Optimal floating offshore wind farms for Mediterranean islands

被引:4
|
作者
Faraggiana, E. [1 ]
Ghigo, A. [1 ]
Sirigu, M. [1 ]
Petracca, E. [1 ]
Giorgi, G. [1 ]
Mattiazzo, G. [1 ]
Bracco, G. [1 ]
机构
[1] Polytech Univ Turin, Dept Mech & Aerosp Engn, I-10129 Turin, Italy
关键词
Renewable energy; Wind farm; Offshore; Floating platform; Optimisation; PARTICLE SWARM OPTIMIZATION; LAYOUT OPTIMIZATION; RENEWABLE ENERGY; TURBINES; PLACEMENT; POWER; DESIGN;
D O I
10.1016/j.renene.2023.119785
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 will play an important role in achieving the Green Deal's goals of green transition and renewable energy generation. The European Union (EU) has launched an initiative to support a clean energy transition towards sustainable and renewable energy production in the EU islands. In fact, the Mediterranean islands obtain most of their energy supply from imported fossil fuels, making electricity costs generally very high due to their remote location. In this paper, we compare the optimal offshore wind farm layout, type and number of wind turbines for four selected sites next to Mediterranean islands. Each layout is evaluated in terms of levelised cost of energy, taking into account aerodynamic wake and transmission losses in the productivity estimation and a detailed cost model. Aerodynamic losses are modelled using a Jensen kinematic wake model and an area overlapping model to consider partial wake shadowing between wind turbines, while transmission losses are estimated as Ohmic losses of the inter-array and export transmission cables. Compared to the state-of-the-art PyWake code, the in-house MATLAB wake model demonstrated higher computational efficiency and is integrated into an efficient optimisation algorithm consisting of several iterations of the Interior-point optimisation algorithm. Results show that offshore wind turbines can provide renewable energy at a competitive price, especially at the most energetic site with an LCOE about 80 euro/MWh. The normalised optimal LCOE and capacity factor as a function of the number of wind turbines are not significantly influenced by the chosen location and reach a maximum difference of 2-3 %, showing that they mainly depend on the type of wind turbine. The lowest optimal LCOE depending on the number of wind turbines is reduced by about 10 % and 25 % by the higher rated wind turbine.
引用
收藏
页数:16
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