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Optimization of O&M of Offshore Wind

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Optimization of O&M of Offshore Wind FACULTY MECHANICAL, MARITIME AND MATERIALS ENGINEERING Delft University of Technology Department Marine and Transport Technology Mekelweg 2 2628 CD Delft the Netherlands Phone +31 (0)15-2782889 Fax +31 (0)15-2781397 www.mtt.tudelft.nl Specialization: Transport Engineering and Logistics Report number: 2017.TEL.8167 Title: Optimization of O&M of offshore wind farms Author: J.P.R. Triepels Title (in Dutch) Optimalisatie van O&M van offshore windparken Assignment: Literature project Confidential: no Supervisor: Dr. ir. X. Jiang Date: August 1st, 2017 This report consists of 42 pages and 4 appendices. It may only be reproduced literally and as a whole. For commercial purposes only with written authorization of Delft University of Technology. Requests for consult are only taken into consideration under the condition that the applicant denies all legal rights on liabilities concerning the contents of the advice. FACULTY OF MECHANICAL, MARITIME AND MATERIALS ENGINEERING Delft University of Technology Department of Marine and Transport Technology Mekelweg 2 2628 CD Delft the Netherlands Phone +31 (0)15-2782889 Fax +31 (0)15-2781397 www.mtt.tudelft.nl Student: Assignment type: Review Supervisor: Dr.ir. Jiang Report number: 2017.TEL.xxxx Specialization: TEL Confidential: Creditpoints (EC): 10 Subject: Deployment of big data technology to reduce O&M cost of offshore wind Offshore wind is a relatively new industry and in general offshore wind is more expensive to generate than many alternative renewable sources. Operation & Maintenance (O&M) makes up a significant part of the overall cost of running offshore wind turbines. The complication of O&M lies in that its responsibility has been split between turbine manufacturers, wind farm operators and the offshore transmission owners. This has resulted in procedures and systems that have evolved to provide short term solutions. Thus this has inevitably led to areas of inefficiency, duplication of effort and lack of information. Big data technology is one great technologies that will drive future growth. Big data would offer three huge benefits that can transform an industry in terms of visualization of real time data; development of decision support tools based on disparate data sources; and data mining to aid planning and find performance inefficiencies to improve real time operations. It should be noted that even with the data in place, there are several challenges facing converting data into valuable information, such as posing the right question, developing the right software using the right technique to answer the questions, etc. This assignment aims is to investigate the possible impact of big data on O&M of offshore wind turbine in order to answer such questions as whether and how a better collection, management and presentation of data (coupled with an integrated software solution) would provide significant cost reductions in O&M. The following aspects are required to be illustrated in the report: • The definition of big data in context of offshore wind technology • The state of the art – Application of big data in offshore wind industry addressing on - Wind turbine monitoring - Supply chain management - Marine operations - Other aspects, if applicable Including available database, analysis models and methods, software and techniques, etc. • Exploration of future work (remaining issues and possible ways for improvement / solutions) This report should be arranged in such a way that all data is structurally presented in graphs, tables, and lists with belonging descriptions and explanations in text. The report should comply with the guidelines of the section. Details can be found on the website. If you would like to know more about the assignment, you may contact with Dr. X Jiang through [email protected]. X Jiang Abstract Europe is working on a transition to a sustainable, reliable and affordable energy supply for everyone. As de- termined in the Innovation Outlook Offshore Wind (2016) of IRENA (International Renewable Energy Agency) [1] wind power will have to become the leading power generation technology by 2030 to ensure a decar- bonization of the global economy. In order to achieve such growth, the levelized cost of energy (LCOE) needs to be reduced. One of the important factors of the LCOE is operations and maintenance (O&M). Due to the offshore location and the uncertain weather conditions, wind farms at sea have different requirements, chal- lenges and costs compared to onshore wind farms. O&M responsibility is currently split between wind farm owners, turbine manufacturers, offshore transmission owners and sometimes independent service contrac- tors. This makes the already difficult process of operations even more complicated. There is a demand for an approach to make the O&M more effective. Furthermore, the availability of cheap, reliable sensors and the general recognition of the value of data has lead to an explosion in interest in the area of “big data”. Operations and maintenance covers all activities from completion of installation works to the start of decom- missioning. Different stakeholders can have different interests making it sometimes difficult to determine the best strategy. There are three main actors involved: project owners, wind turbine original equipment manufacturers (OEM) and offshore transmission owners (OFTO). Operations and maintenance of offshore wind farms can be categorized into three fields: supply chain man- agement, wind turbine monitoring and marine operations. Supply chain management is the management of all the flows of materials, parts, equipment and storage thereof. There is limited literature available on the topic of supply chain management specifically related to offshore wind farms. Wind turbine monitoring has to do with gathering data on the wind turbine itself for both performance control and condition based maintenance. A lot of research is going in this field at the moment. Marine operations include all operations that are necessary to get workers and equipment to and from the wind farm. Although not much researched, marine operations is also an interesting field for data collection and analysis. The most likely developments in operation and maintenance are in the following areas: improvements in weather forecasting and analysis, introduction of turbine condition-based maintenance strategies, improve- ments in OMS strategy for far-offshore wind farms, improvements in personnel transfer and access, intro- duction of remote and automated maintenance, and introduction of wind farm-wide control strategies. In particular, a lot is expected from the implementation of condition-based maintenance in combination with wind farm-wide optimizing control strategies and the improvements and innovations of the PTVs and SOVs. There have been a few attempts to optimize the maintenance control strategy with the help of an inte- grated system. ECN is an important Dutch organization working on this principle. Other recent projects are DAISY4Offshore and the in start-up phase project ZEPHYROS. ZEPHYROS is a project by World Class Main- tenance trying to bring together relevant actors in the field with researchers, students and local authorities. Projects like these are important in the process of innovation. By working together on improvements, Europe will only have the leading role, but also keep this leading role. v Contents 1 Introduction 1 2 Offshore WIND IN The Netherlands3 2.1 Current situation.........................................3 2.2 Roadmap to 2023.........................................3 3 Offshore WIND OPERATIONS AND MAINTENANCE5 3.1 Stakeholders...........................................5 3.1.1 Contracting types.....................................5 3.2 Activities.............................................6 3.2.1 Operations.........................................6 3.2.2 Maintenance........................................6 4 Role OF BIG DATA IN OFFSHORE WIND9 4.1 Supply chain management....................................9 4.1.1 Supply chain in offshore wind industry..........................9 4.1.2 Purchasing and supply management practices....................... 10 4.1.3 Supply chain assessment The Netherlands......................... 10 4.1.4 Big data in supply chain management........................... 11 4.2 Wind turbine monitoring..................................... 12 4.2.1 Wind Turbine Maintenance................................ 12 4.2.2 Monitoring system: CMS.................................. 12 4.2.3 Monitoring system: SCADA................................ 13 4.2.4 Opportunities....................................... 13 4.2.5 Big data in wind turbine monitoring............................ 14 4.3 Marine operations........................................ 15 4.3.1 Offshore logistics...................................... 15 4.3.2 Case study by UEA..................................... 15 4.3.3 Operations at Gemini................................... 16 4.3.4 Opportunities....................................... 17 4.3.5 Big data in marine operations............................... 18 5 Projects ON OPTIMIZING CONTROL STRATEGIES 19 5.1 ECN................................................ 19 5.2 Decision support tool by H. Koopstra............................... 19 5.3 World Class Maintenance..................................... 20 5.3.1 DAISY and DAISY4Offshore................................ 21 5.3.2 ZEPHYROS......................................... 21 6 Conclusions & FUTURE WORK 23 6.1 Conclusions...........................................
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