A neighborhood search integer programming approach for wind farm layout optimization

Two models and a heuristic algorithm to address the wind farm layout optimization problem are presented. The models are linear integer programming formulations where candidate locations of wind turbines are described by binary variables. One formulation considers an approximation of the power curve by means of a stepwise constant function. The other model is based on a power-curve-free model where minimization of a measure closely related to total wind speed deficit is optimized. A special-purpose neighborhood search heuristic wraps these formulations with increasing tractability and effectiveness compared to the full model that is not contained in the heuristic. The heuristic iteratively searches for neighborhoods around the incumbent using a branch-and-cut algorithm. The number of candidate locations and neighborhood sizes are adjusted adaptively. Numerical results on a set of publicly available benchmark problems indicate that a proxy for total wind speed deficit as an objective is a functional approach, since high-quality solutions of the metric of annual energy production are obtained when using the latter function as an substitute objective. Furthermore, the proposed heuristic is able to provide good results compared to a large set of distinctive approaches that consider the turbine positions as continuous variables.</p

Enabling power system transformation globallya system operator research agenda for bulk power system issues

The primary objective of a power system is to safely provide reliable energy services to society at an affordable cost. In many countries, this objective has been supplemented by another: meeting the energy demand with sustainable resources, which has culminated in the energy transition to low-carbon and zero-carbon energy systems. This transition, occurring rapidly around the world, is characterized by the increasing penetration of variable renewable energy (VRE), inverter-based resources (IBRs), and distributed energy resources (DERs)