specific turbine design.
• Other crucial improvements include: loss management (excessive clearance between blades and casing, clogged air filters), regeneration, intercooling, and reheating all can increase net output. By implementing these key strategies, gas turbines can more easily maintain entitlement and operate at peak performance.

Calculating the efficiency of a gas turbine involves comparing the work output of the turbine to the energy input in the form of fuel. To calculate the efficiency, you would need the following data:

1. Power Output: The actual power output of the gas turbine in megawatts (MW).
2. Fuel Flow Rate: The rate at which fuel is consumed by the turbine, typically in kilograms per second (kg/s).
3. Heating Value of Fuel: The amount of energy released when a certain amount of fuel is burned, usually given in megajoules per kilogram (MJ/kg).

A simplified formula to calculate the thermal efficiency of a gas turbine n= work output/heat input = power output/(fuel flow rate x heating value of fuel). There are more detailed calculations that include the compressor and turbine efficiencies, pressure ratios and specific heats of the gases at constant pressure. These require complex calculations involving thermodynamic equations and isentropic processes.

Performance optimization of a gas turbine engine are methods and strategies to achieve optimal performance. This is achieved by implementing strategies to improve efficiency, reliability and overall performance. Common techniques include methods to reduce fuel consumption while maintaining output, maximizing thrust for same fuel consumption while reducing turbine blade temperature (source Science Direct).

Methods to improve efficiency of gas turbines include:

• Thermodynamic Optimization: Involves improving the thermodynamic cycle of the turbine, for instance, optimizing the pressure ratio. Thermodynamic Optimization enhances efficiency by maximizing the energy extracted from the fuel.
• Component Efficiency: Enhances the efficiency of individual components like compressors, combustors and turbines. Improved cooling techniques or aerodynamic designs help to achieve component efficiency.
• Control System Optimization: Improves transient response and overall performance such as reinforcement learning to ensure the turbine operates within its most efficient parameters.
• Maintenance and Monitoring Optimization: Achieved with regular maintenance and real-time monitoring. Predictive data analytics of the turbine's performance provides even more optimization with early issue identification and by preventing issues that could lead to energy losses or reduced output.
• Fuel Optimization: May involve higher quality or alternative fuels for improved combustion efficiency. New technology that uses AI/ML can also automatically improve combustion and reduce fuel and emissions.

Sources: Cambridge.org, Ntrs.nasa.gov, Science Direct

Several factors affect the performance of gas turbines. Examples include compressor pressure ratio, turbine inlet temperature, humidity, altitude, compressor efficiency, compressor exit diffuser Cp, combustor pressure loss, turbine efficiency, and blade metal allowable temperature. Inlet air temperature, for example, impacts performance because the temperature of the air entering the turbine affects its density. Cooler air is denser and can improve the mass flow rate, leading to better performance. On the other hand, maintenance and fouling are more controlled by plant teams and teams that perform regular maintenance can prevent fouling and degradation of components that impact performance.

There are different methods of calculation for fuel consumption of a gas turbine. The choice of formula depends on the specific application and available data. Here are 3 examples of common formulas used to calculate fuel consumption of a gas turbine:

1. Specific Fuel Consumption (SFC) represents the amount of fuel consumed per unit of power output. It is particularly useful for assessing the efficiency of a gas turbine in terms of fuel consumption.
2. Empirical Approximation which is good for simple-cycle gas turbines.
3. Heat Rate Method is used for combined-cycle plants and relates fuel consumption to the power output.

The life expectancy of an aeroderivative gas turbine typically ranges from 20-30 years, depending on several factors such as:
• Operating profile (base load vs. peaking)
• Maintenance practices
• Fuel types used
• Environmental conditions
• OEM design and materials
• Upgrades and overhauls

Aeroderivative turbines are different from heavy-duty frame turbines. Aeroderivative gas turbines are derived from aircraft engines and are modular in design. This allows for routine replacement of critical engine sections, making life-extension strategies more flexible and cost-effective. For example, the GE Vernova LM6000 series is one of the most widely used aeroderivative turbines. With proper maintenance and part replacement, these turbines can last over 25 years in many applications.

Software, such as Autonomous Tuning, can significantly extend the lifespan of gas turbines by optimizing how the turbine operates in real time by reducing thermal stress (resulting in a longer life for hot section parts), minimizing mechanical wear and reducing vibrations (especially valuable for peaking units). This helps improve combustion stability by maintaining optimal air-fuel ratios and reducing combustion dynamics.

Aeroderivative gas turbines can fail due to a combination of mechanical wear, thermal stress, foreign object damage, lubrication issues, or fuel quality. Common failure points include turbine blades, bearings, and seals which can be exacerbated by high operating temperatures and cyclic loads. Other causes of failures include inadequate maintenance.

GE Vernova’s Autonomous Tuning solution helps to prevent or mitigate common failure modes in aeroderivative gas turbines by continuously optimizing combustion and performance parameters in near real-time.

Three ways it helps address specific failure causes:
Hot section failures
• How Autonomous Tuning helps: By dynamically adjusting fuel splits with AI/ML, firing temperatures, and airflows, Autonomous Tuning finds optimal combustion conditions in near real-time. This reduces thermal stress, hot spots, and temperature cycling, which are major contributors to creep and fatigue in turbine blades.

Combustion system issues
• How Autonomous Tuning helps: It continuously monitors combustion dynamics (e.g., pressure pulsations, flame stability) and adjusts parameters to:
o Prevent combustion instabilities
o Maintain low NOx emissions without over-injecting water or steam
o Avoid lean blowout or rich quenching, both of which can damage hardware

Structural and vibration issues
• How Autonomous Tuning helps: By smoothing out transients and maintaining optimal operating conditions, Autonomous Tuning reduces the likelihood of resonance and harmful vibrations that can lead to structural fatigue or misalignment.

Gas turbine tuning is the process of adjusting the operational parameters of a gas turbine to optimize its performance, efficiency, emissions, and reliability. This tuning can be done manually or automatically (as in Autonomous Tuning systems).

The purpose of gas turbine tuning includes:
1) Optimizing combustion for different ambient conditions (e.g. temperature, pressure, humidity), which protects the equipment and reduces fuel consumption;
2) Minimize emissions;
3) Maximize efficiency and power output;
4) Equipment health maintenance for improved reliability and uptime to avoid issues like combustion dynamics or lean blowout; and,
5) Extend component life by reducing thermal and mechanical stress.

There are two different types of tuning: manual tuning and autonomous (auto) tuning. Manual tuning is performed by engineers during commissioning or maintenance. Auto-tuning uses sensors, control algorithms, and machine learning. Manual tuning can’t adapt to changing conditions and is dependent on the test data and experience of the engineer. Closed-loop software such as Autonomous Tuning continuously adjusts parameters in near real-time and can respond to ambient changes, load shifts, and fuel variability.

Key parameters adjusted during tuning are:
• Fuel-to-air ratio: Balancing combustion for efficiency and emissions
• Inlet guide vane (IGV) positions: To control airflow into the compressor
• Variable stator vane angles: To optimize compressor performance
• Turbine firing temperature: To manage output and component life
• Water or steam injection rates: For NOₓ control in some systems

Gas turbine tuning is essential for maintaining optimal performance, reliability, and emissions compliance. Specifically:
• Performance optimization: Tuning ensures the turbine operates at peak efficiency across varying loads and ambient conditions. Poor tuning can lead to reduced power output and increased fuel consumption.
• Emissions control: Gas turbines must meet strict NOx and CO emissions regulations. Tuning adjusts fuel-air ratios and combustion dynamics to stay within limits without sacrificing performance.
• Hardware protection: Imbalanced combustion or temperature spikes can damage hot section components. Tuning helps maintain uniform temperature profiles and avoid thermal stress.
• Operational flexibility: In peaking or cycling operations, tuning ensures smooth transitions between load points, minimizing wear and tear during startups, shutdowns, and load changes.
• Avoiding combustion instabilities: Instabilities can cause pressure oscillations, leading to fatigue and failure. Tuning dampens these instabilities by adjusting combustion parameters in real time.

Combustion tuning is the process of adjusting the fuel and air mixture, firing temperature, and other combustion parameters in a gas turbine to optimize performance, reduce emissions, and ensure stable operation. It involves fine-tuning the combustion system to achieve the best balance between efficiency, power output, and environmental compliance. Combustion tuning is either manual or automated. Combustion tuning helps prevent issues like combustion instability, excessive NOx emissions, or component overheating.

Common combustion tuning techniques for gas turbines include:
• Adjusting fuel-to-air ratios to optimize flame stability and minimize emissions.
• Modifying fuel nozzle configurations to improve mixing and combustion efficiency.
• Using variable geometry components, such as inlet guide vanes, to control airflow and temperature distribution.
• Implementing advanced control algorithms that respond to near real-time sensor data for dynamic tuning.
• Monitoring and adjusting combustion dynamics, such as pressure oscillations, to prevent instabilities like humming or rumbling.
• Utilizing emissions feedback loops to fine-tune for lower NOx and CO levels.

If performing manual tuning, these techniques are often applied during commissioning, after major maintenance, or when performance or emissions drift from desired targets. GE Vernova’s Autonomous Tuning uses AI and machine learning, specifically neural networks, to continuously adjust flame temperatures and fuel splits every two seconds to optimize combustion for emissions compliance, fuel efficiency, and acoustic performance. This closed-loop system responds dynamically to changes in ambient temperature, fuel properties, and turbine degradation, eliminating the need for manual seasonal tuning and reducing downtime.

An aeroderivative gas turbine is a type of gas turbine engine that is derived from aircraft jet engines but adapted for industrial and marine applications. These turbines are known for their lightweight design, high efficiency, and fast start-up capabilities, making them ideal for power generation, mechanical drive, and marine propulsion.

Key Characteristics:
• Aircraft engine heritage: Aeroderivative turbines are based on the core design of jet engines used in aviation (like those on commercial or military aircraft). Manufacturers adapt these designs for stationary or marine use by modifying components such as the power turbine and gearboxes.
• High power-to-weight ratio: Because they originate from aviation, aeroderivative turbines are much lighter and more compact than traditional heavy-frame industrial turbines, which is beneficial for mobile or offshore applications.
• Fast start and load-following: They can ramp up quickly, making them ideal for peaking power plants, grid balancing, or backup power in renewables-heavy systems.
• Fuel flexibility: These turbines can operate on a variety of fuels, including natural gas, diesel, and even biofuels, with some models capable of dual-fuel operation.

GE Vernova currently offers a portfolio of aeroderivative gas turbines designed for fast, flexible, and lower-emission power generation including:
• LM2500 series with over 100 million operating hours
• LM6000 series with over 1,300 units shipped and 40+ million operating hours
• LMS100, which is an economical solution for the dispatch needs of industries needing fast and flexible power
• TM2500, which has over 140 million operating hours and is known for its widespread deployment and mobile, emergency-use versatility