How digital technology helps processing industries connect the dots

Leaders in the processing industry are exploring ways of using digital technology to create intelligent and autonomous operations that optimize daily production, manage risk, improve margins and enable a more flexible workforce.

Gas turbines play a critical role across the processing industries, such as mechanical drive applications in LNG facilities, compressor stations on natural gas pipelines and cogeneration power utility islands within a processing facility. Digitizing gas turbines and the associated balance of plant equipment can provide significant payback in response to continued pressure to drive down costs, increase efficiency, and improve reliability and availability while meeting new regulations to reduce emissions.

Connecting the dots. By combining closed- and open-loop optimization, whether the producer’s objective is to meet profitability key performance indicators (KPIs) or sustainability goals, digitizing gas turbines makes it possible to connect the dots and meet those goals. As such, producers can extract more value from existing assets with software by bringing intelligent and autonomous operations to bear in three ways:

1. Deploy new operating modes in gas turbines and plant controls that automate and enable flexible, reliable operations
2. Optimize dispatch by ensuring that operations and commercial teams have the best available information on asset- and plant-specific capabilities and costs to manage risk, uncertainty and improve margins
3. Maintain optimal performance across changing operations by monitoring thermal performance and flexible operating modes using plant-level diagnostics to quickly identify and cost-effectively address performance shortfalls.

Digital technologies can help processors connect the dots to make their gas turbines and facilities more adaptable to meet production goals and reduce risk and cost. Software can provide real-time insights, powerful optimization and data-informed decisions. By deploying new operating modes, optimizing dispatch and maintaining optimal performance, digitization helps producers decrease fuel costs, meet emissions regulations and improve availability to drive better economic outcomes.

Deploy new operating modes. Producers in the processing industries increasingly need tools that help reduce the cost of operations, but not at the expense of reliability and availability. New digital technologies have shown the ability to be deployed for gas turbine controls that enable flexible operations and process automation while improving the costs of operation and reliability. An example of such technology is applying artificial intelligence (AI) and machine-learning (ML) to the tuning of gas turbine combustion.

Gas turbines typically require seasonal adjustment, a tuning or mapping of flame temperatures and fuel splits to enable dependable and emissions-compliant operations as weather patterns change throughout the year. This is a manual process performed by an onsite expert and requires an outage that impacts availability, resulting in operational challenges in the processing industry where gas turbine uptime is critical to meeting overall production goals. Furthermore, manual seasonal tuning is only efficient for the precise conditions under which it was completed and does not enable the gas turbine to respond effectively to ambient temperature or fuel property changes between tunings.

Demonstrations have shown that by digitizing the gas turbine and utilizing AI/ML technology to continuously optimize combustion in closed-loop control—in place of manual seasonal adjustments—aero-derivative gas turbine operators can achieve the following benefits:

• 0.5%—1% reduction in fuel consumption/carbon dioxide (CO₂) emissions
• Up to 14% reduction in carbon monoxide (CO) emissions
• Up to 12% reduction in nitrogen oxide (NO_x) emissions
• Improved availability with no manual tuning or associated downtime.

By deploying AI-enabled tuning software in a supervisory control system fully bounded by control system safety-critical programming, ML can be used to safely determine the ideal flame temperatures and fuel splits continually and autonomously for optimal combustion, considering critical variables such as ambient conditions and fuel quality change. By sensing changes in ambient temperature, gas fuel properties and degradation, real-time adjustments can be sent to the turbine controls in seconds to deliver cleaner, more efficient and reliable operations. Another benefit of letting software do the tuning is that it allows experts to be deployed to address more critical actions.

Optimizing dispatch. Once a gas turbine has been digitized and enabled with new operating modes, digital technology can provide additional value by optimizing the dispatch of the plant and gas turbines. Many gas turbines are used for cogeneration in a power utility island of a processing facility. Meeting flexible and sometimes conflicting thermal and electrical demands is needed in such applications.

Plant operators have traditionally lacked comprehensive, timely and accurate data and tools that provide a single integrated source of truth to make sense of it all. Only with a complete picture of a plant’s operations, maintenance and actual capability, coupled with market and environmental conditions, is it possible to make decisions about dispatch that maximize revenues while reducing fuel and maintenance costs.

This is where digitization comes in. Software can provide the information and analytics necessary to operate and dispatch a plant and gas turbine in a way that meets today’s complex and continuously evolving market dynamics most efficiently. For example, AI-enabled software can reduce dispatch plan uncertainty with accurate capacity predictions (power and steam) and heat rate for the gas turbines and other supplementary power assets in the plant, such as duct burners, boilers and inlet conditioning. When coupled with a unit commitment optimizer using advanced numerical methods that can manage the wide range of constraints and inputs required, fuel and CO₂ savings of 0.5% or more may be achievable.

As weekly or daily plans change during operations due to a shift in demand or ambient condition, a digitized plant can respond almost instantly, without any manual handoffs, to optimize based on the latest inputs and constraints.

Maintain optimal performance. In addition to deploying new operating modes and optimizing dispatch, digital technology can be applied to maintain the optimal performance of the gas turbine and plant. Assets (i.e., gas turbines) degrade over time, and companies are always searching for ways to keep their assets healthy. To do that, companies must have visibility into the operation of that asset, not only to prevent unplanned and unwanted downtime, but to recover lost performance. This recovered degradation will reduce the cost of fuel, save emissions and potentially boost output. Operational and system efficiencies are critical to ensure business and environmental performance are paramount.

Industry professionals responsible for managing assets are faced with numerous challenges in designing cost-effective maintenance strategies for equipment. Intelligent approaches for identifying optimal processes and systems for managing assets combine data-driven modeling of known degradation mechanisms with field expertise in asset performance and plant operations.

Many companies use digital twins, digital representations of physical assets that apply advanced analytics and ML to reduce operational costs and risks. Digital twins are a key piece of the digital transformation puzzle and a great example of how software connects the dots. By embedding digital twins in fully automated software, engineering and plant personnel can achieve operating targets through benchmarking, analytics-based alerts and advisors across thermal performance and flexible operating modes, such as starts, ramping and minimum load.

Takeaway. Without digitizing a gas turbine or plant, ensuring the assets are operating as expected can be challenging. For example, a gas plant’s primary operating cost is fuel. Heat rate—a measurement of plant efficiency—is a moving target that changes with seasonal load profile, operating modes, ambient conditions and equipment health. Heat rate is not directly measurable in the plant, so without a digital twin to benchmark performance against, it can be unclear whether a change in heat rate is attributable to a change in operating conditions or a change in equipment health and degradation. With clarity of the source and the magnitude of the change, the most efficient use of resources can be deployed to achieve the most significant impact on recoverable degradation and ensure optimal performance over time.

Automating more operations creates a more reliable and safe plant. To improve profitability and reliability while lowering operation and maintenance costs, plant operators must evolve and adapt. Tapping digital tools that enhance flexibility, visibility and analytics for optimal operation is one readily achievable way to do that. GP