The properties of the global offshore wind turbine fleet

被引:13
作者
Jung, Christopher [1 ]
Schindler, Dirk [1 ]
机构
[1] Univ Freiburg, Environm Meteorol, Werthmannstr 10, D-79085 Freiburg, Germany
关键词
Wind power; Offshore wind resource; Water depth; GIS; ERA5; DECISION-ANALYSIS; SITE SELECTION; ENERGY; GIS; DISTRIBUTIONS; SYSTEM; CHINA; GULF;
D O I
10.1016/j.rser.2023.113667
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Offshore wind capacity increased massively in recent years. Sufficient wind potential must be available to realize the ambitious goals regarding further wind capacity expansion. Thus, the goal of this study is to quantify the meteorological, geographical, and technical properties of the current global offshore wind turbine fleet. The offshore wind turbine fleet is classified by twelve factors that belong to meteorological, geographical, and technical factor categories. A comprehensive wind turbine site dataset is evaluated, including 5473 sites in Europe and 3404 in Asia. The factors at the wind turbine sites are derived using publicly available datasets, including a reanalysis wind speed dataset, geodata, and technical properties. The results of this study are that the global median (1) wind speed is 8.7 m/s, (2) water depth is 17 m and (3) distance to shore is 27 km. The distance to the nearest wind turbine is 5.1 times the rotor diameter. The factors studied have a high regional variability. While Asian offshore wind turbines operate in shallower water closer to the shores than European, European wind turbine sites provide higher wind resources. The regional differences indicate that the wind potential and wind turbine siting criteria differ depending on the country. The factor values obtained are reference values for future offshore wind resource assessments and estimates of the wind potential from a regional to global scale.
引用
收藏
页数:13
相关论文
共 53 条
  • [41] Spatial planning to estimate the offshore wind energy potential in coastal regions and islands. Practical case: The Canary Islands
    Schallenberg-Rodriguez, Julieta
    Garcia Montesdeoca, Nuria
    [J]. ENERGY, 2018, 143 : 91 - 103
  • [42] Global offshore wind energy resources using the new ERA-5 reanalysis
    Soares, Pedro M. M.
    Lima, Daniela C. A.
    Nogueira, Miguel
    [J]. ENVIRONMENTAL RESEARCH LETTERS, 2020, 15 (10)
  • [43] Regulatory aspects and electricity production analysis of an offshore wind farm in the Baltic Sea
    Sobotka, Anna
    Rowicki, Marcin
    Badyda, Krzysztof
    Sobotka, Piotr
    [J]. RENEWABLE ENERGY, 2021, 170 : 315 - 326
  • [44] Spatial energy planning of offshore wind farms in Greece using GIS and a hybrid MCDM methodological approach
    Spyridonidou, Sofia
    Vagiona, Dimitra G.
    [J]. EURO-MEDITERRANEAN JOURNAL FOR ENVIRONMENTAL INTEGRATION, 2020, 5 (02)
  • [45] Statistical BP, 2022, Review of world energy
  • [46] TeleGeography, 2022, Submarine Cable Map
  • [47] GIS-based multi-criteria decision analysis for site selection of hybrid offshore wind and wave energy systems in Greece
    Vasileiou, Margarita
    Loukogeorgaki, Eva
    Vagiona, Dimitra G.
    [J]. RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2017, 73 : 745 - 757
  • [48] A macroscale optimal substructure selection for Europe's offshore wind farms
    Vazquez, Asier
    Izquierdo, Urko
    Enevoldsen, Peter
    Andersen, Finn-Hendrik
    Blanco, Jesus Maria
    [J]. SUSTAINABLE ENERGY TECHNOLOGIES AND ASSESSMENTS, 2022, 53
  • [49] Assessment of surface wind datasets for estimating offshore wind energy along the Central California Coast
    Wang, Yi-Hui
    Walter, Ryan K.
    White, Crow
    Farr, Hayley
    Ruttenberg, Benjamin I.
    [J]. RENEWABLE ENERGY, 2019, 133 : 343 - 353
  • [50] Wikiwand, 2022, OFFSH WINDP