This case study highlights how Flownex helped detect a fault in a power plant’s Draught Group, improving generation load by 5% after correction. By comparing the Flownex model with plant measurements, abnormal readings were identified, prompting an investigation that revealed a thermocouple failure in an air heater, causing a 20.1 MW loss. The early detection, combining Flownex data with plant measurements, led to a positive financial impact. |
CHALLENGE
Faulty system operation is a major factor that results in significant generation losses. The air heater is one system that recovers waste heat and increases the performance of the power station, thus making it one of the major components that contribute to the amount of power generated. It requires the proper operation and maintenance of individual systems and the plant as a whole to ensure the ability and availability of plants to reliability and safely generate power at a maximum. This case study will focus on the draught group of a power plant and show the impact of a faulty air heater operation on the generated power.
BENEFITS
Combining on-site measurements with expected results from a model such as Flownex assists with the early detection of faults and abnormal process behaviour in plants. Early detection offers the ability to act fast and recover power generation losses. This, together with increased system performance as a result of proper maintenance and operation, offers the benefit of increased power generation, which inherently leads to minimized operation expenditure and increased capital income for the power plant.
SOLUTION
A power plant Draught Group network was developed in Flownex. For comparison, plant data was obtained from flow measurements taken at the induced draught (ID) fan inlet. Abnormalities in the measurements triggered an investigation of the performance of upstream systems. In Flownex, the operations of upstream components were varied until the same results as the plant measurements were obtained. In doing this, Flownex provided a tool that enabled the identification of the component that caused the problem. In short, combining the measurements with the Flownex model results narrowed down the under-performing system that gave rise to the root cause. In this case, it was a failure in the operation of an air heater.
INTRODUCTION
Combining on-site measurements with expected results from a model such as Flownex assist with the early detection of faults and abnormal process behaviour in plants. The purpose of this case study is to communicate a case where Flownex served in the detection of a fault that resulted in an improvement of 5% in the generation load of a power plant after correcting the fault. This case focuses on the Draught Group of a power plant that was developed in Flownex.
CASE STUDY
As mentioned, in this case study, a network of the Draught Group of a power plant is developed in Flownex. Figure 1 shows the schematic representation of the draught group.
Flownex results were compared to plant data obtained from flow measurements taken during the performance and testing procedure to obtain the mass flow rate through the ID fan. Differences between the Flownex results and the plant measurements were detected, which triggered an investigation of the performance of upstream systems. The differences included a high temperature reading at the AH outlet and ID fan inlet. Looking at the temperature reading downstream of the air heater on the combustion air side, it was found that the thermocouple measurement at the boiler exit (AH inlet) indicated zero, which is not possible. Figure 2 shows the historian plant data which encapsulate the behaviour and will be further explained below.
The graph shown in Figure 2 has two occurrences to it. These occurrences are distinguished by ‘A’ and ‘B’. The air heater gas inlet temperature thermocouple indicated in orange has failed which resulted in the opening of the air heater bypass valve on the air side, but the opening of the bypass valve was not immediately realised. Occurrence ‘A’ shows the readings with the bypass valve open. It was during this time that the plant measurements did not correspond to the Flownex model. The air heater gas outlet temperature was too high and the air outlet temperature too low. After considering different possibilities, it was postulated that the bypass valve was open, and the plant operator was notified thereof. The operator confirmed that it was indeed the case and responded by closing the valve.
Occurrence ‘B’ is what happened subsequent to the closure of the bypass valve. The air heater gas outlet temperature started to decrease and the air outlet temperature increased. This increased the efficiency of the plant and improved the plant generation load (indicated by the purple line). The generation load increased by 20.1 MW which is a noticeable 5% increase in the load.
SUMMERY
The purpose of this case study is to communicate a case where Flownex served in the detection of a fault that cost the plant a significant amount of power. It was a faulty operation due to a thermocouple that had failed, which resulted in the opening of the air heater bypass valve. With the assistance of the draught group network developed in Flownex, the fault was detected and the bypass valve was closed.
It is thus clear that combining on-site plant measurements with expected results from a model such as Flownex permits the early detection of faults and abnormal process behaviour in plants. There is no doubt that the benefit of recovering power generation losses was found in increased power generation load, which inherently leads to increased capital income for the power plant.