Optimization strategies for improving combined-cycle performance

Ten years ago, or so, in most areas of the country it didn’t much matter how long it took to start up a steam turbine. Most of those units were in baseload service, or nearly so, with fewer than about a dozen starts annually. Transitioning to the new world of competitive generation and must-take renewables, and their demands for daily start/stop, fast ramp, and other operating capabilities for which most steamers were not designed, has not been easy.

Attend meetings of the Steam Turbine Users Group and you’ll see first-hand what your industry colleagues are doing to remain competitive. Control-system upgrades that include both automated starting and shutdown, and heating blankets, for example, have eliminated cold starts at many plants and reduced start times by as much as 50% in some cases, more in others. Consider attending the next STUG meeting (Phoenix, August 28-31) to learn more.

Attendance at meetings of the user group supporting your plant’s steam-turbine (ST) and balance-of-plant (BOP) control systems also is recommended: Refinements are ongoing and it’s important to know what’s worth the investment in time and money and what might not be.

At the most recent meeting of the Ovation Users Group, the editors sat down with engineers from conference host Emerson Automation Solutions to understand better how they help turbine owner/operators build more flexibility into their operations and improve plant performance to competitively and profitably satisfy changing load demand and cycling requirements.

The company’s extensive BOP experience, they said, shows that for power blocks experiencing heavy cycling, it’s critical to look at the complete operational cycle from shutdown back through startup to drive maximum performance. Understanding the latest controls methodologies for applying targeted automation and advanced control strategies can help sites achieve quantifiable and sustainable combined-cycle efficiency improvements.

The first step in this process requires the site to understand the plant’s current operating performance, relative to the fleet, to determine if and where there are opportunities for improvement. Developing and leveraging a “matrixed database” of the combined-cycle sites in the US to establish the baseline performance against which all sites with equivalent equipment can be measured provides important insight into the world of the frequent startup and shutdown process. This can be done in several ways.

One method involves collecting relevant historical operating data from the DCS or other historian and then manually calculating key performance metrics—if historian data are available and dead bands are sufficient—such as the fuel burned, start time expended, or emissions generated to complete a specific segment of an operation or process.

This information helps answer questions like these, faced daily by owner/operators:

      • What is the optimum shutdown load path I can use to plan tomorrow’s unit release or are there steps I can take to ensure my restart tomorrow will be hot based on my projected release time?

      • How much fuel or time does it take to develop floor pressure in the drum and how much NOx was emitted during that time?

      • What are those same values measured from gas-turbine (GT) start to synchronization?

Given ongoing O&M pressures and the limited resources of most power generators, a better option might be to have the control-system vendor write logic directly into the DCS that automatically calculates and reports on critical startup efficiency parameters. The raw data are there, it’s just a matter of extracting them in a meaningful way. Trying to replicate these data at the corporate historian level often results in some loss of integrity because of data compression and archiving techniques. This effort requires a highly structured process and close collaboration between the DCS vendor and the site.

DCS-integrated dynamic performance metrics serve to benchmark current power block performance and support evaluation of opportunities for improvements. Additionally, they are later used to track and document actual improvements as the optimization project progresses.

Data collected then are used to develop accurate models of the complete operational cycle, from the beginning of shutdown back through startup. The development of these process models provides the most accurate picture of the dynamic process capabilities and allows for the mathematical solution of optimal loading paths.

Through this process, the Emerson engineers said, they have found that effectively managing the process energy state on shutdown can have a significant impact on the fuel necessary to restart the process. Achieving this demands coordination among all major control areas such as heat-recovery steam generator (HRSG), BOP, ST, and GTs.

Once the optimized startup and shutdown processes are validated (and statistically significant variables identified) using the developed models, the next step is to focus on minimizing variability through increased task automation to reduce dependency on personnel to perform “routine operations.”

This typically includes modifying start times and loads, automating load control, coordinating loading of GTs and ST, and subsequently reducing thermal stress (through predictive temperature control) in the HRSGs and steam turbine/generator. Using advanced control and automation strategies (model-based and predictive technologies) that holistically control the site’s mass energy balance will minimize energy losses and maintain the process within engineering constraints.

There is no silver bullet for improving combined-cycle plant performance, and while sites are the experts on their process, the Emerson team encourages power generators to consider the multi-discipline approach available from industry experts knowledgeable about optimization. Successful vendors adhere to a highly structured process to identify opportunities for improvement, the participants said, and then select targeted automation and advanced control applications. Implementing the optimal combination of these tools can provide significant benefits—including improved startup time, reduced emissions, improved unit stability, and increased ramp rate—all while justifying the project financially based on reduced fuel consumption and fewer trips.

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