Josef Petek, VTU Energy GmbH, Austria
According to a study by the German market research company trend:research, more than 50 per cent of the new power plants to be built in Europe until 2030 à‚— or in absolute numbers about 98 GW of a total of 185 GW in plant capacity à‚— will be fuelled with natural gas.
Although recent turbulences in the gas supply to Europe may have some impact on this projection, gas turbine based combined-cycle power plants look set to remain one of the world’s most cost-effective options to generate electric power over the next few decades. Thus, engineers will continue to look into developing new plant concepts and optimizing performance and operational flexibility of combined-cycle power plants.
Figure 1: General data for a specific GT model and library of gas turbine models contained in the VTU Energy Gas Turbine Library.
One of the key elements to such analysis is the correct representation of gas turbine performance, since gas turbine output and heat rate, as well as exhaust gas flow and temperature (serving as the energy input to the subsequent steam cycle), are the main constituents to the overall plant performance.
It is important to understand that because of the nature of the gas turbine process, ambient conditions have a significant impact on gas turbine performance. Since the inlet air volumetric flow (as a function of ambient temperature and pressure, and inlet filter pressure drop) affects the compressor mass flow and power demand, and because the back pressure to the turbine (resulting from ambient pressure and HRSG pressure drop) determines the shaft power produced to drive the compressor and the generator, gas turbine performance always has to be reported with the corresponding inlet and outlet conditions.
Further operating parameters that affect gas turbine performance are: inlet air humidity which impacts the compression process by changing the thermal properties of the inlet air; and the heating value of the fuel which determines the actual fuel and exhaust gas mass flow.
Part Load Operation
Part load operation of gas turbines adds even more complexity to the prediction of gas turbine performance. While in general the efficiency of the gas turbine decreases with decreasing load level because of the losses induced by the deviation from the design flow conditions, the control schedules implemented by equipment manufacturers in order to cope with material constraints (such as the temperature resistance of the blades or the root strength of the last turbine blade row) generate very specific part load behaviour for each individual gas turbine design.
The use of inlet guide vane (IGV) control to trade off gas turbine performance against overall combined-cycle performance has also become standard industry practice, so another layer of controls needs to be considered when modelling gas turbine part load operation.
Advanced combustion technology to reduce NOx emissions adds a further piece to the puzzle. Virtually every OEM has developed its own design for achieving desired NOx emissions levels à‚— through fuel-air premixing and sophisticated devices or control features to constrain the combustion process within tight reactant concentration and temperature limits. Several characteristics of gas turbine performance, such as turn down ratio or part load efficiency, are affected by these measures.
Figure 2: Comparison of exhaust temperature versus load for different heavy duty gas turbines
Figure 2 illustrates the differences in part load operation by comparing typical exhaust temperature versus load level characteristics for three different heavy duty gas turbines at 15 à‚ºC and 45 à‚ºC, respectively.
Figure 3: Exhaust temperature pattern over load for a GE aeroderivative gas turbine at temperatures between -15 and +30 à‚ºC with 5 à‚ºC increments.
Gas turbines that are derived from aircraft engines may contain even more complex part load control schedules, as can be seen in Figure 3. For such multi-shaft engines, a multitude of mechanisms, including IGV control, blow-off valves, and various burner configurations, interact in order to retain both material stress and emissions within allowed limits.
Gas Turbine ModeLling Approaches
Since the modelling of complex processes and equipment has proven to be a reliable and cost-effective engineering practice to design, monitor and improve turbomachinery practically, all gas turbine manufacturers apply in-house software to simulate and predict the performance of their equipment à‚— based on detailed physical models as well as fleet experience.
Because of the level of detail contained in the physical sub-models of these vendor programmes, such as compressor and turbine maps or the control schemes, these codes are considered trade secrets and are often kept confidential. Some manufacturers however, do provide access to web portals or customized performance estimation tools as they respond to the need of engineering companies and gas turbine users to simulate the performance of their products.
But when it comes to modelling the behaviour of the overall plant, the above mentioned vendor programmes lack one significant capability: they are not designed to include the remaining plant equipment such as a HRSG, steam turbine or condenser, nor can they be linked to commercial heat balance software. This means that the engineer analyzing the performance of his plant concept would need to go back and forth between several software programmes to conduct design calculations or load scenario studies. Thus, it is highly desirable to have a gas turbine model that is fully integrated into heat balance software.
One approach to take is the reverse engineering of measured or published performance in order to develop detailed physical models to be implemented in components of the heat balance programme. Physical models are well- suited to capture the ‘natural influences’ of changes in ambient conditions, but in order to adjust for the various control schemes and internal details of individual gas turbine models, they require a level of insight into these technical details that often conflict with the right of the OEM to protect its know-how and intellectual property. Any attempt to adjust generic mechanistic models to performance characteristics, will, on the other hand, be prone to failure because of the many unknown process parameters that cannot be measured or received through vendor information.
Gas Turbine Library
VTU Energy therefore took a data driven approach to develop its Gas Turbine Library that allows the accurate prediction of gas turbine performance à‚— based on vendor information or measured performance. VTU Energy’s approach was derived from gas turbine performance test procedures, such as ISO 2314 and ASME PTC 22.
When evaluating equipment performance based on guaranteed data valid at specific reference conditions, respective corrections have to be applied to adjust the guarantees to test conditions. Therefore, all gas turbine vendors can supply such sets of correction curves for individual parameters, which are typically generated using the type of in-house simulation software mentioned above.
For the heat balance calculations using the Gas Turbine Library a similar process is applied. At a defined set of reference conditions, the base rating provides the values for a gas turbine’s power output, exhaust gas flow, exhaust gas temperature and à‚— if applicable à‚— the cooling duty rejected from the gas turbine under these reference conditions, as well as the water or steam injection flow applied.
Figure 1 shows a sample set of this ‘general data’ in the user interface of the Gas Turbine Library. The docking window at the right hand side contains the library of gas turbine models that can be sorted or searched using user-defined criteria. Double-clicking on a selected row in this table will upload the respective data set of rating information and correction curves into the gas turbine model.
One important criterion in the design of this software module was to provide maximum transparency on the type of corrections applied for the specific gas turbine model, and on the quality of the data contained in the curve sets. With a potential total of 53 individual correction curves (some of them two-dimensional to account for cross-effects) the user may actually be facing thousands of data points to describe the entire operating range of the engine.
Figure 4: Matrix of correction curves and curve plot view.
The matrix shown in the left side of the sample screenshot in Figure 4 indicates active corrections with a green background colour. When selecting a specific correction curve such as [water] injection flow versus [inlet air relative] humidity, as shown in this example, the data can be viewed as a curve plot or in tabular format. It is important to note that the library allows the user to modify existing data sets (e.g. for updating base rating according to new vendor information) or to add their own data sets for project-specific gas turbine performance data.
When analyzing the calculation results, the engineer can similarly trace back to the correction factors and offsets of the individual corrections. This approach, which is in accordance with usual performance test procedures, has shown to be of great help to the engineering users because it quickly identifies the operating parameters that have the highest impact on certain performance characteristics under current conditions.
Developing/Optimizing Combined-Cycle Concepts
VTU Energy’s Gas Turbine Library can be acquired as a module for the EBSILON Professional heat balance software, developed by Evonik Energy Services GmbH, (Essen, Germany).
Through an individual model component, the gas turbine performance characteristics can be integrated with a detailed plant model, and in-depth thermodynamic analysis can be performed benefiting from the features of EBSILON Professional. These features include:
- individual equipment characteristics in design and off-design mode
- full record of all gas, water/steam and electrical flows of the plant
- flexibility in equipment arrangement, plant configuration and mix of technologies
- a powerful, fast and reliable equation-based solver
- open architecture to include user-defined models for new technology or vendor data
- a state-of-the art graphical user interface and a wide variety of output options in graphical and tabular formats
- an interface with Microsoft Office Excel.
Thus, the engineer can link detailed gas turbine performance models with any plant arrangement including, but not limited to, power generation, cogeneration and district heat, as well as multi-purpose plants, such as combined power generation and seawater desalination. Through its long history in the coal and nuclear industry, EBSILON Professional also allows the mixing of gas turbine plants with conventional or nuclear steam plants. Furthermore, because of its open and flexible architecture the thermodynamic analysis can also be extended to new technologies such as concentrated solar power or fuel cells.
With correct representation of gas turbine performance over the entire range of operating and load conditions, the design and evaluation of new plant concepts can be performed with accuracy and reliability because the plant concept can be tested against a broad range of operating scenarios, including a multitude of design alternatives.
Benefitting Gas Turbine Users and Vendors
Both gas turbine users and vendors can benefit from integrating detailed performance data into professional engineering tools. Supplying engineers with gas turbine performance data will pay back to the vendors because new plant concepts and improved overall plant efficiencies will grow the market and competitiveness of their products.
The current release of VTU Energy’s Gas Turbine Library, which will soon be shipped to more than 120 users of EBSILON Professional worldwide, includes 50 models of three major gas turbine vendors, namely Alstom, Siemens and GE.
VTU Energy will continue to work with these parties and contact other vendors to grow the Gas Turbine Library to make it a valuable and living source for gas turbine performance information, so engineers across the globe can make use of reliable and first-hand data to analyze and improve the design of combined-cycle plants.