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

1. 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

2. Now what?? 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 Source: WMEP 2002 Onshore ≤ 1 MW

3. Introduction • 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

4. Unplanned Corrective Maintenance DATA Calendar OMCE Calculator Based Maintenance Condition Based Maintenance O&M Cost Estimator: Structure • Failure rate • Repair strategy INFO Annual O&M Costs • Time to failure • (Repair strategy) INFO

5. 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 • Generate input data for OMCE-Calculator • Generate useful insight in general

6. Building Block ‘Operation & Maintenance’ • Goal: • Estimate failure frequencies of the different wind turbine components • Method: • Structured collection of O&M data • Ranking • Trend analysis using CUSUM-plots • Determine failure frequencies ???

7. Building Block ‘Operation & Maintenance’ • Goal: • Estimate failure frequencies of the different wind turbine components • Method: • Structured collection of O&M data • Ranking • Trend analysis using CUSUM-plots • Determine failure frequencies

8. Sheets with vessels used Sheets with workable days Files with alarms and downtimes Building Block ‘Logistics’ • Goal: • Quantify costs of repair actions • Spare part and stock control • Method: • Analyse information sources • Link different maintenance actions to one event • Determine costs/effort per Repair Class - Monthly management reports - Overview of used spares - Etc….

9. CUSUM plot of certain event Building Block ‘Logistics’ • 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 • Goal: • Quantify costs of repair actions • Spare part and stock control • Method: • Analyse information sources • Link different maintenance actions to one event • Determine costs/effort per Repair Class

10. Building Block ‘Health Monitoring’ • Goal: • Estimate degradation • Estimate remaining lifetime • Method: • Combine information sourcesand set limits • Structure and de-trending • Determine failures, degradationand remaining lifetime

11. De-trending generator temp. Degradation of bearing Building Block ‘Health Monitoring’ • Goal: • Estimate degradation • Estimate remaining lifetime • Method: • Combine information sourcesand set limits • Structure and de-trending • Determine failures, degradationand remaining lifetime

12. 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)

13. Event list Structured data Raw data Event List for structuring raw data

14. Event List for structuring raw data • 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)

15. Unplanned Unplanned Corrective Corrective Maintenance Maintenance Calendar Calendar OMCE Calculator OMCE Calculator Based Based Maintenance Maintenance Condition Condition Based Based Maintenance Maintenance 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

16. OMCE-Calculator Example of Input screen Example of Output Screen

17. OMCE-Calculator Uncertainty analyses

18. OMCE-Calculator Specs based on long term experiences with ECN O&M Tool > 10 licenses world wide; > 20 wind farms since 2005 • 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

19. 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

20. 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)