Welcome. Analysis, comparison and optimization of the logistical concept for wind turbine commissioning. Dr. Marcel Wiggert

Transcription

1 Welcome Analysis, comparison and optimization of the logistical concept for wind turbine commissioning Dr. Marcel Wiggert

2 Agenda & Goals Topic and challenges Introduction WaTSS concept Approach Case study: Commissioning Conclusions Figure: Florian Meier

3 Topic Title: Analysis, comparison and optimization of the logistical concept for wind turbine commissioning Conditions: Weather risk of the WTG installation Optimization of the number of commissioning teams Comparison of 3 different logistical concepts Decision criteria: lowest cost and risks

4 Challenge WTG i Completion Installation COAST 1 Weather Risks Comparison of logistical concepts Commissioning team optimization WTG i Access for commissioning Commissioning COAST 1 Resource issue 1 COAST Comprehensive Offshore Analysis and Simulation Tool

5 IWES Modeling Approaches VIRTUAL TEST RIGS Cost and Risk Assessment Objective General Tools (e.g. MS-Excel) Project Management Software (e.g. MS-Project) Engineering Tools (e.g. Matlab) Developer Environments (e.g. Java) COAST 1 Transport & installation Commissioning Regular maintenance Large component rep. Decommissioning Offshore TIMES 2 Maintenance logistics 1 COAST Comprehensive Offshore Analysis and Simulation Tool 2 Offshore TIMES Offshore Transport, Inspection an Maintenance Software

6 Information Profile WEATHER CONDITIONS WEATHER PARAMETERS PROJECT SCHEDULES INSTALLATION STRATEGY Local weather conditions, e.g. Significant wave heights Wind speeds Currents Temperature Visibility WEATHER TIME SERIES T&I CONCEPT Required cabling processes and sequences Project overall project time schedule PROJECT SCHEDULES Location wind farm/ ports Vessel and equipment concept Guideline requirements Contractual agreements BOUNDARY CONDITIONS MEASURED HINDCAST RESTRICTIONS GUIDELINES FORECAST PROJECT DURATION WEATHER RISK PROFILE Sensitivity and Scenario Analysis ROBUST PROJECT SCHEDULES CONTINUOUS ANALYSIS PROCESS EASY WORK FLOW INTEGRATION COST AND RISK OPTIMIZATION

7 WaTTS Method Weather Time Series Scheduling Consideration of: Task sequence Contingencies in guidelines Different weather restrictions Calculation of project durations and their probabilities 1/24/2018 7

8 Virtual Project Test Center Yearly Simulation 180 DURATION VS. START DATE DURATION SIGN. WAVE HEIGHT TIME SCALE START DATE: E.G

9 Virtual Project Test Center Continuous Simulation 180 DURATION VS. START DATE 170 DURATION SIGN. WAVE HEIGHT TIME SCALE

10 Duration vs. Start Day PROJECT DURATION P95 P50 P5 JAN. FEB. MAR. APR. MAY JUN. JUL. AUG. SEP. OCT. NOV. DEC. START DATE

11 COAST Software

12 Simulation Concept ANALYZING Weather Risk Installation 1. Installation dates of the wind turbines per analyzed year Goal: Definition commissioning start dates 2. Success of the commissioning work for every day Goal: Definition of the turbine accessibility SCENARIOS LOGISTIC-CONCEPT ANALYZING Weather Risk Commissioning Post Processing Analyzing/ Optimizing 3. Post Processing: e.g., MS Excel or MATLAB Goal: Analyzing the scenarios 1Calculation of the commissioning duration per turbine and year under consideration of weather and resource constraints 2 Calculation of the required vessel days and costs 3Evaluation and presentation of the results COMBINED OPTIM IZATION

13 Case Study: IWES Baltic Introduction OWP IWES Baltic Reference Sassnitz Weather parameters: Significant Wave Height (h S ) Wind Speed (U) IWES OWP Baltic

14 WTG Installation Strategy WTG Installation Strategy only

15 Scenario Analysis SCENARIO CTV SCENARIO HV SCENARIO SOV CREW TRANSFER VESSEL HOTEL VESSEL SERVICE OPERATION VESSEL ASSUMPTIONS H S = 1.5m; 3 Teams on board; 12h/7 days Costs: 4,000 /d 8h/day on turbine H S = 1.5m 20 Teams; 24h/7 days Costs: 20,000 /d 10h/day on turbine H S = 2.5m 20 Teams; 24h/7 days Costs: 24,000 /d 10h/day on turbine

16 Scenario Analysis SCENARIO CTV SCENARIO HV SCENARIO SOV CREW TRANSFER VESSEL HOTEL VESSEL SERVICE OPERATION VESSEL ASSUMPTIONS H S = 1.5m; 3 Teams on board; 12h/7 days Costs: 4,000 /d 8h/day on turbine H S = 1.5m 20 Teams; 24h/7 days Costs: 20,000 /d 10h/day on turbine H S = 2.5m, U = 10 m/s 20 Teams; 24h/7 days Costs: 24,000 /d 10h/day on turbine

17 Case Study: IWES Baltic Results COSTS (P50) RISK PROFILE Costs [Million ] Project duration [days] Base case SOV SOV HV HV NET DURATION CTV CTV SOV HV Number of commissioning teams % CTV SOV-10 HV-12 CTV-14 Risk Spectrum Costs [Million ]

18 Conclusion Costs [Million ] CTV HV SOV Post processing extends capabilities of the WaTSS method Approach to consider the availability of transport (resources) for the commissioning teams Project duration [days] Base case SOV HV NET DURATION CTV SOV HV Number of commissioning teams CTV Important to consider risks and cost simultaneously Case Study: IWES Baltic 1/24/

19 Acknowledgements Fraunhofer IWES is funded by the: Federal Republic of Germany Federal Ministry for Economic Affairs and Energy Federal Ministry of Education and Research European Regional Development Fund (ERDF): Federal State of Bremen Senator of Civil Engineering, Environment and Transportation Senator of Economy, Labor and Ports Senator of Science, Health and Consumer Protection Bremerhavener Gesellschaft für Investitions- Förderung und Stadtentwicklung GmbH Federal State of Lower Saxony Free and Hanseatic City of Hamburg

20 References

21 Thank You For Your Attention Any questions?

22 Background DETAILED INFORMATION

23 Detailed Analysis Bau-Netto Net. time Inbetriebnahme Commissioning WoW Ressources Ressourcen Project duration [days] CTV HV SOV

24 Risk Efficiency RISKPORTRAIT: CUMULATIVE PROBABILITY E WIDTH B D B A EXPECTED VALUE RISKPORTFOLIO: RISK F E D feasible solution area B C A non-feasible solution area RISK-EFFICIENT BOUNDARY (C-F) BASE VALUE EXPECTED VALUE Risk efficiency concept by CHAPMAN/WARD 2003, based on MARKOWITZ portfolio theory Rule: that the investor does (or should) consider expected return a desirable thing and variance of return an undesirable thing (MARKOWITZ 1952, S.77)

25 Primary and Secondary Weather Risks Duration vs. Start Day PROJECT DURATION P95 P50 P5 PROJECT DELAY 4 Months SECONDARY WEATHER RISK APRIL AUGUST PRIMARY WEATHER RISK JAN. FEB. MAR. APR. MAY JUN. JUL. AUG. SEP. OCT. NOV. DEC. START DATE

26 Weather Impact Example Accessibility (July December) 100% h S = 1.5m; Weather Window d= 10h; Data Model: HZG CoastDat v1 ( ) 90% 80% 70% 60% 50% July August September 40% 30% 20% 10% 0% October November December