typically only objective functions such as Annual Energy Production (AEP) are considered
easily causing increased fatigue damages for wind turbines and higher operation and maintenance costs for the wind farm
thus the final layout of wind farm might not be the optimal if the optimization codes don't consider the wind turbines fatigue loads constraint. On account of that
this study proposes practical measures to address this issue. Firstly
the damage equivalent loads are predicted by inputting load surrogates for the effective wind speed and effective turbulence intensity of each wind turbine. After that
the open-source wind farm optimization platform TOPFARM is utilized in this study to optimize the wind farm layout. Furthermore
the constraint is added to limit the Lifetime Damage-equivalent Fatigue Loads (LDEL) of the wind turbines during the optimization process. Finally
this study optimized the layout of Horns Rev 1 wind farm considering constraints on wind turbine fatigue loads
concluding that the optimized wind farm only sacrificed a small amount of AEP in exchange for a significant reduction in LDEL.
KAMAL M, RAHMAN M M.Advances in fatigue life modeling: a review[J]. Renewable and sustainable energy reviews, 2018, 82: 940-949.
ZHAO R Y, SHEN W Z, KNUDSEN T, et al.Fatigue distribution optimization for offshore wind farms using intelligent agent control[J]. Wind energy, 2012, 15(7): 927-944.
COLLET D, ALAMIR M, DI DOMENICO D, et al.A fatigue-oriented cost function for optimal individual pitch control of wind turbines[J]. IFAC-PapersOnLine, 2020, 53(2): 12632-12637.
HUANG L L, TANG H, ZHANG K H, et al.3-D layout optimization of wind turbines considering fatigue distribution[J]. IEEE transactions on sustainable energy, 2020, 11(1): 126-135.
DIMITROV N, KELLY M C, VIGNAROLI A, et al.From wind to loads: wind turbine site-specific load estimation with surrogate models trained on high-fidelity load databases[J]. Wind energy science, 2018, 3(2): 767-790.
RIVA R, LIEW J, FRIIS-MØLLER M, et al. Wind farm layout optimization with load constraints using surrogate modelling[J]. Journal of physics: conference series, 2020, 1618(4): 042035.
STANLEY A P J, KING J, BAY C, et al. A model to calculate fatigue damage caused by partial waking during wind farm optimization[J]. Wind energy science, 2022, 7(1): 433-454.
STANLEY A P J, KING J, NING A. Wind farm layout optimization with loads considerations[J]. Journal of physics: conference series, 2020, 1452(1): 012072.
JONKMAN J, BUTTERFIELD S, MUSIAL W, et al.Definition of a 5-MW reference wind turbine for offshore system development[J]. Contract, 2009(February): 1-75.
GORISSEN D, COUCKUYT I, DEMEESTER P, et al.A surrogate modeling and adaptive sampling toolbox for computer based design[J]. Journal of machine learning research, 2010, 11: 2051-2055.
FRANDSEN S T.Turbulence and turbulence- generated structural loading in wind turbine clusters[D]. Roskilde: Risø National Laboratory, 2007.
BASTANKHAH M, PORTÉ-AGEL F.A new analytical model for wind-turbine wakes[J]. Renewable energy, 2014, 70: 116-123.
KATIC I, HØJSTRUP J, JENSEN N O. A simple model for cluster efficiency[C]//EWEC'86: European Wind Energy Association Conference and Exhibition. Rome, Italy, 1986, 1: 407-410.