Luc Rademakers , Henk Braam, Tom Obdam, Rene v.d. Pieterman

Operation & Maintenance Cost Estimator (OMCE) To Estimate the Future O&M Costs of Offshore Wind Farms

Luc Rademakers, Henk Braam, Tom Obdam, Rene v.d. Pieterman

• Introduction

• Structure of the O&M Cost Estimator

• Building Blocks for data processing

• Event list to structure raw data

• OMCE-Calculator

Introduction

• O&M costs offshore account for 25-30% of KWh costs

• Optimizing O&M is essential; requires accurate estimates of

(1) averages and (2) uncertainties

Corrective Maintenance Costs as a Function of Age

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500 -1000 kW

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Extendedservice contract

Corrective repairresponsibility of owner

? ? ? ?


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500 -1000 kW

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Warrantyperiod



? ? ? ?


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0 2 4 6 8 10 12 14 16 18 20

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500 -1000 kW

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Now what??Source: WMEP 2002

Onshore ≤ 1 MW

To estimate the future (say 2 to 10 years) O&M costs

based on operational data and measured loads

When, why?

– Making reservations for future O&M budgets

– Deciding on new O&M contracts

– Optimise O&M at end of warranty period

Introduction

O&M Cost Estimator: Structure

BB Operation & Maintenance

BB Loads&Lifetime

BB Health Monitoring

BB Logistics

INFO

INFO

DATA

-Failure rate

-Repair strategy

-Time to failure

(Repair strategy)

Annual

O&M CostsOMCE Calculator

Condition Based

Maintenance

Unplanned Corrective

Maintenance

Calendar Based

Maintenance

Building Blocks

Process wind farm data in such a way that useful

information is obtained, each covering a specific data set.

- BB Operation and Maintenance

- BB Logistics

- BB Loads and Lifetime

- BB Health Monitoring

- BB Meteo

1) Generate input data for OMCE-Calculator

2) Generate useful insight in general


BB Loads&Lifetime


BB Logistics

INFO

INFO

DATADATA

-Failure rate

-Repair strategy

-Time to failure

(Repair strategy)

Annual


Condition Based

Maintenance


Maintenance

Calendar Based

MaintenanceOMCE Calculator

Condition Based

Maintenance


Maintenance

Calendar Based

Maintenance

Building Block ‘Operation & Maintenance’

Method:

• Structured collection of O&M data

• Ranking

• Trend analysis using CUSUM-plots

• Determine failure frequencies

Goal:

• Estimate failure frequencies of the

different wind turbine components

S C A D AS C A D A

W o r k S h e e tW o r k S h e e t

O p e r a to r sO p e r a to r s

???

Building Block ‘Operation & Maintenance’

Year 3 recommendedfor future estimates

dT

dn


dT

dn


dT

dn


dT

dn

Method:

• Structured collection of O&M data

• Ranking

• Trend analysis using CUSUM-plots

• Determine failure frequencies

Goal:

• Estimate failure frequencies of the

different wind turbine components

Building Block ‘Logistics’

Method:

• Analyse information sources

• Link different maintenance

actions to one event

• Determine costs/effort per

Repair Class

Goal:

• Quantify costs of repair actions

• Spare part and stock control

Sheets with vessels used

October1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 Tot

0,00 0,00 0,00 0,00 0,00 0,00 0,00 0,00 0,00 0,00 0,00 0,00 0,00 0,00 0,00 1,00 0,30 1,00 1,00 0,00 0,00 0,00 0,00 0,00 0,00 0,00 0,30 1,00 0,30 1,00 0,30 6,20

October1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 Tot

0,00 0,00 0,00 0,00 0,00 0,00 0,00 0,00 0,00 0,00 0,00 0,00 0,00 0,00 0,00 1,00 0,30 1,00 1,00 0,00 0,00 0,00 0,00 0,00 0,00 0,00 0,30 1,00 0,30 1,00 0,30 6,20

Sheets with workable days

- Monthly management reports

UnitDetected

Reset/RunDuration Code Description

WTG019-11-2007 0:29

9-11-2007 0:310:01:27

356 Extreme yawerror 24.1m/s 20.0°

WTG019-11-2007 2:16

9-11-2007 2:200:03:21


WTG019-11-2007 2:20

9-11-2007 2:300:09:23

144 High windspeed: 20.5 m/s

WTG019-11-2007 3:59

9-11-2007 4:060:06:15


WTG019-11-2007 4:15

9-11-2007 4:200:04:05


WTG019-11-2007 9:30

9-11-2007 9:400:09:56

156 Chock sensor trigged: 0.0RPM

WTG019-11-2007 9:49

9-11-2007 9:500:00:47

224 Pause

WTG019-11-2007 10:58

9-11-2007 11:000:01:25


WTG019-11-2007 11:09

9-11-2007 11:100:00:21

224 Pause

WTG019-11-2007 12:39

9-11-2007 12:400:01:00


WTG019-11-2007 14:47

9-11-2007 14:500:03:00


WTG019-11-2007 14:52

9-11-2007 15:000:07:47


WTG019-11-2007 16:29

9-11-2007 16:300:00:59


WTG0111-11-2007 23:47 11-11-2007 23:50

0:02:01356 Extreme yawerror 0.0m/s 0.0°

WTG0115-11-2007 13:56 15-11-2007 14:00

0:03:23220 New SERVICE state: 0, 0

WTG0115-11-2007 23:09 15-11-2007 23:49

0:39:50276 Start auto-outyawing CCW

WTG072-11-2007 11:03

2-11-2007 11:100:06:27

224 Pause

WTG072-11-2007 11:10

16-11-2007 8:29 333:19:25223 Stop

WTG0716-11-2007 8:30 16-11-2007 13:36


WTG0716-11-2007 13:42 16-11-2007 13:50

0:07:59840 Gear oil level too low 0 mm

WTG0716-11-2007 13:52 16-11-2007 14:00

0:07:48222 Emergency

WTG0716-11-2007 14:08 16-11-2007 14:20


WTG0716-11-2007 14:27 16-11-2007 14:30

0:02:32223 Stop

WTG0716-11-2007 14:37 16-11-2007 14:51


WTG0730-11-2007 0:53 30-11-2007 14:40 13:46:40

633 Signal error. PAUSE 0, 0

WTG0730-11-2007 14:40 30-11-2007 14:50


WTG0730-11-2007 14:50

1-12-20079:10:00

633 Signal error. PAUSE 50,22

WTG117-11-2007 10:08

7-11-2007 10:100:01:43

220 New SERVICE state: 1, 0

WTG118-11-2007 23:56

9-11-2007 0:010:04:58


WTG119-11-2007 2:12

9-11-2007 2:250:12:41


WTG119-11-2007 2:58

9-11-2007 3:000:01:30


WTG119-11-2007 3:59

9-11-2007 4:070:08:09


WTG119-11-2007 14:45

9-11-2007 14:520:07:02


WTG119-11-2007 16:18

9-11-2007 16:200:01:40


WTG119-11-2007 19:18

9-11-2007 19:200:01:35


WTG1110-11-2007 0:49

10-11-2007 0:500:01:00


WTG1110-11-2007 10:09 10-11-2007 10:10


WTG1111-11-2007 20:18 11-11-2007 20:20


WTG1111-11-2007 23:47 11-11-2007 23:50


WTG1113-11-2007 12:55 13-11-2007 13:00


WTG1113-11-2007 13:09 13-11-2007 13:10

0:00:23224 Pause

WTG211-11-2007 0:10

1-12-2007 719:50:00226 Power cutout

Files with alarms and downtimes

- Overview of used spares

- Etc….

Building Block ‘Logistics’

Method:

• Analyse information sources

• Link different maintenance

actions to one event

• Determine costs/effort per

Repair Class

Goal:

• Quantify costs of repair actions

• Spare part and stock control

Nu

mbe

r of

occu

rrenc

es

Year 1 ?? [events/day]

Year 2 ?? [events/day]

Date from start to end

Turbine ID

All turbines Year 2

All turbines Year 1

Linear (All turbines Year 1)

Linear (All turbines Year 2)

CUSUM plot of certain event

Quantification of Repair Classes

• successive activities

(inspection, replacement, and/or repair)

• time to organise repair activities

• duration of each activity

• equipment used

• crew size

• spare parts

Building Block ‘Health Monitoring’

Method:

• Combine information sources

and set limits

• Structure and de-trending

• Determine failures, degradation

and remaining lifetime

Goal:

• Estimate degradation

• Estimate remaining lifetime

SCADA

SCADA data

SCADA

SCADA data

Drive train monitoringDrive train monitoring

Building Block ‘Health Monitoring’

Method:

• Combine information sources

and set limits

• Structure and de-trending

• Determine failures, degradation

and remaining lifetime

Goal:

• Estimate degradation

• Estimate remaining lifetime

De-trending generator temp.

Maximum daily RMS of electrical powerwithin the range of 2.5 – 3.0 Hz.Maximum daily RMS of electrical powerwithin the range of 2.5 – 3.0 Hz.

Degradation of bearing

Building Blocks: Conclusions

• BB ‘Health Monitoring’ (and ‘Loads & Lifetime’)

- Health monitoring systems (often “firmware”) provide remaining lifetime

- BB not “piece of software” but a combination of (many) methods

• BB’s ‘O&M’ and ‘Logistics’

- Data sources contain information relevant for OMCE!

BUT

- Current format for data capture too time consuming

- Data sources independent

Raw data needs to be structured!

(Conclusions based on ECN’s experiences with data from on- and offshore wind farms)

INFO

INFO

DATADATA

-Failure rate

-Repair strategy

-Time to failure

(Repair strategy)

Annual


Condition Based

Maintenance


Maintenance

Calendar Based


Condition Based

Maintenance


Maintenance

Calendar Based

Maintenance

Event List for structuring raw data


BB Loads&Lifetime


BB Logistics

INFO

INFO

DATADATA

-Failure rate

-Repair strategy

-Time to failure

(Repair strategy)

Annual


Condition Based

Maintenance


Maintenance

Calendar Based


Condition Based

Maintenance


Maintenance

Calendar Based

Maintenance

Raw

data

Event list Structured

data


BB Loads&Lifetime


BB Logistics

INFO

INFO

DATADATA

-Failure rate

-Repair strategy

-Time to failure

(Repair strategy)

Annual


Condition Based

Maintenance


Maintenance

Calendar Based


Condition Based

Maintenance


Maintenance

Calendar Based

Maintenance

Requirements:

• Relations between event and maintenance actions

• Events per turbine in chronological order

• Each event classified as one of the Repair Classes relevant for

O&M modelling

• Contain sufficient details to determine OMCE input parameters

• (Integrated with works management system)

Event List for structuring raw data

OMCE-Calculator

Specifications

• User friendly input to define 3 types

of maintenance and their priorities

• Considering limitations in: vessels, weather limits,

stock control, spares

• Scenario studies, optimisation of strategy

• Uncertainty analyses

• MatLab simulation tool

OMCE Calculator

Condition Based

Maintenance


Maintenance

Calendar Based


Condition Based

Maintenance


Maintenance

Calendar Based

Maintenance

OMCE-Calculator

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1 2 3# of personnel transfer vessels

Ann

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Example of Output ScreenExample of Input screen

Uncertainty analyses

Regression Sensitivity for total costs per kWh

0.614

0.473

0.277

0.191

0.187

0.152

0.13

-1 -0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8 1

Fail Freq Gearbox

Fail Freq Blade

Fail Freq Generator

Mat. costs repl. Blde

Mat. costs repl. gearbox

Fail freq elec. syst.

Mat. costs repl. Generator

Regression coefficients

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Total costs per kWh [Euro cent]

CD

F [

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OMCE-Calculator

ECN O&M Tool (Planning phase)

Cost estimate based on:

- Average values

- Historical generic data

- Design (calculated) loads

- Same loading and O&M for all turbines

Results:

- Long term annual average values

OMCE (Operational phase)

Cost estimate based on:

Values time depend

Actual specific wind farm data

Measured loads

Loading and O&M turbine specific

Results:

Values more time dependent

OMCE-Calculator

Specs based on long term experiences with ECN O&M Tool

> 10 licenses world wide; > 20 wind farms since 2005

OMCE Concluding remarks

• OMCE-Calculator efficient tool for determining

future O&M Costs (first release end of 2009)

• Processing raw data by means of Event List and

BB’s requires improved data capture procedures

No “reverse engineering” and less time consuming if data

capturing could be integrated in works management system

Thank you for your attention!

The OMCE developments are sponsored by:

• SenterNovem through the We@Sea program

• European Fund for Regional Developments (EFRO)

of the EU through the D OWES project

Special thanks to Noordzeewind for providing data of

the Offshore Wind farm Egmond aan Zee (OWEZ)

Documents

Luc Rademakers , Henk Braam, Tom Obdam, Rene v.d. Pieterman