operational flexibility for steam turbines based on
TRANSCRIPT
- 1 - © Siemens AG 2006. All rights reserved.
Power Gen Europe 2006 Cologne, Ref. No. 306 2006-03-07
Operational Flexibility for Steam Turbines based on Service Contracts
with Diagnostics Tools
Michael Killich,
Siemens Power Generation, Germany
Power Gen Europe 2006
Cologne,
0 Abstract
The world wide liberalization of the electricity market forced the utilities to deliver electrical
energy with high efficiency and at a competitive price. To achieve these demands cost
reduction and technical innovation programs were implemented in power generation process.
Furthermore according to the actual market conditions a higher flexibility in operating and
maintaining the plants is necessary. Older base load units have to cycle, which creates higher
stresses to the materials. Planned overhauls will be postponed to avoid uneconomic standstill
time. Uprating of power output of existing units to the absolute design limits is often used as
an additional option to catch maximum profit during high price periods. In parallel with all
these market demands the operation of the complete power plant with the steam turbine set
and generator as key components need to be enhanced by higher reliability, availability and
utilization.
- 2 - © Siemens AG 2006. All rights reserved.
The traditional way of handling the maintenance business is not aligned to these market
requirements, because it is based on transactional and price oriented business models. The
contractual parties are focusing unilateral objectives, which normally are different from each
other, and trying to reach them separately. As a result, a lot of resources are necessary for the
awarding process. Orders has to be prepared and evaluated for different work scopes and the
packages has to be negotiated by the parties. All this leads to high transactional costs and
long, inflexible outage planning processes which are a handicap for the operator to remain or
become competitive and successful.
One way to achieve the objective of a flexible and short termed outage planning and to reduce
the transactional costs is to establish Strategic Alliances between the utilities on the one side
and the manufacturers on the other. These tailor made contracts should be the basis to leave
the transactional business behind and to enter value based and success depending business
models or contracts. Critical factors for the success were the alignment of the objectives and
the definition of benchmark matrices (Score Cards) to measure the level of success. The range
of this Strategic Alliances can vary from simple parts availability programs or Operating Plant
Service Agreements (OPSA) to Long Term Programs (LTP) with risk sharing elements and
the value based payment mentioned above.
In addition these aims could be achieved more efficiently by using intelligent condition
monitoring strategies for the power plant and its key components using a supervisory on-line
diagnostic system. The use of comprehensive on-line data acquisition, internet data
transmission systems, task-related data analysis and an expert background knowledge base at
newly founded Remote Diagnostic Center enable detailed diagnosis of the actual plant
condition.
With human expert support and engineering solutions from the manufacturer together with the
knowledge based supervisory diagnostic system a long term condition based plant operation
with enhanced reliability and profitableness will be possible. This Power Diagnostic
enterprise promotes the client to
• make inspection decisions on turbo set components on a condition and risk based
maintenance strategy,
• better life time management under technical and commercial aspects,
- 3 - © Siemens AG 2006. All rights reserved.
• more smooth turbo set operation to avoid frequent overstressing the machine which will
result in life extension.
• Together with our Strategic Alliances Programs like LTPs risk sharing models and
extended warranties could be implemented.
Condition monitoring with the Power Diagnostic tool leads to effective live cycle asset
management.
- 4 - © Siemens AG 2006. All rights reserved.
1 Deregulation of the markets
Like in other regions of the world, the power generation market in the Asian-Pacific region
has in recent years been characterized by its orientation towards deregulation. The use of gas
turbines in simple-cycle and combined-cycle plant applications grew rapidly. But also the
mature fleet has to be operated more cost efficient. Market trends in the last years could be
summarized as follows:
Privatization & deregulation of global energy markets
Entering on Independent Power Producers (IPPs)
New market purchasing new and existing plants
Rising operational cost no longer a pass through to rate payers
Aging conventional steam units requiring modernization to remain competitive
Increasing stringent environmental requirements
Asset value optimization driving all customer decisions
The privatization and deregulation trend is an international movement, which has already
taken place in the American market. In Asia, Europe and Australia the movement strongly
depends on the different country markets and political strategies. For the year 2008 there will
be a market liberalization of 40% in the non-American markets. This trends leads to changes
in the behavior of power producers. Increasing competition has caused power plants to switch
from traditional time-based maintenance strategies to those based on a plant’s operating
condition. As deregulation becomes a reality for the power generation industry and as
competitive power production becomes standard operation procedure, the quality of power a
company produces becomes the measure of its success. This requires the utility, independent
power producer (IPP) and/or industrial power producers (IND) to bid power competitively at
current market rates. The power producer that operates at the lowest cost per kilowatt-hour
will thrive in this challenging environment.
In a regulated environment electricity prices are typically calculated using the average costs of
generation plus a recovery fee for the investment and a multiplier for the return of the
investment. In a deregulated market this costs are no longer a pass trough to the customer and
plant operation (the plant dispatch) depends on the marginal costs for the electricity
production (Figure 1). If the actual market price is lower than the marginal costs, the plant
cannot be operated in a cost-effective manner. A recovery of capital, return of investment and
- 5 - © Siemens AG 2006. All rights reserved.
recovery of sustaining costs is achieved only during periods with spot prices higher than the
marginal costs. Therefore the operating requirements can be summarized as follows:
Reliability and Availability is the Key
Maximum Flexibility needed for Cycling Operation
Reliable and Quick ‚Start Up‘ and ‚Shut Down‘ capabilities
Ability to effectively take advantage of the high price phases in the Market - „80% of
Annual Sales is earned during 20% of the time“
Optimize component life usage
Extension of the maintenance intervals
Adequate and proactive maintenance to reduce forced outage rate
Reduction of overhaul durations
Figure. 1a. (Simplified Dispatch Curve – Example taken from German electricity market)
Power GenerationPG O26
cumulated capacity
NPP
STPP (coal)
STPP (oil)
CCPP
GTPP
grid demand
€€ market price
marginal costs
Deregulation / Cost Reduction
Fig. 1a
- 6 - © Siemens AG 2006. All rights reserved.
Figure. 1b. (Simplified Dispatch Curve – Example taken from German electricity market)
Power GenerationPG O26
cumulated capacity
NPP
STPP (coal)
STPP (oil)
CCPP
GTPP
grid demand
Reduction of marginal costs
Competitive Advantage
Deregulation / Cost Reduction
Dispatch rate
100 %
50 %
0 %
Fig. 1b
The market situation and the different areas of competitive position can be abstracted in a
strategic gameboard shown in Figure 2. Power producers or power plants with high marginal
costs in power production and inflexible processes concerning operations and / or
maintenance are in a zone of competitive disadvantage (danger zone). Therefore it is of
outrageous importance to bring or keep your assets in such a position. Even for older plants
the reduction of transactional costs, the reduction of fuel costs (availability, efficiency) or the
reduction of spare parts in the warehouse could be key factors to enter this success area (lower
right). We see plants in this area only to be the successful ones in the long term.
- 7 - © Siemens AG 2006. All rights reserved.
Figure. 2. (Strategic Gameboard)
Power GenerationPG O26
Strategic Game Board
Competitive Advantage
Increasing Competition
Increasing Competition
Danger Zone
Marginal costs
Flexibility
high
low
highlow
Fig. 2
2. Traditional Maintenance Concepts Basis for all Strategic Alliances is the traditional maintenance business with its variety of
services from Technical Field Assistance (TFA) to Turn Key Outages. As shown in Figure 3
the Total Maintenance Service (TMS) concept could be implemented for all contracts or
business models. TMS is a cyclic planning process to make sure that all necessary personnel,
spare parts and tools are at site at the right time. This objective is been achieved by several
meetings with the customers for planning and checking purposes. The complete TMS process
is installed for Customers with alliances contracts in particular.
For high quality engineered components there are repair opportunities in our workshops all
over the world. In more and more cases it is possible to have an on site or even in-situ repair
using advanced on site tools.
- 8 - © Siemens AG 2006. All rights reserved.
A consolidated outage management is available for all turn key outages and strategic
alliances.
Figure. 3. (Traditional Maintenance Concepts)
Portfolio of Service Programs Power Generation 8PM O26 MarketingOctober 2003
Total Maintenance Services (TMS)
Technical Field Assistance (TFA)High Quality Engineered Components
Component Repairs
Consolidated Outage Management
Advanced Technology Specialty Inspection & On-site Repairs
Maintenance Contract (MC)Turn-key Inspections and Outages
Traditional Maintenance Concepts
Fig. 3
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3. Strategic Alliances Programs Strategic Alliances are linking advantages and work scopes of the traditional business to a
single long term maintenance contract. This process of integration is shown in Figure 4. The
result is an integrated solutions for deregulated markets where Siemens is more or less
responsible for all maintenance issues in the turbine island. The risk sharing level, the level of
goal alignment and the value based pricing is increasing from our Operating Plant Service
Agreement (OPSA) over the Long Term Programs (LTP) to Operation & Maintenance
(O&M). The OPSA agreement is designed for customers with own experiences and / or
capacities regarding maintenance issues who are interested in long term budgeting and new,
more competitive business models. These business models are the basis for online
diagnostics, up grades and condition based maintenance also. The OPSA contract is actually
the most preferred contract type for the turbo generator performance maintenance business,
but it is limited in its risk sharing level. Customers who are interested in value based risk
sharing models prefer the LTP contract. The interconnection between scope flexibility and
risk sharing level is shown in Figure 5.
Figure. 4. (Philosophy of Strategic Alliances -Contract Portfolio)
Power GenerationPG O26
Mut
ual B
enef
it
TMS
TFA
OPSALTP
O&M
TransactionalTransactional ExpandedScope / RiskExpanded
Scope / RiskPerformance
DrivenPerformance
Driven
MC
Alliances
Commitment
Contract Portfolio
Project ManagedMaintenance Contract
Operating PlantService Agreement
Total Maintenance Services
Long TermProgram
Operations &Maintenance
Technical Field Assistant
- 10 - © Siemens AG 2006. All rights reserved.
Fig. 4
Figure. 5. (Philosophy of Strategic Alliances)
Power GenerationPG O26
Transactional Performance driven
Individual Goals Mutual Benefit
Price Driven Risk Sharing
Turnkey Outage
OPSA
LTP / O&M
Fixe
d sc
ope
Flex
ible
sco
peDeregulation / Cost Reduction
Fig. 5 3.1 Availability Parts Program (APP) The scope of the APP program is defined as follows:
Perform unit configuration & interchangeability study
Parts modification to improve unit reliability
Provide outage parts as “kits”
Identification of critical spares
Parts Catalogue
Inventory Reduction Program
3.2 Operating Plant Service Agreement (OPSA) The scope of the OPSA program is defined as follows:
Same as APP with addition of …
Component repair and refurbishment
Turnkey inspections / outages / overhauls
Consolidated project management (optional) and back-office support
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Alignment to outage duration needs / goals
Performance of unit configuration & interchangeability study
Parts modification to improve unit reliability
Forced Outage Protection
The OPSA is more or less a master agreement to purchase exclusively from Siemens for 6-12
years. Based on the order values (per year) there is a certain discount level on field services
and spare parts. (see Figure 6)
Figure. 6. (Discount OPSA)
Power GenerationPG O26
Basic Discount
Discount Trends
Order Value
Dis
coun
t % Different contracts
Maximal Discount
Contract StructureDiscount Matrices
Ope
ratio
n Pl
ant S
ervi
ce A
gree
men
t(O
PSA
)
Fig. 6
3.3 Long Term Program (LTP) The scope of the OPSA program is defined as follows:
Same as APP & OPSA
Goal Alignment, plant assessment, mutual agreed Score Cards
Unit condition assessment
Determine Long Term Maintenance Requirements
- 12 - © Siemens AG 2006. All rights reserved.
Modernization & Refurbishment
(implementation of TMs “Technische Mitteilung”)
Performance based payment
Risk sharing models
Dedicated Program Manager
There are the following key roles in an LTP contract:
Executive Management
Contact partner at Siemens PG
Leads commitment for the process
Vision philosophy
Periodic review (Goals and objectives, Progress metrics)
Assure resource commitments
Strategic Alliance Core Team (Alliance Managers)
Facilitator / Coordinator / Catalyst
Full vertical & horizontal span
Identify initiatives & report performance
Implement corrective actions
Manage Alliance Process
Implementation Teams
Each group has unique functions and tasks that
contribute value to the LTP
The typical organization Structure of an LTP is shown in Figure 7.
- 13 - © Siemens AG 2006. All rights reserved.
Figure. 7. ( LTP Organization Structure)
Power GenerationPG O26
ExecutiveManagement
Strategic AllianceCore Team
(Implementation Teams)
LT StrategicPlanning:
Maintenance& Perf. Enhance
AlliancePerformance
Metrics
Outage Implementation
PerformanceEnhancement
Implementation
Unit / FleetPerformanceEvaluation
Long
Ter
m P
rogr
am (L
TP)
Customer
Organization StructureImplementation Teams
Fig. 7
As mentioned in chapter 3, the idea of a value based pricing and risk sharing is a key element
in an LTP contract. One possibility to achieve this is the implementation of Score Cards,
developed and mutually agreed upon, during the negotiation process by the contract partners.
This Score Cards should contain all important issues and results coming out of the agreed
work scope (critical to quality (CTQ) outputs). Depending on the degree of success, each
issue is evaluated and scored separately. Because the listed issues are not all of the same
importance typically, there is the possibility of a weighting factor. An example of such a
Score Card is shown in Figure 8.
The sum of all scored points in comparison with the maximal accessible number of points is
basis for the bonus / penalty calculation shown in Figure 9.
- 14 - © Siemens AG 2006. All rights reserved.
Figure. 8. (Example of a Score Card)
Power GenerationPG O26
1,0MTP*
1,0MTP*
1,0MTP*
0,5Occurrences of MWhr curtailments due to TG work by Contractor
0,5Any post-outage TG work performed by Contractor.
AWP*15
7,5
0WeightQuality / Reliability
0,4Actual Schedule/ Target Schedule
0,3Startup, in number of runs
0,3Key Milestones completed on time5
AWP*10
50WeightSchedule Compliance
0,6Other
0,4Record able Injuries per OSHA
AWP*52,5
0WeightSafety / Human Performance
AWP: Actual Weighted Points MTP: Maximum Total Points
Penalty Bonus
Financial AdvantageScore Card (Example)
Long
Ter
m P
rogr
am (L
TP)
EXAMPLE
Fig. 8 Figure. 9. ( Financial Advantage: Bonus / Penalty System)
Power GenerationPG O26
Target Price –5%
Performance weighted points
Max Target Price
Bonus/Penalty = Target Price x 5% x[2x (AWP / MTP)-1] AWP: Actual Weighted Points MTP: Maximum Total Points
Target Price
Penalty
Bonus
Financial AdvantageBonus / Penalty System
Long
Ter
m P
rogr
am (L
TP)
Fig 9.
- 15 - © Siemens AG 2006. All rights reserved.
3.4 Program Implementation Process The implementation process is shown in Figure 10. First of all the program objectives have to be defined and a plant assessment has to be performed in the case of a risk sharing model. The following list of project objectives should be basis for the negotiations:
Reliability and Availability Goals
Maximum Flexibility needed for Cycling Operation
Reliable and Quick ‚Start Up‘ and ‚Shut Down‘ capabilities
Optimize component life usage
Extend intervals between inspections
Predictive maintenance to reduce Forced Outage Rate
Reduced outage durations
Flexible outage schedules
The definition of the work scope and the contract structure are linked to the different program types defined in chapter 3.1 – 3.3. The contract structure could contain:
Organizational Structure
Execution Process
Identify Strength / Weakness (Customer/Siemens)
Task, Function, Process, Responsibility
Commercial Conditions
Master Terms and Conditions
Enhanced Guaranties
Share Risk
Definition of Condition Based Payment
- 16 - © Siemens AG 2006. All rights reserved.
Figure. 10. (Implementation Process)
Power Generation 17PM 026 MarketingNovember 2002
Program Implementation Process
Strategic Alliance Programs
Driven by Executive Steering Committee
Program Objectives
Definition of Work scope
Contract Structure
Execution, Monitoring, Measurement & Change
Fig. 10
After Execution and order implementation the results are monitored and analysed to improve
the process and the performance. This issue is handled by a dedicated program manager. Last
but not least the financial results are measured and are input to the implementation loop again
(Figure 11.).
- 17 - © Siemens AG 2006. All rights reserved.
Figure. 11 (Measurement – Improvement Loop)
Power Generation 22PM 026 MarketingNovember 2002
Managed by Program Manager
Alter Process as necessary
Measurement of Objective
Financial Goals Met
Program Objectives
Definition Of Work scope
ContractStructure
Execution, Monitoring, Measurement & Change
Strategic Alliance Programs
Fig. 11
- 18 - © Siemens AG 2006. All rights reserved.
4. Remote Diagnostics as Building Block for Optimized Plant Operation
Power DiagnosticsTM is a modular built system to monitor, analyze and diagnose the complete
turbine island. The advanced service product is a high sophisticated remote expert diagnostic
system which is the basis for condition based maintenance strategies and optimization of the
plant operations. The results of Power DiagnosticsTM can be recommendations for further
operations, repairs and/or modernization of customer’s equipment. Power DiagnosticsTM is
not limited to Siemens units but is applicable to all kind of steam turbines and generators.
The goal of Power DiagnosticsTM is to diagnose the operation of the turbine island for purpose
of early detection of abnormal operating conditions. Hardware failures, instrumentations
malfunctions may lead to abnormal conditions. Detection of these conditions results in
optimized operation, higher availability, and improved turbine island efficiency. This service
can benefit operations by mitigating running off nominal conditions. It also provides the
original manufacturers’ key information that can be used to further improve products and
services such as increases in hardware life and durability, mitigation of collateral equipment
damage through early detection, improvement in reliability, and optimization of maintenance
durations. Skilled OEM engineers and technicians, enabling them to make timely
recommendations to customers, who can be used to help assess future actions, will analyze
this information.
- 19 - © Siemens AG 2006. All rights reserved.
Figure. 12. (Diagnostics Basics , Monitoring, Analysis vs. Diagnostics)
Power GenerationPG O26
Terms and Definitions
Analysis
Operation
Data Logging
Signal Analysis
Data Base
Visualization
Monitoring
Operation
Limit Value Check
Data Logging
Signal Analysis
Alarm
Trip
Data Base
Visualization
Diagnostic
Operation
OnlineDiagnostics
Offline ExpertDiagnostics
Deviation fromNormal Behavior
Learning PhaseNormal Behavior
Data Measurement Data Compression
Data Processing Data Interpretation
Fig. 12
To reach the objective not only to monitor the different measured values but to implement a
real diagnostics system, a global network of high sophisticated experts is needed and the raw
data of the turbo generator, process factors and state variables have to be collected and have to
be correlated and analyzed. There is no software solution for this in depth diagnostics
available and will not be in near future. This data evaluation has to be done by engineers. But
the software is capable of learning the “normal behavior” of a machine or a system and to
detect deviations from this normal behavior. Therefore it is possible to set alarm and trip
thresholds and to create intelligent and event driven data management systems. The software
is operating more or less like a watchdog or a filter, to make sure human experts are dealing
with complex diagnostics issues only.
- 20 - © Siemens AG 2006. All rights reserved.
The differentiation between monitoring, analysis und diagnostics is shown in Figure 12 and
defined as follows:
Monitoring:
Simple stand-alone-monitoring-systems offer the possibility of visualization of all measured
values and a simple comparison against defined thresholds. A detailed knowledge to define
the alarm and/or trip level is needed even here. The System consists of:
Sensors (temperature, vibration, magnetic flux, data from I&C, a.s.o.)
Data processing System
Visualization Equipment (could be part of the I&C System)
Analysis:
The analysis system is based on the data coming out of the monitoring system and is
characterized by complex data calculation of interacting parameters. The software is capable
to create reference values which are the basis for comparison of expected and actual values to
the machine conditions.
The System consists of:
Sensors
Processing of measured values
Personal PC
Software (Analysis Function)
Diagnostic
The advanced product solution represents the diagnostic system setting up on the results of
the analysis and contains the measurement values and parameters, the identification of
failures, disturbances and recommendations from an remote expert center. The software is
capable of learning the normal behavior of a machine or a system during a period of time
which should contain all different load factors and start up and shut down procedures. Data
which cannot be explained by the process model will be passed through to the human experts
only. The System consists of:
Sensors
Processing of measured values
- 21 - © Siemens AG 2006. All rights reserved.
Personal PC
Software (Analysis Function)
Remote Expert Center
Due to the fast growing market of new sensor technology Power DiagnosticsTM is built up on
a modular basis. In this way a high flexibility and a fast adoption to new developments can be
achieved.
The critical factor of Power DiagnosticsTM is the data processing:
On-site data acquisition and monitoring system
Data infrastructure and collection
Measurement and analysis of equipment conditions and performance
Comparison of conditions to fleet equipment baselines, design specification
and experiences, communication of relevant data
Technical advice
Identification and isolation of problems
Root-cause analysis and experience-based learning
Data archiving and unit/machine analysis
Remote Expert Center
Problem reporting and corrective action recommendation
Identification and isolation of problems
The focus of Power DiagnosticsTM is to bring together the core business of the operator and
the manufacturer to use their overlapping fields of experience (Figure 13) to establish real
condition based maintenance based on a relevant data basis. Modern computer software
allows to have access to all data by the experts in our global network but privacy protection is
a must and is a key function of our system.
- 22 - © Siemens AG 2006. All rights reserved.
Figure. 13. (Power DiagnosticsTM, Concept of overlapping know-how areas)
Power GenerationPG O263 Michael Killich
Global network of engineers Know-how from design and manufacturingRecommendations for optimized power plant operationFind and implement measurements in cooperation with the customer -oriented on customer benefitsConditioned based maintenancePerformance based paymentsExtended warranties and risksharing in combination with LTPs
Diagnostics ConceptPower Plant Diagnostics with Remote Control & Smart SensorsDiagnostics ConceptPower Plant Diagnostics with Remote Control & Smart Sensors
Assessment using overlapping areas of know-how & Diagnostics
Boi
ler
Turb
ine
Gen
erat
orI &
CB
OP
Operation Assessment
Design Development
Siemens
Cus
tom
er
Kno
w H
ow W
idth
Kno
w H
ow W
idth
Know How DepthKnow How Depth
Fig. 13
The underlying philosophy of the monitoring and diagnostics concept is described within the
know-how range and depth:
- focus on core competencies, data privacy, communication
- time: short response times due to global resources
- value: access to Siemens’ engineering, condition based maintenance,
prevention of forced outages.
- 24 - © Siemens AG 2006. All rights reserved.
reports or recommendations to the product line marketing and to the sales service. In urgent
cases the customer will be informed immediately.
Summarizing the Power DiagnosticsTM Center is performing analysis and diagnostics using
high sophisticated learning software modules, is providing trend analysis, problem
identification and root-cause analysis done by human experts. The learning software solution
prevents them from dealing with trivial problems. The engineers in the remote expert center
are comparing and analyzing the incoming data from the whole fleet connected to the
diagnostics center. Because of the pool of information coming from a huge fleet, the
experience is growing much faster than it would be possible for a single operator.
Even if there is no problem the engineering experts are able to generate recommendations on
plant operations and/or maintenance actions. The recommendations are designed to maximize
the equipment’s performance, reliability and availability and potentially, extend outage
interval cycles.
The organization structure and the process flow is shown in Figure 15 below.
Power GenerationPG O26
Network Process Data Flow
Deviation of normal behaviourStorage of historic machine data
Diagnostic Center
Data securityTools
Data
Power Plant Turbine
Generator
I&C
E-Technic
BoP
Boiler
Process
Specifications
Engi
neer
ing
Coo
rdin
ator
Thermodynamic
Processes
Mechanics
Fluid mechanic
Rotor dynamics
Commissioning
Construction
Fig. 15
- 25 - © Siemens AG 2006. All rights reserved.
The following diagnostic modules are available today, but the technology is proceeding fast.
In addition to the more general development of faster computer networks, there is a fast
development of new sensor technologies. (Figure 16):
• Vibration Diagnostics:
Shaft vibration, bearing vibration, end-winding vibration using fiber optic
accelerometers.
• Thermodynamics Diagnostics “KRAWAL”:
A tool developed for plant design and engineering of the thermodynamic processes
integrated in the online diagnostic to compare current process data with expected
values.
• Turbine Operability Enhancement “TOE”:
Historically steam turbine operation were designed for a market that was typically
either base load or intermediate duty load operation. Applying the historical steam
turbine start-up philosophy either limits the operating flexibility or exceeds steam
turbine allowable stresses increasing service consumption.
The demand for flexible operation leads to the development of innovative concepts to
reduce start-up times of steam turbines while minimizing service time consumption
thereby improving availability. This new concepts include plant operability
enhancements, such as e.g.
- steam turbine stress controller and stress monitoring system
- high level of plant automation
- plant systems designed to provide steam conditions necessary for a pre-selected
start-up mode
- remote online monitoring and diagnostics
• Online Life Consumption Calculation:
Basis for TOE.
RF Monitoring:
In high-voltage equipment such as Generators, Terminal lead area, transformers and
motors faults occur. To avoid repair costs or even loss of revenue due to unscheduled
outages, it is necessary to identify these faults and rectify them in time
- 26 - © Siemens AG 2006. All rights reserved.
Faults in electrical equipment do not occur suddenly but, in most cases, are announced
in advance by telltale partial discharges. They short-circuit across part of the high-
voltage insulation and can be detected by radio frequency (RF) measurement methods
because of their radio-frequency character.
Suitable selection of RF measuring points allows detection of partial discharge sources
over the entire high-voltage range. To avoid intervention in the insulation system of
the components itself, natural coupling points are preferred.
By digital unmasking of the partial discharge signals from the usually noisy complex
mixture of RF signals it is possible to determine the causes of the discharge. With
simultaneous measured data acquisition and different measuring points it is possible to
locate possible source of faults.
• Other modules as shown in Figure 6
Figure 16 (Available Diagnostic Modules).
Power GenerationPG O26
Diagnostics Module Portfolio
Measurementof internalefficiency
TOE
Steam turbine
Generator
Auxiliaries/Balance of Plant
BearingTemperature
Coast downTime
Operatinghours
Counter
Online Life Consumption
calculation
Turbine stress
Evaluator
HF-Monitoring
H2 LeakageDetection
Stator barsTemperature
Monitor
Humity Ingress
Monitoring
GeneratorTemperature
Analysis
KRAWAL
TorsionalVibration
Monitoring
Shaft/BearingVibration
Monitoring
End windingVibration
Monitoring
Fig. 16
- 27 - © Siemens AG 2006. All rights reserved.
4.2 Diagnostic : Contractual Models – Partnership Solutions The concept of Power DiagnosticsTM is designed to fit in our Strategic Alliances Programs.
These long term service contracts (OPSA, LTP, O&M) are designed to develop the business
from transactional and price driven models to performance driven contracts with value based
pricing. Performance driven, value based pricing means mutual agreed objectives like
availability, reliability or other customer benefits measured and evaluated in a Score Card.
The prices for services ordered within such long term contracts are therefore fixed prices from
a list of specifications plus a bonus / penalty based on the results of the Score Cards.
This concept of a value based pricing system is available for Power DiagnosticsTM Service
Contract also. In this case the customer’s benefits have to be identified and written down in a
mutual agreed matrix. Events like avoidance of an forced outage or early detection of an
developing failure could be those benefits. The early detecting for example gives the customer
additional time for planning and can therefore shorten the outage duration. The different
service packages coming with a diagnostics service contract are clustered in the following
packages / modules (Figure 17):
Service Package 0
The service package 0 is a fingerprint of the actual behavior of the plant or machines at
different (normal) operating / load conditions. All the incoming data from the different
measurement chains are identified and interpreted to be the normal status of the system.
Extreme variations from the expected conditions can be determined by comparison with the
design data of the engineering details.
Service package 0 is based on a fixed work scope.
Service Package 1
All measured values are within normal ranges (experience from service package 0) and no
extreme variations or trends could be found in the data. The package includes cyclique human
expertise also (online weekly / offline quarterly). The results are stored and added to the
databases. An quarterly report is issued.
Service package 1 is based on a fixed work scope.
- 28 - © Siemens AG 2006. All rights reserved.
Service Package 2
All measured values are in normal ranges (below alarm levels) , but there a trend is identified
which needs a more detailed examination to make sure that no generic problem is upcoming
that might result in values (e.g. vibrations) over the alarm or trip level. The measures which
can be taken are defined in co-operation with the customer. proactive activities.
The work scope depends on the single accuracy and cannot be fixed or predicted.
Service Package 3
One or more measured values are higher than the corresponding alarm levels. Based on a root
case analysis a recommendation is provided which may result in a allowance of a risk
operation by the manufacturer or the insurance company for a limited time period. In the
mean time all data are evaluated by human experts.
Power GenerationPG O26
Definition of Service Packages
Service- Package 2Detail. Trend Tracing(Control of deviations) evil. Offline measurements on site)Analysis of actual machine conditionEstimation of continuing operationRecommendations to operating modeFinding based cause studiesActualisation of lifetime documentation
Service- Package 1Trend tracing(fixed monitoring schedule)Actualisation of the lifetime documentationCustomer visit
Service- Package 3Detail. Trend TracingAnalysis of actual machine conditionDocumentationEstimation of continuing operation(Risk operation)Recommendations to operating modeFinding based cause studiesRecommendations for the preparation and implementation of measurementsControl of measurementsActualisation of lifetime documentation
Detailed monitoring(based on deviations from normal
conditions/behaviour)
Monitoring and additional measurements
(based on findings in Package 1 or 2)
Continuous monitoring
Fingerprint
Service-Package 0Documentation of normal conditions
Machine lifetime documentation
Figure 17 (Available Diagnostic Modules). The range of the diagnostic packages / modules and the scope of the different service
packages are not fixed and can be adopted to the customers’ needs. The boundaries between
the different services packages are results of customer interviews so far.
- 29 - © Siemens AG 2006. All rights reserved.
For customers who have already signed an long term program the costs for the service
packages 0 and 1 including the regarding recommendations coming with a quarterly report
(Figure 8) will integrated in the existing contract. Hard- and software costs will be charged
separately and all costs from service modules 2 and 3 will be charged on time and material
bases or on the above mentioned value based pricing models.
Figure 18 (Market Drivers – Transactional business vs. performance driven business ).
„Power DiagnosticsTM“Power GenerationPerformance Maintenance – Marketing O263
Commitment
Mut
ual B
enef
it
TMS
TFA
OPSA
LTP
O&M
TransactionalTransactional ExpandedScope / RiskExpanded
Scope / RiskPerformance
DrivenPerformance
Driven
MC
Today:fire fighting
reactiv
Diagnostic compatibleData collection
proactiv
Long Term Alliances
Minimum of contineous
costs
Sales estimation
- 30 - © Siemens AG 2006. All rights reserved.
The customer benefits and the corresponding investment for the different packages is shown
in Figure 19. The benefits related to the Service Package can be summarized as follows:
Service Package 1:
Access to the Siemens expert network and the Siemens service hotline
(the expert network consists of Siemens engineers of all main power plant disciplines
like steam turbine engineering, gas turbine engineering, generator engineering, I&C,
E-Technics, Process Engineering, Balance of Plant, Boiler)
Documentation and reporting of the plant / machine conditions on a regular basis
Early detection of changes because of good and reliable data bases
Service packages 2 and 3:
Risk operation
Early problem (damage) detection
Additional time for planning
All in all the Power DiagnosticsTM System is basis for
Condition based maintenance
Flexible operations
Lifetime extension
Efficiency improvement
Availability increase
- 31 - © Siemens AG 2006. All rights reserved.
Power GenerationPG O26
Customer Benefits
Marginal costsFixed Price
Benefit
Costs
Base amountBasicInvestment
Condition based maintenanceFlexible operationLifetime extension
Efficiency improvementAvailability increase
Time and material or performance based chargingOne off costs
Access to Expert Networkregular documentationEarly detection of problems
Service Package 0
Service Package 1
Service Package 2
Service Package 3
Hard-/Software
Investment
Risk operation Early damage detectionContinuing operation
Power DiagnosticsTM
is basis for...
Figure 19 Customer Benefits and Partner Solutions. 4.3 Data Acquisition, Network Operation and Feedback Cycle An efficient and safe network configuration is the key to reliable remote data acquisition and
diagnostics. Local acquisition, archiving and diagnostics combined with periodic and event-
based data transfer are the on-site tasks. The system infrastructure for the data handling have
to fulfill high safety requirements to make sure that the data flow is secure (Figure 20).
Operative measuring, the evaluation of troubles and the periodic measurement for trend and
state assessments in the past came to the conclusion that the information content is often used
insufficiently by measuring signals for the assessment of the machine condition. E.g. on the
one hand the traditional supervision carries out a low evaluation of the information content of
the signals and on the other hand all periodic measurements with transportable measuring and
analyzing equipment have only the character of sample measuring, despite an extensive signal
analysis.
- 32 - © Siemens AG 2006. All rights reserved.
In both cases the knowledge over the time and the temporal course of the changed, often very
complex behavior of a machine, inclusive of all accompanying boundary conditions is
insufficient.
Power Generation
Access Server
DMZ
Rem
ote S
ervic
eRe
mot
e Ser
vice
Plat
form
Plat
form
InternetISDN, POTS VPN
Intra
net
DiagnosticsReportsRemote Clarification
SAP Remote Service CenterHQ
Region
UserAccounts
Installed Base Data
DataServices(temp)
Basic Software Components
Extended Platform Services
Cust
omer
Site
Customer Network
On Site ServerLocal Services
J
RS-AgentRemote Access Client Remote enabled equipmentRS-Agent
Power Diagnostics TM Center
Expert Network
Experten,Engineering Know-how
Diagnose
Figure 20 Secure Data Handling. With Power DiagnosticsTM comprehensive diagnostic statements concerning the assessments
of the turbo machines and its operation mode and therefore requirements and decisions with
regard to further operation shall get possible.
Prerequisite for the diagnostics is the comprehensive usage of the information content of
signals to the plant assessment.
Data acquisition suitable for diagnostic:
The data acquisition requires the measuring of signals, which contain adequate
information about the condition and condition changes of the respective machine.
The data acquisition has to be carried out in a way that a considerable information loss
doesn’t already occur in the measuring phase:
Continuous signal recording
- 33 - © Siemens AG 2006. All rights reserved.
Recording of the operation regime as well as of the relevant measures
of the process technology.
Data analysis and data reduction to informative code numbers suitable for diagnostic
at minimal information loss:
The objective is a to reduce the data to informative characteristic quantities. The large
amount of data has to concentrate on few representatives and qualitatively clear
characteristic quantities.
Data preparation suitable for diagnostic for off-line diagnostic by experts.
Manual assessment of machine conditions. In the context of a diagnostic computer in
on-line operation or of stored data a variety of representations have to be selectable or
over printer/plotter displayable.
Determination of the machine type and measuring place specific normal condition and
normal behavior of the characteristic quantities in the fluctuation area of normal
operation parameters for the operation condition.
Supervision suitable for diagnostic, i.e. automatic data assessment in the comparison
with the values of the normal condition and normal behavior with data storage at
deviation of the normal condition as well as qualified machine protection:
The tasks of supervision suitable for diagnostic consist in the comparison of the
characteristic quantities with the characteristic quantities of the normal condition or
the normal behavior among the respective operation regime of the plant with
following two functional aim positions in the variation area of the normal operation
parameters.
Plant protection:
Condition changes of characteristic quantities which signal the plant
endangering of the operational safety must be recognized in the interest of the
quickest possible triggering of the machine protection.
Control of the data storage:
Condition changes of single characteristic quantities, which don't lie in the area
of its normal behavior, must be subjected to event-driven data storage.
Automatic on line diagnostic at deviation of the normal condition:
Automatic determination of the machine type and measuring place specific behavior
of characteristic quantities. The full effectiveness of the diagnostic is achieved if
machines and measuring place specific limit and reference values which take into
- 34 - © Siemens AG 2006. All rights reserved.
account the constructive unusual features of the machines and their operation are
defined for the characteristic quantities.
The global network configuration shown (Figure 14) gives an idea of the performance of the
plant diagnostics integrated into the Siemens intranet. The PG Power Diagnostics Center is
located in the middle. Worldwide secure modem connections establish the data links to the
individual plants and their WIN_TS installations. For qualified assessment of diagnostic
findings, links to the various centers of knowledge (competence) for say steam turbines, gas
turbines, generators and the balance of plant are established via the in-house Intranet.
October 2004 © PG G1 17
R: PG2004_Schei, Be,Ta_.ppt
Power-Gen Asia 2004, Bangkok
Worldwide Implementation of WIN TS Gas Turbine Diagnostics
250 WIN TS Diagnostic Systems Installed for Gas Turbines * including steam turbines
350 WIN TS Diagnostic Systems installed worldwide*
> 120 installed
> 130 installed
60 Hz
50 Hz
Fig. 21 Figure 21 shows the installation status of WIN_TS diagnostic systems worldwide.
More than 120 installations for gas turbines are in service in the 60 Hz region, and over 130
installations in the 50 Hz region.
- 35 - © Siemens AG 2006. All rights reserved.
October 2004 © PG G1 18
R: PG2004_Schei, Be,Ta_.ppt
Power-Gen Asia 2004, Bangkok
It is important to receive continuous live data feedback from "running technological systems" at early stage, both for
- immediate customer support
- product feedback
WIN_TS
SIEMENS PG
Service
Engineering
R&D
Erection/Commisioning
Benefits for Operation, Research and Development
Feedback Loop
Fig. 22
Live data from a running technology system for immediate customer support and product
lifecycle feedback provides a significant benefit for operation, research and development. As
Figure 22 shows, remote online diagnostics serves as the feedback loop into customer
service, engineering and research & development after erection and commissioning.
Through remote access, the local diagnostic systems are connected to Diagnostics Centers in
Orlando and Erlangen, to where they send data via data containers. From the Diagnostic
Centers, the experts are able to assist in any critical situation which needs their immediate
attention during commissioning or service. Just a few mouse clicks and they have access to
data from gas turbines all over the world
5. Summary, Outlook Due to the changing market conditions all over the world the traditional way of handling the
maintenance business does no longer fit these new environmental requirements. The solution
is to achieve a flexible and short termed outage planning process and a reduction of marginal
and transactional costs. Strategic Alliances in combination with Remote Diagnostics can fulfil
all these demands because they are tailor made solutions based on contracts designed to leave
the transactional business behind. The range of this Strategic Alliances varies from Operating
Plant Service Agreements (OPSA) to Long Term Programs (LTP) and Operation and
- 36 - © Siemens AG 2006. All rights reserved.
Maintenance Contracts (O&M) with risk sharing elements and the possibility of complete
outsourcing of the maintenance tasks. Value based and success oriented payment makes sure
that both partners will benefit from a good performance.
Monitoring and diagnostics is a rapidly evolving field in power generation. The combination
of available on-line expertise and Strategic Alliances provides cost-efficient service and
benefits to the customer.
In summary:
• Risk sharing and value based pricing based on assessment using diagnostics • Extended Warranties • More and more specific analysis and diagnostic technology is now available • To maximize the benefit for power plants, the challenge is to employ all
technologies needed via a single platform • Global networking of a running fleet enables OEM experts to analyze data
quickly and respond rapidly to customer requirements • On-line diagnostics - in combination with remote expert knowledge - is the key to
condition-based maintenance and provides cost-efficient service for reliable plant operation.
For the customer, it is important in any given situation to have access to the knowledge of the
people who designed his equipment.
For the equipment supplier, the greatest benefit is to have live feedback from his own
"running technological systems" that enables him to optimize his own learning..
And last but not least, on-line diagnostics and Strategic Alliances paves the way from
scheduled maintenance to condition-based maintenance, thus helping customers to operate
their units at maximum profit.
Literature [1] Taud R.; Scheidel M.: Use and Experience with Gas Turbine On-Line Diagnostics,
Power Gen Europe, Barcelona 2004 [2] Bender, K.; Grühn, M.; Rukes, B.; Scheidel, M.: Online Remote Diagnosis of
Turbosets and Combined Cycle Power Plants; VDI-Bericht Nr.: 1641, VDI-Verlag, Düsseldorf, 2001
[3] Adam, G.; Bode, A.: Ferndiagnose und Teleservicesystem für GUD-Kraftwerke; VDI-Bericht Nr.: 1566, VDI-Verlag, Düsseldorf, 2000
[4] Brummel, H.-G.; Scheidel, M.; Thompson, E.: Gut behütet aus der Ferne; Siemens Power Journal, Heft 1/00
- 37 - © Siemens AG 2006. All rights reserved.
Biographical Information Speaker: Michael Killich
Position: Marketing Manager Steam Plant Services
Company: Siemens Power Generation
Country: Germany
____________________________________________________________________
Michael Killich is head of the marketing group within the O26 Performance Maintenance
product line, responsible for Europe, Africa, Asia-Pacific
He is holding a Master of Science Degree in Power Engineering of Aachen Technical
University. After some years as project manager for Von Roll AG in Switzerland for waste
fired cogeneration power plants he joined a privately owned operating company for a waste
incineration in Germany as head of the technical department during erection phase and as a
maintenance manager after PAC.
In 2001 he entered Siemens AG to work for the Performance Maintenance O26 product line
in Mülheim, Germany. 2003 he became head of the marketing group.