Gottfried Adam
Power Generation Group, Siemens AG, Mülheim/Ruhr, Germany

Dr. Hans-Gerd Brummel
Siemens-Westinghouse Power Corp., Orlando, USA


Figure 1. Faults in the turbines can be located or prevented to reduce down times and maintenance costs
Click here to enlarge image

Increasingly stiff competition in the energy markets is forcing power plant operators to reduce their operating costs while also maintaining, or even increasing, plant availability and reliability. The only way to achieve this is by optimizing power plant operations in terms of technology, operating economy and organization. Valuable assistance is available in the form of the Remote Diagnostics and Teleservice System through which operators of combined cycle power plants can access the technical expertise of Siemens Power Generation (PG).

The Remote Expert Centre (REC) provides the link between plant-side distributed data acquisition and evaluation processes and the REC’s own experts through a worldwide network. These experts can access analytical tools and rule-based diagnostic procedures, and can communicate with external specialists via the internet.

The REC sector from the Remote Diagnostics and Teleservice System supports plant operators with the optimization of their operations and business management processes through:

  • Technical process analysis: Thermodynamic process optimization, status analysis and diagnostics, fault and damage prevention
  • Tools for optimizing cost-intensive and sensitive processes: Planning of preventive and corrective maintenance procedures, spares inventory, generation schedules, condition-based maintenance
  • Cost tracking: Controlling, cost management, and accounting.

The REC system is still under development, but in its initial stage it will mainly focus on the areas covered by the “technical process analysis”. The other areas will be added during subsequent development stages.

REC pilot projects are currently underway in Erlangen, Germany and Orlando, USA, and the production version is scheduled for completion toward the middle of 2002.

Acquisition and conditioning

Data from any of the power plant’s instrumentation and control systems can be accessed through the plant-side monitoring and analysis system, WIN_TS. It is therefore possible to standardize all down-stream functions that are essential for the qualified operation of a remote diagnostics system. These functions include archiving, visualization, analyses, alarms and data transmission.

The software contains task-specific modules whose functions include simulation of thermodynamic combined cycle processes – gas turbine, steam turbine, water/steam cycle, calculation of component fatigue in thick-walled steam turbine components, documentation of operating conditions, performance of on-line analyses with an early warning function for critical process conditions, and data collection for specific process variables with a high time resolution.

Evaluation of data

The central server in the REC receives, stores, manages and analyzes all the data that the combined cycle plant logs into the system. It performs automatic analyses and diagnostic functions, and provides REC personnel with qualified software tools for manual evaluations. The server also handles administrative tasks such as documentation, communication, cost tracking and customer administration.

Any data that is transferred is received in the database of the central server software, and is assigned to a system or component and archived. A special mail server notifies software-definable user groups according to data priority and origin, and provides information on fault symptoms. Immediately after archiving, a selected series of measured values are automatically checked for anomalies using a powerful analyzer tool.

Typical applications include mathematical analyzers which provide automatic evaluations of turbine outlet temperature distribution and transient response, calculation and comparative monitoring of performance data and other normal relations. These automatic checks free the service experts in the REC from much of their routine work. This analysis software can also be used in the service centre to visualize, combine, assign and condition measurement series using a large number of mathematical functions.

Another important tool provided by the central server is a rule-based diagnostics programme which can diagnose incipient performance anomalies in technical systems.

Plant optimization

The Remote Diagnostic and Teleservice System provides tools which can provide precise on-line and analyses of thermodynamic processes – the factors leading to trips and failed starts and other technical faults. As part of this process the system learns to limit or avoid such incidents altogether in the future.


Figure 2. Power plants operators have access to Siemens PG expertise
Click here to enlarge image

The REC database offers a wealth of user-friendly features for analyzing stored information relating to trips, failed starts and other faults such as frequency distributions of events and downtimes, weak-point analyses, comparisons with general fleet performance, etc. Event analyses are supported by incident review logs (IRLs) which supply specific information on event causes (pre-event history) and successful counter-measures (post-event history) in the form of measured value profiles and binary signals.

It is possible to supply this fault-specific information in such a compressed form thanks to variable, trip-signal-related protocol components, which are closely linked to the particular trip signal both technically and physically, and can therefore speed up the detection of fault causes in the service centre. Incident review logs can be used for all detectable events – including faults, malfunctions, limit violations – and are stored in the REC database.

The tools used for thermodynamic optimization of the gas and steam turbine cycle are cycle simulation programmes which are installed in the local WIN_TS analysis systems. These programmes supply a wealth of additional information in the form of precise mathematical models of running processes. Such information is absolutely indispensable for qualified optimization processes with results that can be transferred to practical applications.

Automated, condition-related forecasting of in-service maintenance and cleaning operations – e.g. air and oil filter replacement, compressor washing – is also possible, enabling the power plant’s manpower and material resources to be optimized.

Condition diagnosis

Diagnostic systems are supposed to evaluate how far complex processes converge with undesirable conditions. In addition to powerful analysis tools these systems require a technological knowledge base which is filed in the REC server in the form of linked control records relating to specific components.

In practice, individually assigned control records and configuration files are loaded automatically on receipt of the data record relating to a gas turbine, for example. Pre-defined standard diagnostic procedures covering the entire time range of the received data record are then run, giving the experts in the service centre a rapid overview of the gas turbine’s process status. If the system diagnoses any process anomalies, the REC experts have access to additional analysis tools or can intervene on-line to investigate the causes of the fault. They can then notify the personnel in charge in the power plant once the problem has been resolved.

Damage prevention

The local instrumentation and control (I&C) system is still the first port of call for fast, reliable fault and damage control. In addition, preventive methods and tools should be activated as far below the I&C trip thresholds as possible, thus fulfilling the function of a sensitive early warning system. This is achieved with the help of trend analyses, limit value statistics and standardized relations.

When an extrapolation function has exceeded a pre-defined threshold, or when a time profile being analyzed has exceeded a maximum rate of change, more detailed and broader based technological and physical analyses are performed and messages are issued.

The limit value statistics function analyzes the timing and frequencies of measured value violations of specified thresholds. An early indication of faults or prior damage to a component is obtained from the curve showing the weighted areas of chronological threshold violations. This method is applied wherever the correlations between damage cause and effect are non-linear.

A comparative evaluation of standardized relations requires suitable process variables to be combined in such a way that they either represent analytically reproducible results – e.g. energy balances – or lead to simple, i.e. reproducible correlations based on a component’s operating mode. For instance, electric terminal output represented as a function of thermal energy input must produce a virtually linear correlation. While a pressure drop across the fuel oil control valve as a function of fuel oil mass flow should be represented as a root mean square function.

Any change in the parameters of such correlations over the plant’s service life despite comparable operating conditions indicates an equivalent change in the technical condition of the particular component.

An ideal solution

Power plant operators are recognizing the ever growing role of selectively generated and practically implemented information within the plant process, and its value in technical, economic and organizational terms.

In the future the process of generating and evaluating information will have to be transferred to competent service providers because cost-effective solutions for such complex tasks require specialist tools and knowledge.

The development of a closed information circuit between customers and manufacturers is an ideal solution because it allows for a targeted combination of specific know-how and experience from both partners. The REC information system described here enables appropriate structures to be implemented and allows for a pioneering approach to the resource information in the field of fossil-based power plant technology.

null