STEAG KETEK IT, November 2006, Page 1
Discover optimization potentials –
maximizing efficiency of power plant operation
with state of the art energy management systems
Dr. Christian Herr
STEAG KETEK IT GmbH
STEAG KETEK IT, November 2006, Page 2
STEAG Power Plant Sites (8.800 MW in total)
Based on decades of experience…
… treading new paths in the energy business.
Herne
950 MW
Walsum
600 MW
Lünen
500 MW
Voerde
2,222 MW
Bergkamen
747 MW
Bexbach
773 MW
Weiher
707 MW
Fenne
502 MW
Termopaipa
165 MW
1999
Iskenderun
1,320 MW
2003
Köln-Godorf
211 MW
2004
Mindanao
232 MW.
COD 2006
Walsum
750 MW
COD 2010
Herne
750 MW
COD 2011
Leuna
158 MW
1996
COD = commercial operation date
STEAG KETEK IT, November 2006, Page 3
STEAG KETEK IT products monitor, control and optimize the essential,
techno-commercial relationships in the power generation process
SR::EPOS
EbsilonProfessional
SR2
■ Quality management of the operational measuring equipment
■ Evaluation of the process component performance
■ Optimization of the plant operation mode
■ Information extraction for state-related maintenance
SR1
STEAG KETEK IT, November 2006, Page 4
■ Long-term storage of measured and computed values in time-oriented archives
■ Versatile trend displays featuring drag and drop from values in the process screens provide easy data analysis and evaluation
■ Excel-Add-In and HTML-List generator allow the generation of extensive reporting systems
SR::x - central data management and “state-of-the-art” visualization
STEAG KETEK IT, November 2006, Page 5
EBSILONProfessional - A powerful tool for power plant cycle calculation
■ Software tool for modeling, simulating and validating power plants
■ Continuous development since 1990
■ Over hundred companies worldwide are using EBSILONProfessional for offline planning tasks and for online performance monitoring and optimization
■ Offline and online what-if calculationscan be easily performed with this tool
■ Extensive configuration options at the user´sdisposal in a graphical user interface (GUI)(“build your own power plant modelcomponent by component”)
■ Comprehensive component library for modeling all kinds of power plant processes
STEAG KETEK IT, November 2006, Page 6
EBSILONProfessional - Entire plant modeling
- Mapping of 85 units in India based on GTZ project
STEAG KETEK IT, November 2006, Page 7
Neural networks can quickly solve complex optimization tasks based on non-linear modeling
Training of neural
networks
Calculation of global
optimum
The combination of thermodynamic simulation tools, neural networks and heuristic optimization algorithms represent a reliable concept for complex optimization tasks for power plant operation
EBSILONProfessional - Multi unit optimization
STEAG KETEK IT, November 2006, Page 8
SR::EPOS - the SR product for performance monitoring and unit optimization
■ Monitors periodically (every 5 mins) the power plant process technically and economically
■ Evaluates plant components online and provides planning data for state-related maintenance
■ Suggests optimum modes of operation from economic and ecological aspects
■ Evaluates the impact of different, changing environmental conditions
■ Optimizes the units operation and enhances its efficiency – typically by 0.1-0.3%, up to 1%
Based on EBSILONProfessional
STEAG KETEK IT, November 2006, Page 9
SR::EPOS - SIMHADRI Power Plant + 14 additional UNITS (NTPC)- BHEL – Cooperation on PADO/BPOS
Optimization of
cleaning of air
heaters and ESPs,
evaluation of fan
operation
Optimization of
turbine cycle,
condenser, cold
end and pre-
heating
Boiler mapping,
optimization of
boiler operation
including soot
blowing, air supply,
burner tilt, coal
mills, etc.
What-if calculation,
metal temperature calculation,
set point optimization
STEAG KETEK IT, November 2006, Page 10
SR::EPOS - Cost of condenser fouling
162T€ total losses
due to condenser
fouling
STEAG KETEK IT, November 2006, Page 11
■ Controlled by costs or other criteria the optimum points in time for activating the individual blower levels are calculated
■ Closed-Loop application possible if desired
■ Application of fuzzy technology
SR::EPOS::BCM - the SR product
for optimizing the soot blowing
Color changes indicate heater efficiency
Soot blowing
recommendations
Actual heater
efficiencies
Allowed minimal
efficiency values
STEAG KETEK IT, November 2006, Page 12
Heating value
Ash
S, Fe
K, Ca
Al, Si
Na
Detection and forecast of
fouling behavior; self
learning knowledge base
Steam generator
Coal
Online analysis
of coal
Intelligent
soot
blowing
sequenceCalculation
of heat
surface
fouling
SR::EPOS - Online coal analysis (in cooperation with RWE)
STEAG KETEK IT, November 2006, Page 13
SR::EPOS - Data preparation / data reconciliation
Raw measurement value5min. average value from main system
Neural plausibility checkSubstitute values from neural networks
Range checkSubstitute value from range check
Check by data reconciliationSubstitute value from data reconciliation
SR-ValueInput value for SR::EPOS-calculation
Σ ( x - u) ² /σσσσ² = Min
x = Measured valueu = validated value
σσσσ = standard deviation
Input data set 2
Output data set
Model output
Forecast
Input data set 1Neural Network
STEAG KETEK IT, November 2006, Page 14
SR::EPOS - Online realization of statistical process control based on data
reconciliation reduces the noise in key figures derived from site measurements
� Pre-heaters with small TTD are especially sensitive to measurement errors
� The online application of data reconciliation points out the continuous degradation of the components
STEAG KETEK IT, November 2006, Page 15
Objectives of CO2 monitoring and benchmarking at STEAG based on data reconciliation
� Fleet wide real time tracking of CO2 emissions
� Data reconciliation of coal consumption data
� Consistent determination of characteristic plant data for the STEAG fleet
SR::EMUB - Emission Monitoring & Unit Benchmarking
SR::x as
central platform
for optimization
results
Provision of
current, validated
figures of all
STEAG power
plant units:
- Operation mode/
load case
- Characteristics
- Efficiencies
- Coal consumption
- CO2-emissions
