Statoil Wind O&M data monitoring, analysis and simulation · Example Hywind production during a...
Transcript of Statoil Wind O&M data monitoring, analysis and simulation · Example Hywind production during a...
Statoil Wind O&M data monitoring, analysis and simulationDr. Nenad KesericStatoil MPR Renewables, Operations Strategy and SupportNorcowe, Science meets industry, Bergen 9.9.2014 2013-08-30Classification: Internal
Statoil Renewables- Building our portfolio:Maximise value in offshore wind
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2009- 2012- 2017
2.3MW
DoggerBank
Hywind Pilot Park
DudgeonSheringham
ShoalHywind Demo
317MW1.1 Twh / yr*
IIIncrease
Portfolio
*total average production for Scira
2016/17
Up to 560 MW
Up to 9 GW
30 MW
Operation and maintenannce
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The O&M as important area within the complete set of business processes
Map the full value chain – integrated Operations/Asset Management approach
Plan
Weather forecasting
Production planning O&M planning
Operation & Maintenance
Production & Dispatching
Do
Check
Act
Safe workPersonnel and cargo logistics
Job execution Monitoring operation
Process control and optimisation
Deviation analysis
Corrective actions Settlements Improvements Large
potential
2013-08-304 Classification: Internal
Balanced Asset Performance Management
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• To run a wind farm as efficient as possible, it is important to build performance based culture. KPI measurements on three levels:
− High level: set of (KPIs) following closely all aspects of running the park
− For the Critical processes in the Wind Operating Model a set of Performance Indicators (PIs) are defined
− Lowest and most detailed level: a set of Critical Parameters (CPs) are defined to follow the O&M processes in the wind farm closely
• The targeting and planning goes from the top level and down while the analysing and reporting of the performance indicators goes from the lowest level and up
Close Collaboration with service providersIntegrated Operation
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Databases and data management
IO is the integration of people, process, and technology to make and execute better decisions quicker. IO is enabled by the use of real time data, collaborative technologies, and multidiscipline work flows.
Plan for short meeting points, called arenas, with fixed participation and fixed agenda.
All participants should have access to same data to be able to prepare
Benefits of sharing common goals
Owners
Monthly KPIsfor board follow-up
Internal KPIs and Performance indicators
KPIs
Process indicators
Critical parameters
Measure performance
Targ
etin
g an
d pl
anni
ng Analysing and reportingDaily
operationmeeting
Weekly operationmeeting
Monthly operation meeting
Boardmeeting
. . . and follow up results and deviations
“If you can not measure it, you can not improve it” (Lord Kelvin)
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Source: Wind Farm Management System
Analysis and reportingKPI to be followed up daily, weekly and monthly
Classification: Internal 2012 12 31
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What happens when we do not acknowledge each others competence areas
• Gearbox failure:
• 4 months of lost production due to wrong decision.
• Lack of owner involvement
• Lack of incentives to cooperate will in the end hurt the entire wind industry
Detailed analysis of historical vibration data show that alarm should have been raised 26. December
Allowing ample time to plan mitigating actions and exchange.
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Bazefield- Operation monitoring and analysis
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Hywind- world first and biggest floating turbine
2014-05-09
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Øyvind Hagen/Statoil
• 2.3MW WTG in operation since 2009
• Located 10km off Norwegian coast at 200m water depth
• In operation since September 2009
• Produced 40 GWh since start-up
• Capacity factor:
− Record of 50.2 % in 2011
− Overall 41.4%
− Very good numbers!
• Maximum wind speed of ca.44m/s and maximum wave height of ca.19m
• Performance has been good
Example Hywind production during a storm conditions
• 24 hour period during storm “Dagmar”, Dec 2011
• Avg. wind speed 16 m/sec
• Max wind speed 24 m/sec
• Max significant wave height 7.1m, ie max wave height ~ 12m
• Power production 96.7% of rated
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13 -Classification: Internal 2011-08-04
Statoil Energy Forecasting System• Reliable weather forecasts needed safe marine operations
and as basis for nominations and trading
• Forecast error can not be avoided but it can be minimisedand Energy Forecasting and Planning System is using Neural Networks and state of the art methods providing reliable and accurate forecast to Trading department.
Terrain Wind farm
Flat 9-12 %
Complex 12-14 %
Highly complex < 20 %.
Calibrated forecast
- with uncertainty
Original forecast
Photo from Anders Wikborg. ©Statoil
Probabilistic production/wind/wave forecast
Internal 22.01.201314-
« The purpose of visualization is insight, not pictures » - Ben Shneiderman 1999
New techniques- Visual Analysis of Multi-Dimensional Data (CMR)
Visual Analytics
« Visual analytics is the science of analytical reasoning facilitated by interactive visual interfaces. »
-- Thomas and Cook, 2005
Main characteristics:•Main purpose: confirm/reject hypotheses•Directed•Automatic methods•Operator/User is steering / controlling•One, two, 3D and N-dimensions
Focus + ContextCoordinated Multiple Views
Density of Low productionDensity of samples with a production lower than 200 MW
Selecting curtailed production
Analysing all samples with a wind speed higher than 7m/s and a production lower than 0,5 MW.
This is the selection used in the next plot
Curtailed productionDensity of samples producing less than 200MW with wind speeds higher than 7m/s
Best producing but load on components?
Analysing the samples of wind turbines that produce more than average given wind speeds between 7 and 12 m/s.
Spatial load (stress) on turbinesDensity over where loads on turbine “stress” occurs
Advanced selections of Curtailed Power
Production Animation
Security Classification: Internal
- Status: D ft
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Change overview
Classification: Restricted 2013-09-20
• Clear change in the relation• Natural fluctuation or systematic effect ?
Security Classification: Internal
- Status: D ft
Lost production focus
• Fit model to data• Estimate parameters• Estimate (Wald) confidence intervals for parameters
• Compare curve fitted to different data subsets• If confidence intervals not overlapping, statistical significant difference in fitted
curves
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PhD work on wind park O&M simulation model
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Marine logisticsMarine logistics
MaintenanceMaintenance Wind turbineWind turbine
• Vessel weather dependence• Vessel capabilities• Access technology• Vessel movements• Coordination between vessels
• Fault diagnostics• Work planning• Resource allocation• Spare part management• Vessel charter• Wind turbine repair
• Wind turbine reliability• Power production• Wind park location (lat/lon)
Simulation results
• Breakdown of downtime in causes
• OPEX per category/y
• Actual and lost production
• Time-based and energy-based availability (average and in time domain)
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Optimising maintenance strategy
• 1st strategy could be increasing resources, having more vessels and technicians ready when a failure occurs; however, this would probably eat away the potential earnings.
• 2nd strategy could be to have other types of vessels that make access to wind turbines less dependent on weather and transit times from onshore bases to the wind park shorter. For example with a mother ship in the park continuously.
• 3rd strategy is to do maintenance when the wind is low, i.e. do better planning and forecasting. Energy-based availability is a function of theoretical production at wind speeds between cut in/cut out speeds. Still some failure categories (large ones) are difficult to plan only in times of low wind speeds as the heavy lift vessel charter market and spare part availability are uncertain, and the downtime due to the combination of weather and spare parts is difficult to mitigate –unless it is possible to foresee in advance when a failure will occur.
• Condition based maintenance - we believe that the industry can realize the potential increase in availability. Not only the big data it should be smart data! How to utilize the information we gain from analyzing condition and SCADA data?
Lead time spare parts
Lead time vessel
Waiting on Weather
Waiting on available
timeTransit to WT Accessing WT Work on WT Accessing
vesselTransit to
base
Waiting on available
technicians
Corrective maintenance downtimeCondition based maintenance
downtime
Summary- status and way forward • Still a young industry will only a handful of large scale
parks operating. Scarce historical data and experience to investigate reliability of turbines. More cost-effective O&M solutions needed to get OPEX/LCoE cost down!
• Lack of transparency/Supply industry protective attitude hindering collaboration across organisational borders.
• Very different from the offshore oil and gas industry where suppliers, operators and R&D institutions actively share data and information for the benefit of the industry
• Requires monitoring and analysis, generate data by simulation model, give operators a tool to handle the risks
• Using good analysis and decision support tolls will increase certainty (reduce risk) through better planning
• Still need to rely on technical support from the turbine manufacturer will decrease as ISP’s and in-house experience increases
LCOE120 £/MWh
EuropeOPEX
25 £/MWhElectricity
price Norway50£/MWh
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Dr. Nenad KesericMPR RE Operations Strategy and [email protected]+47 954 33 483www.statoil.com
Thank you
The future is floating!