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

2

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

3

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)

2013-08-30 7

Source: Wind Farm Management System

Analysis and reportingKPI to be followed up daily, weekly and monthly

Classification: Internal 2012 12 31

8

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.

2013-08-30 9

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

2013-08-30 26Classification:

PhD work on wind park O&M simulation model

27

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

31 -

Dr. Nenad KesericMPR RE Operations Strategy and Supportnenk@statoil.com+47 954 33 483www.statoil.com

Thank you

The future is floating!