In a combined cycle power plant (CCPP), the overall performance is usually parametrized in terms of the efficiency (heat rate), and power output. These values are usually easily calculated when there is access to the necessary data. Still, the calculated efficiency and output of a CCPP will hardly ever be the same two times. This is because there are many ever-changing conditions that affect the efficiency and output of the plant.
In the short term case, the performance is dominantly affected by changes in atmospheric conditions. In general, performance tends to be better during night and morning periods when ambient air temperature tends to be lower, and worse on midday and afternoon when ambient air temperatures are higher. In the long term case, performance tends to decrease due to the effects of component degradation. This could be caused by gas turbine compressor fouling, gas turbine backpressure increase due to HRSG flue gas path fouling, dirty air filters, mechanical degradation of equipment such as pumps and generators, increased tolerances due to friction and erosion, etcetera.
One can see that there are very many factors that affect the performance of a plant, and a question that comes out of this is: Which are the main factors that affect performance, and by how much do they affect the performance? Not surprisingly, this is a very difficult question to answer since the effects of all these factors aggregate and their individual contributions to the efficiency and output of the plant cannot be singled out.
TGPS makes use of power plant modelling software for detailed and precise analysis of CCPP performance. Within the capacities of this approach is the prediction of performance change due to variations in any of thousands of parameters. For example, the performance of a plant can be accurately predicted under different ambient conditions, or on operation with fouled components.
A case study for a modern combined cycle power plant with a 2×1 configuration, triple pressure reheat, is presented here for demonstration. The plant has been modeled with the main design criteria shown in Table 1 below.
Using these design conditions as a starting point, the effect that a change of several individual parameters has on the efficiency and output of the plant can be predicted. The results for some of the most important parameters are shown below in Table 2.
These numbers are reasonable values in general situations, and can be used to roughly estimate the effect that a change in one variable may have on the overall performance. Still, one should keep in mind that no two power plants are the same, and therefore may not respond in the same way for all cases.
Another consideration is that the variations are not necessarily linear throughout the entire operating envelope. For example, the change in efficiency or output due to a 5°C ambient air temperature increase may not necessarily be the same if the initial ambient temperature is 15°C or 20°C.
To help our customers understand and predict the performance of their plant, TGPS uses state of the art modelling tools to create performance correction curves that encompass the entire operational envelope. Our team also runs “what if” analyses to predict the performance after a major unit uprate. This allows our customers to confidently take financial decisions based on quality prediction data.