Abstract
The wind farm layout optimization problem is concerned with the optimal location of turbines within a fixed geographical area to maximize energy capture under stochastic wind conditions. Previously it has been modelled as a maximum diversity (or p-dispersion-sum) problem, but such a formulation cannot capture the nonlinearity of aerodynamic interactions among multiple wind turbines. We present the first constraint programming (CP) and mixed integer linear programming (MIP) models that incorporate such nonlinearity. Our empirical results indicate that the relative performance between these two models reverses when the wind scenario changes from a simple to a more complex one. We also propose an improvement to the previous maximum diversity model and demonstrate that the improved model solves more problem instances.
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Zhang, P.Y., Romero, D.A., Beck, J.C., Amon, C.H. (2013). Solving Wind Farm Layout Optimization with Mixed Integer Programming and Constraint Programming. In: Gomes, C., Sellmann, M. (eds) Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems. CPAIOR 2013. Lecture Notes in Computer Science, vol 7874. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38171-3_19
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DOI: https://doi.org/10.1007/978-3-642-38171-3_19
Publisher Name: Springer, Berlin, Heidelberg
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