TY - GEN
T1 - Modelling the Wind Farm Layout Optimization Problem Using Integer Programming
AU - Perez-Rua, Juan-Andres
AU - Cutululis, Nicolaos A.
PY - 2023
Y1 - 2023
N2 - The wind farm layout optimization problem is addressed in this manuscript through the perspective of integer programming. A number of intrinsic modelling benefits are obtained by means of this discrete optimization approach, as for example, possibility to include turbines number and type selection within the program, inclusion of terrain-dependent cost functions, incorporation of any shape for available and forbidden areas or unified optimization with electrical and control systems, among others. Three integer linear programs are presented and compared respect to a highly non-linear true annual energy production metric. All the formulations are wrapped in a neighborhood search heuristic for both accelerating convergence and to correct the optimization search. Two of the models support explicit power curve modelling following discrete sampling techniques of this function, while the last model focuses on minimizing a measure closely related to total wind speed deficit, ignoring the power curves. Numerical results on a benchmark problem indicate that the power-curve-free model outperforms the power-based models in terms of final solution quality.
AB - The wind farm layout optimization problem is addressed in this manuscript through the perspective of integer programming. A number of intrinsic modelling benefits are obtained by means of this discrete optimization approach, as for example, possibility to include turbines number and type selection within the program, inclusion of terrain-dependent cost functions, incorporation of any shape for available and forbidden areas or unified optimization with electrical and control systems, among others. Three integer linear programs are presented and compared respect to a highly non-linear true annual energy production metric. All the formulations are wrapped in a neighborhood search heuristic for both accelerating convergence and to correct the optimization search. Two of the models support explicit power curve modelling following discrete sampling techniques of this function, while the last model focuses on minimizing a measure closely related to total wind speed deficit, ignoring the power curves. Numerical results on a benchmark problem indicate that the power-curve-free model outperforms the power-based models in terms of final solution quality.
U2 - 10.1109/CCTA54093.2023.10252646
DO - 10.1109/CCTA54093.2023.10252646
M3 - Article in proceedings
T3 - 2023 Ieee Conference on Control Technology and Applications (ccta)
SP - 566
EP - 573
BT - Proceedings of 2023 IEEE Conference on Control Technology and Applications (CCTA)
PB - IEEE
T2 - 2023 IEEE Conference on Control Technology and Applications
Y2 - 16 August 2023 through 18 August 2023
ER -