What s Hot in University Offshore Renewable Research

Transcription

1 What s Hot in University Offshore Renewable Research Peter Tavner Emeritus Professor, Durham University Former President of European Academy of Wind Energy Beginning is easy - Continuing is hard Japanese Proverb 1

2 Overview Preventing failures, monitoring Condition Monitoring A cautionary monitoring tale About wave & tidal Conclusions 2

3 Preventing Failures, Monitoring 3

4 London Array, Offshore Wind Farm 175 x 3.6 MW WTs, 630 MW 4

5 Wind Turbine monitoring in context Typical data numbers for a 3.6 MW WT: SCADA: I/O, 25% alarms 75% signals; SHM: I/O; CMS: I/O. SCADA evolved from 1980s-requirement to measure performance of β testing onshore Danish Concept WTs; SHM evolved from 1990s-requirement to meet insurance measurement needs to prove structural strength; CMS evolved from 2000s-requirement from insurers following stall-regulated machine gearbox failures. Diagnosis, 10 khz Not continuous SCADA, < Hz Continuous signals and alarms Condition Monitoring, CM, < 35 Hz Continuous Structural Health Monitoring, SHM, < 5 Hz Not continuous 5

6 CMS, Vibration, Oil & Electrical Signals Reference 22 6

7 CMS in Context Conventional rotating machine condition monitoring Vibration accelerometers, proximeters particles in oil Electrical system monitoring Blade and pitch monitoring 7

8 Gearbox Vibration & Particle Count CMS during a 1.3 MW 2-speed WT Gearbox Bearing Fault Reference 12, 13 & 16 8

9 Durham 30 kw Wind Turbine Condition Monitoring Test Rig (WTCMTR) Reference 13 9

10 Power CMS during a 30 kw WTCMTR Generator Rotor Asymmetry Fault Reference 13 10

11 Gear Vibration CMS during a 30 kw WTCMTR Gear Tooth Fault Healthy Tooth Early Stages of Tooth Wear Missing Tooth SBPF = e 0.042*P R² = SBPF [gp 2 ] SBPF = e *P R² = SBPF= e *P R² = Power [%] Reference 18 11

12 Gear Vibration CMS during a 750 kw WT Gearbox Gear Tooth Fault Reference 18 12

13 SCADA Alarms & Signals Reference 22 13

14 Converter SCADA Alarms 1.67 MW Variable Speed WT Double Fed Induction Generator Bypass Contactor Main Switch Main WT Transformer Grid Rotor Stator DC Link Crowbar Rotor-side Inverter Grid-side Inverter Series Contactor Alarm Names Turbine Pitch General Turbine Blade1-3 Emergency Rotor Over-current Rotor-side Inverter Over-temperature Rotor-side Inverter IGBT DC LinkOver-Voltage Grid-side Inverter Over-current Grid-side Inverter Over-temperature Grid-side Inverter IGBT Converter (General) Main Switch Grid Voltage Dip Reference 10 14

15 Converter SCADA Alarms 1.67 MW Variable Speed WT Normalised Cumulative Alarm Duration vs Calendar Time 10 alarms associated with grid fault were chosen Grid Fault1 Grid Fault 2 Reference 10 15

16 Converter SCADA Alarms 1.67 MW Variable Speed WT Grid-side Inverter Overcurrent Rotor-side Inverter Over-Current & Rotor-side Inverter Over-temperature DC Link Over-voltage Grid Voltage Dip Converter General Main Switch Pitch General & Blade1-3 Emergency Reference 10 16

17 Pitch System SCADA Alarms 1.67 MW Variable Speed WT T set by switching frequency Rectifier Diode Bridge DC Bus Converter/SPA 2 IGBT Series Field Pitch Gearbox AC Relay timer Encoder M Shunt Field 2 Quardrant Chopper Motor Reversing Switches Battery (EPU) Alarm Name Turbine Pitch General Turbine Blade1-3 Emergency Pitch Warning General PCP Initiated Emergency Feather Control Blade 1 Saturation Limit Blade 1 Short Circuit Servo Pitch Amplifier (SPA) Fault Blade 1 Reference 10 17

18 Pitch System SCADA Alarms 1.67 MW Variable Speed WT Pitch Warning General Pitch General Blade1-3 Emergency Blade 1 Servo Pitch Amplifier Fault PCP Initiated Emergency Feather Control Blade 1 Short Circuit Blade 1 Saturation Limit Reference 10 18

19 SCADA Alarm Key Performance Indices*(KPI) KPIs: KPI 1, Average Alarm Rate: long term average number of alarms /10 min KPI 2, Maximum Alarm Rate: maximum number of alarms /10 min * Standard Alarm systems, a guide to design, management and procurement No. 191 Engineering Equipment and Materials Users Association 1999 ISBN Reference 10 19

20 SCADA 10 min Alarm KPIs from 7 Wind Farms Reference 10 20

21 Conclusions Wave & Tidal 21

22 The Problem: UK Offshore Rounds 2 & 3 Reference 15 Wind Farms of WTs 400 I/O per WT WT I/O per Wind Farm, excluding substation, cables & connection Total Wind Farm I/O > Onshore: 75% of faults cause 5 % of downtime 25% of faults cause 95% of downtime (Reference 10) Offshore this 75% of small faults will be critical With the alarm rates encountered onshore Operations will be overloaded They will consume O&M 22 time & money

23 Power to Weight Ratios of Wind, Wave & Tidal Onshore Wind Turbines Offshore Wind Turbines Tidal Stream Devices Wave Energy Converters Floating Wind Turbines? Power to Weight, kw/tonne Installation 650/kW CoE 85/MWh Installation 1200/kW CoE 110/MWh? Installation 3600/kW CoE 200/MWh? Installation 3600/kW CoE 250/MWh 0.1 Vestas V90, WT SWT 3.6, WT SWT 3.6, OWT, Anholt Vestas V90, OWT, Kentish Flats Vestas V90, OWT, Barrow MCT, TSD, Seagen Atlantis AR1000, TSD, EMEC Oyster, WEC, EMEC Pelamis, WEC, Agucadoura TE5, WEC, Lowestoft SWT 2.3, FWT, Hywind V80, FWT, WindFloat 23

24 Wave Power Pelamis P2, 750 kw Wavegen-Limpet, 150 kw Archimedes Wave Swing, 1 MW 24

25 Tidal Power Hammerfest Strom 1000, 1 MW Atlantis AR1000, 1MW EvoPod, Currently 10kW 25

26 21 st Century Tidal Devices >50 TSD technologies around the world, few will be viable. TSDs can be horizontal, vertical turbines or oscillating hydrofoils. Which is the most reliable architecture? Reference 8 26

27 What s the Predicted Failure Rate Number of subsystems Total number of subsystems s per device (Nss) Device 3, 100% power Device 1, 100% power Device 2, 50% power Device 4, 50% power Device 2, 100% power Device 4, 100% power Subsystems (Nss) Reference 8 27

28 What s the Predicted Failure Rate Total number of subsystems s per device (Nss) Device 3, 100% power Device 1, 100% power Failure Rate Estimates 1 year operation Device 2, 50% power Device 4, 50% power Device 2, 100% power Device 4, 100% power Subsystems (Nss) Alternative Alternative Reference Total Failure rates per device (Failures/year) Measured λ working WTs same size 28

29 How Many Survive in the Water Reference 8 29

30 Reliability Model for TSD 1 Predicted failure frequancy/deviee/year λtfi (Failures/year) TSD 1 critical subassemblies Subassemblies Reference 9 30

31 TSD 2 Reliability Model Comparison between predictions & reality Reference 9 31

32 Conclusions WT reliability is improving Offshore WT reliability is < onshore Subassemblies with high failure rates are consistent Downtime or MTTR and cost are also important Failure rates of subassemblies can improve with time Offshore availability A i is worse than onshore WT experience can be mapped onto Tidal Turbines Current predicted Tidal Turbine reliabilities are poor Predicted Wave Device reliabilities will also be poor Wave & Tidal Device reliabilities need to be improved We need to concentrate on: Introduce redundancy; Remove or relocate high risk components; Review reliability during design; Pre-test components and sub-assemblies before putting them to sea. 32

33 Thank you 1. Polinder, H. van der Pijl, F F A, de Vilder, G J, Tavner, P J (2006) Comparison of direct-drive and geared generator concepts for wind turbines, IEEE Trans Energy Conversion, 21(3): ; 2. Tavner, P J, Edwards, C, Brinkman, A, Spinato, F (2006) Influence of wind speed on wind turbine reliability, Wind Engineering, 30(1):55 72; 3. Ribrant, P J J, Bertling L M (2007) Survey of failures in wind power systems with focus on Swedish wind power plants during , IEEE Trans Energy Conversion, 22(1): ; 4. Hansen, A D, Hansen, L H (2007) Wind turbine concept market penetration over 10 years ( ), Wind Energy, 10(1):81 97; 5. Tavner, P J, Xiang, J P, Spinato, F (2007) Reliability analysis for wind turbines, Wind Energy, 10(1): 1 18; 6. Spinato, F, Tavner, P J, van Bussel, G J W, Koutoulakos, E (2009) Reliability of wind turbine subassemblies, IET Renew Power Gen, 3(4): ; 7. Arabian-Hoseynabadi, H, Tavner, P J, Oraee, H (2010) Reliability comparison of direct-drive and geared-drive wind turbine concepts, Wind Energy, 13(1): 62-63; 8. Feng, Y, Tavner, P J, Long, H (2010) Early Experiences with UK Round 1 Offshore Wind Farms, Invited Paper, Proceedings of the Institution of Civil Engineers, Energy, 163(4): ; 9. Tavner, P J, Faulstich, S, Hahn, B., van Bussel, G J W (2011) Reliability and availability of wind turbine electrical and electronic components, Invited Paper, EPE Journal, 20(4); 10. Faulstich, S, Hahn, B, Tavner, P J (2011) Wind turbine downtime and its importance for offshore deployment, Wind Energy 14(3): ; 11. Qiu, Y, Feng, Y, Tavner, P J, Richardson, P, Erdos, G, Chen, B D (2012) Wind turbine SCADA alarm analysis for improving reliability, Wind Energy 15 (8), ; 12. Feng, Y, Qiu, Y, Crabtree, C J, Long, H, Tavner, P J (2012) Monitoring wind turbine gearboxes, Wind Energy 16 (5): ; 13. Djurovic, S, Crabtree, C J, Tavner, P J, Smith, A.C (2012) Condition monitoring of wind turbine induction generators with rotor electrical asymmetry, IET Renew. Power Gener., 6(4): ; 14. Tavner, P J, Greenwood, D M, Whittle, M W G, Gindele, R, Faulstich, S, Hahn, B (2012) Study of weather & location effects on wind turbine failure rates, Wind Energy 16(2): ; 15. Tavner, P J (2012) Offshore Wind Turbines-Reliability, Availability & Maintenance, IET Energy; 16. Whittle, M W G, Trevelyan, J, Shin, W, Tavner, P J (2013) Improving wind turbine drive-train bearing reliability through pre-misalignment, Wind Energy; 17. Whittle, M W G, Trevelyan, J, Tavner, P J (2013) Bearing currents in wind turbine generators, Journal of Renewable & Sustainable Energy, 5, ; 18. Zappalá, D, Tavner, P J, Crabtree, C. J, Sheng, S (2014) Side-band algorithm for automatic wind turbine gearbox fault detection and diagnosis, IET Renew Power Gen, in Press; 19. Zaggout, M, Tavner, P J, Crabtree, C J, Ran, L (2014) Wind turbine doubly-fed induction generator rotor electrical asymmetry detection, IET Renew Power Gen, under review; 20. Chen, B D, Matthews, P C, Tavner, P J (2014) Automated wind turbine pitch faults prognosis based on SCADA data using an a-priori knowledge-based ANFIS, IET Renew Power Gen, in print; 21. Mott Macdonald Report: UK Electricity Generation Costs Update, Please register to download the following reports: Survey of CMS Systems; Survey of SCADA Systems; 23. Stiesdal, H, Madsen, P H (2005) Design for reliability, European Offshore Wind Conference, Copenhagen. 33