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Innovative Autonomously-Driven Offshore Wind Turbines: a Pre- Feasibility Analysis

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Innovative Autonomously-Driven Offshore Wind Turbines: a Pre- Feasibility Analysis Innovative Autonomously-Driven Offshore Wind Turbines: a pre- feasibility analysis DTU Electrical Engineering Department of Electrical Engineering Xavier Martínez Beseler Kongens Lyngby, August 2019 Innovative Autonomously-Driven Offshore Wind Turbines: a pre- feasibility analysis February 2019 - August 2019 Author: Xavier Martínez Beseler Supervisor: Spyros Chatzivasileiadis Cover illustration: Cèlia Císcar DTU Electrical Engineering Department of Electrical Engineering Technical University of Denmark Ørsteds Plads Building 348 2800 Kongens Lyngby, Denmark Phone +45 4525 3800 [email protected] www.elektro.dtu.dk i Abstract This M Sc Thesis describes a disruptive technology inexistent up to date envisioned by the author of this M Sc Thesis called “Autonomously-Driven Off- shore Wind Turbines” (ADO-WTs). Two integrated models independent from each other plus a costs analysis pave the way for future research. The two models presented are the Wind Energy Yield Assessment model and the Power Losses model. The Wind Energy Yield Assessment model constitutes three models used to quantify potential benefits from moving wind turbines (WTs) on the North Sea: the first model is the reference to assess the extra energy from theother two. The second model sets an upper bound for the proposed technology and the third represents a more realistic implementation. Neither of these models account for the energy losses required to move the WTs nor model the energy system storage. Results for a simulation ran in the Southern North Sea for the whole 2018 historical data shown 45.19% of extra AEP for Upper-Bound model, and 20.98% for Reachable Area model, both compared with the energy produc- tion based on the Conventional model, which was verified based on results from other research. A review of the current State of Art of Energy Storage System (ESS) is shown and three ESS technologies were found suitable for being installed aboard moving wind turbines: Li-ion batteries, Hydrogen and Zinc-Air batteries. The Power Losses model accounts for power required to move ADO-WTs on the sea. A simple catamaran hull to ensure buoyancy was designed for each technology. Results show Hydrogen to be the lightest technology providing the least power losses profile followed by Zinc-Air batteries. Moreover, because of moving the whole system, the wind turbine can work for a wider range of free wind speeds, able to produce at rated power for free wind speeds up to 31m/s for LH2 ADO-WTs, without increasing loads on the blades or rotor. Moreover, optimal boat speeds are shown for each free wind speed and technology. A cost analysis was carried out with huge limitations regarding data avail- ability. Five cases were analysed: a conventional wind farm with an offshore substation (LCOE = $88.34/MW h), ADO-WTs wind farm with an offshore terminal for both ADO-WTs with hydrogen as ESS (LCOE = $104.81/MW h) and Li-ion batteries (LCOE = $3, 774/MW h) and ADO-WTs wind farm with an onshore terminal for hydrogen (LCOE = $99.37/MW h) and Li-ion batteries (LCOE = $3, 767/MW h). ii Acknowledgements First of all, I want to thank Spyros Chatzivasileiadis to believe in my idea from day one when I went to his office and he immediately said he wanted to supervise my work. I am immensely grateful to him for giving me freedom and respecting my decisions on what to research, for giving me advice when I needed it and opening me the door to his network, for instance, to the first meeting of the North Sea Energy Hub Steering Committee where my idea was pitched and I could get feedback from industry. I could not have carried out my works on Naval Architecture without the priceless help of Harry Bingham, who carries with the best attributes a professor cut have. Spending a Friday evening at DTU enlightening me about the world of Archimedes and Froude, for providing me with literature and precise advice as well as for looking after my calculations and foremost, for sharing such positive energy! I also want to thank my friend Andreu Micó for giving me clearly explanations and introducing me to the romantic and archaic jargon of Maritime Engineers. In addition, I give thanks to Manuel Ventura for sharing his estimations for calculating ship costs. People from DTU Wind helped me in several steps of my work. I want to thank Bjarke Tobias Olsen for recommending me the dataset I used to prove my idea. Martin Otto helped me formulating the Power Loss model to which I am truly thankful. Henrik Bredmose was the first who told me about the people from Cen- tral Nantes to whom I exchanged ideas. Thanks in particular to Roshamida Abd Jamil and Aurelien Babarit to share their literature and key findings and for their inspiring work: I give my best wishes to your future findings! I want to thank Fitim Kryezi, Project Manager at Energinet, his inputs and feedback helped me improving my concept and his tireless enthusiast gave me ex- tra energy to bring my idea one step forward. He also connected me with Martin Hartvig Senior Engineer at Energinet who provided me specific knowledge of Power to Gas applications, dreamed with me and gave me invaluable inputs for my ESS analysis both in costs and technology. In general, I have the feeling that people work- ing at Energinet share a huge enthusiasm and willingness to find new solutions and bet on R&D: thanks for that, keep that spirit! iv Acknowledgements Thanks to David Johnsen, Senior Director of COP, who provided me detailed and customized information of how cable arrays are designed in offshore wind farms. I also want to thank to Magdalena Zajonc Business Developer at Peak Wind, who shown a special interest on my idea and contribute with her knowledge to my costs approach providing me some literature and interesting discussions. Thanks to Morten Nielsen from Ørsted who listened to my idea, gave me posi- tive feedback, completely new inputs and cheered on me to keep exploring this idea. In addition, I give thanks to Lucas Marion, R&D Roadmap Manager at Ørsted, who thought over my idea with criticism and shared with me the weak points he saw on my concept. It was really important to me that the uncertainties I foresaw on my concept were shared by those working in R&D at the world’s leading company for offshore wind development. Also, thanks to Bruno Kotovich, Project Manager from Vestas, who always ex- presses interest on what I am working on and shows a willing to share his knowledge with me. I want to thank in general workers from industry to spend some time thinking out of the box and giving constructive feedback to my idea. I have no doubt that the involvement of such renown companies provides my work with a more complete analysis. Please keep giving feedback to future students! The cover illustration was created by my old friend Cèlia Císcar. Núria Martínez and Dani Catalán also contributed in the process. I am immensely thankful to all of them, for allocating part of their time to translate my drafts into such a beautiful piece of art! Finally, thanks to my colleague and good friend Jorge Izquierdo who saved me a lot of time with the LaTeX template and, in general, to all my class mates and friends who throughout informal conversations helped me maturing the idea: let’s never stop dreaming together! Contents Acknowledgements iii Contents v List of Figures vii List of Tables ix Nomenclature xi 1 Introduction 1 1.1 Introduction to the concept ........................ 3 1.2 Approach .................................. 6 1.3 Structure of the report ........................... 8 2 Review of the current Offshore Wind Power 9 2.1 Bottom-Fixed Offshore Wind (BFOW) - Current numbers and trends 10 2.2 Floating Offshore Wind (FOW) ...................... 12 2.3 Similar Studies ............................... 15 2.4 Challenges for Offshore Wind: potential of ADO-WTs ......... 17 3 Wind Energy Yield Assessment model. Methodology & Results 19 3.1 Wind Energy Yield Assessment model. Method ............. 20 3.2 Wind Energy Yield Assessment model. Results ............. 38 3.3 Final Results ................................ 48 4 Energy Storage System 57 4.1 Energy Storage System – Methodology .................. 57 4.2 Energy Storage System – State of Art .................. 58 4.3 Energy Storage System – Selection of best technologies ......... 66 5 Power Losses model 71 5.1 Power Losses. Methodology ........................ 71 5.2 Power Losses. Results ........................... 80 vi Contents 6 Cost Analysis 93 6.1 Costs Analysis. Methodology ....................... 94 6.2 CAPEX ................................... 99 6.3 OPEX .................................... 106 6.4 Costs Analysis. Results and discussion .................. 109 7 Conclusions 117 7.1 Conclusions ................................. 117 7.2 Future work proposed ........................... 118 Bibliography 121 A Appendices Wind Energy Yield Assessment -Code 125 A.1 General Parameters ............................ 125 A.2 main ..................................... 126 A.3 updateVar .................................. 129 A.4 Vo2E ..................................... 131 A.5 getArea ................................... 132 A.6 getB ..................................... 134 A.7 getZ ..................................... 135 A.8 getIntersection ............................... 136 A.9 getLonLatInterp .............................. 137 A.10 interpWS .................................. 139 A.11 getLonLanInterp .............................. 139 B Appendices Wind Energy Yield Assessment -Results 141 B.1 Interpolation
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