Leergang offshore wind Uitdagingen in de logistiek Prof.dr. Ruud - - PowerPoint PPT Presentation

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faculteit economie en bedrijfskunde vakgroep operations

14-11-2019

Leergang offshore wind

Uitdagingen in de logistiek Prof.dr. Ruud Teunter

• Dr. Jasper Veldman

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Offshore logistics network

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Port facilities

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Spare parts

 Infield cables  Export cables  Turbine blades  Turbine components  Spare turbines

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Transport

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Transport

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The main players in O&M

(S)LSP = (specialist) logistics service providers, OWF = offshore wind farm, OEM = original equipment manufacturer IMSP = independent maintenance service provider

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Some basic principles

› A service provider uses a mix of maintenance policies:

• Corrective (run-to-failure)
• Calendar-based
• Condition-based

› Different jobs, different turbine components, different vessels › Importance of weather restrictions

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Our focus

Offshore wind – O&M overview

Strategic Tactical Operational

Offshore wind process Planning horizon level

Maintenance Logistics Installation

• Turbine layout design
• Wind park dimensioning
• Fleet size and mix
• Warehouse location
• Environment forecasting
• Maintenance policy optimization
• Vehicle routing
• Spare part distribution and collection
• Scheduling maintenance tasks
• Routing technicians
• Master distribution plan
• Spare parts inventory policies

Human resource capacity planning

• Spares supplier selection
• Contracts definition

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TACTICAL MAINTENANCE JACK-UP VESSEL DEPLOYMENT

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The setting

› Jack-ups needed for large component replacements (e.g., blades) › Short term chartering costs are immense › Logistics-related delays drastically raise costs

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Cooperation options

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Vessel sharing

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Vessel sharing

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TACTICAL LOGISTICS SPARE PARTS MANAGEMENT (ON AN SOV)

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Service Operations Vessel

https://www.youtube.com/watch?reload=9&v=lk_ww_ynWh4

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• Offshore for 2 to 3 weeks
• Can host tens of workers
• Small repair shop
• Small crane
• Electronic gangway system
• Helicopter deck
• Carries spare parts or

subassemblies for

• Hydraulics
• Generator
• Gearbox
• Electric system

Service Operations Vessel

Characteristics

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SOV Kit

› Goal: find (nearly) optimal SOV stock › Determine the probability that (the n-th) part of some type is needed on a tour › Calculate the ratio of that probability and the cost price

• f a part

› Rank parts based on the ratio (high to low) and add parts to the stock in this

• rder

› Easily done in Excel

What to bring offshore?

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TACTICAL MAINTENANCE (AND PRODUCTION) GET VESSELS, PARTS, TOOLS AND TECHNICIANS READY

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Smart supply chain

Internet of Things (IoT)

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Wind turbine sensoring

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Condition monitoring

Condition-based maintenance

› Condition data (Big data) › Condition information (analytics, data mining) › Condition-based maintenance

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Weather Technicians Spare parts Tools lead time

Condition-based production

› Maintenance planning lead time › Control of the production rate

Condition monitoring

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Smart production & SC

› Variable production speed › Higher production speed leads to more vibration and higher temperatures › Trade-off: production versus deterioration

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Smart production & SC

A block diagram of a wind turbine system (ABB, 2011)

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Decelerate Decrease risk of failure Accelerate Increase production

The single turbine case

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extra production

Cost reduction 10% -- 20%

Win-win scenario

› Lower maintenance cost and lower production losses

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Two turbines (high maintenance setup costs)

› Better to maintain both wind turbines at the same time › Set higher production rate for less deteriorated turbine

Deterioration processes of turbines are much better synchronized

Constant, equal production rates Condition-based production rates

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OPERATIONAL MAINTENANCE SCHEDULING TASKS GIVEN VESSELS, PARTS, TOOLS AND TECHNICIANS

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Scheduling inputs

› Maintenance tasks

• Service time, number of technicians, type of technicians, spare

parts (kg) › Availability of technicians in the harbor › Fleet

• Capacity for personel, spare parts, speed, costs, heterogenous

› Weather conditions

• How long can a particular vessel type work during a period

› Set of periods available for scheduling tasks

Maintenance tasks Technicians Repair or inspection? Fleet

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Scheduling algorithm

Minimize total costs: › Fuel/transportation costs › Technician costs (cost per day) › Maintenance costs Balancing act between 1) Vessel moves with technicians (fewer technicians needed) 2) Vessel picks up and delivers technicans between turbines (fewer vessel trips and lower fuel costs)

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Scheduling outcomes

Scheduling algorithm Transportation (fuel) costs Technician costs Maintenance costs

Plan tasks Plan technicians Select and route vessels Maintenance tasks Technicians Repair or inspection? Fleet

• Efficiency, cost reduction
• Better use of technicians
• Reduced mean time to maintenance
• Fewer vessel trips

Benefits:

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COMBINED INSIGHTS: SIMULATION TOOL

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Simulation tool modules

Turbine Model

1

• Deterioration process
• Power generation
• Service demands
• State inspection

Weather Model

2

• Wind speeds
• Temperature
• Rain
• Wave heights

Maintenance

3

• Maintenance policies
• Preventive maintenance
• Corrective maintenance
• Repair kit problems

Logistics

4

• Vehicle routing
• Inventory management
• Technician scheduling

Dashboard

5

• Performance measures
• Planning suggestions
• Excel reports

To be developed in AnyLogic Simulation Software

Purely simulation Simulation and optimization Analytics and data visualization

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Screenshots

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STRATEGIC MAINTENANCE CONTRACTING

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Contracting & collaboration

OEM Service Provider Owner

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Maintenance contract?

› Wind turbines are often sold with two or five years of warranty › Question: › Should the buyer/owner of wind turbines directly sign a long-term maintenance contract with the OEM (bundling) or not (un-bundling)?

20 yrs auction auction OEMi OEMi OEMi or OEMj

bundling unbundling

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Critical tradeoffs

› Two features of the maintenance industry:

• OEM's learning-by-doing: maintenance cost

decreases over time

• Competitive market: more independent

service providers than OEMs › Trade-off owner: A long term contract

• always takes advantage of the OEM's

learning-by-doing and motivates the OEM to invest in turbine reliability, but

• foregoes the chance to choose a more

efficient provider

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Some findings

Bundling (1 contract) Unbundling (2 contracts)

Investment in turbine reliability Learning-by-doing  turbine reliability Owner’s cost Few service providers Strong learning Owner’s cost Many service providers Weak learning

Making a mess for

• thers

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BEYOND OFFSHORE WIND

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Smart Grids in City Areas

http://smarthome.lisha.ufsc.br/index.php/Main_Page

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Energy storage: balancing smart grids

http://www.powermatchingcity.nl

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Energy storage management

› Integration with renewable resources such as wind and solar power › Integration with natural gas grid › Buffer to balance fluctuating consumption and generation

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Research questions

› How to deploy and control energy storage units to improve system performance?

• Where to install the conversion and storage

units?

• How to dimension these units?
• What is the optimal control policy?

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Questions?