Minimizing Levelized Cost of Energy and visual impact in Mediterranean offshore wind farms: A multi-objective optimization approach

Offshore wind farms are emerging as a key power plant option for EU’s transition to net-zero emissions by 2050. With the growing trend of installing large turbines in multi-gigawatt farms, increasing attention is being given to the visual impact perceived from the coast. This study introduces an optimization method that incorporates visual impact as a social-acceptance indicator and the Levelized Cost of Energy to provide a comprehensive techno-economic sustainability assessment for offshore wind projects. The method resolves a multi-objective and multi-constrained wind farm layout optimization problem in a designated marine area. The number of turbines is one of the independent variables in each studied wind farm and multiple points of observation from the shoreline are contributing to the evaluation on visual impact. The case study is represented by a virtual wind farm located in the Mediterranean Sea, with 15 MW turbines. The results yield a Pareto front, with the trade-off solution represented by a farm with 13 turbines, distributed regularly, and a Levelized Cost of Energy of 110.73 €/MWh. Additionally, four comparative analyses are performed to evaluate the effect of (i) different turbine sizes, (ii) different wake loss models, (iii) different wind data source and (iv) different wind farm areas. • Multi-objective wind farm layout optimization using genetic algorithm. • Visual Impact accounts for rotor orientation and multiple observers’ location. • Gaussian Curl Hybrid model estimates wake losses and energy yield. • Regular layouts reduce visual impact, irregular layouts improve energy yield. • Impact of wake models, turbine sizes, wind data sources and project sizes evaluated.