Presentations

Abstract

Wind farm layout optimization must often comply with regulatory limits on noise. This work investigates how search space formulation affects optimization performance in such scenarios. We compare three approaches: a discrete (grid-based) layout optimization, a continuous layout optimization, and a joint layout plus operation mode optimization. The discrete grid approach restricts turbine positions to a finite set of predefined points, simplifying the search and accelerating convergence, but potentially missing optimal configurations. The continuous approach allows turbines to be placed anywhere in the area, better representing the true allocation problem at the cost of an infinitely large decision space. The joint layout and curtailment optimization combines a layout and operation mode optimization, which significantly expands the feasible solution space. Joint optimization of wind‑farm layout and curtailment strategy enlarges the feasible design space by coupling turbine placement with operational modes. Prior studies show that this coupling can yield higher‑quality solutions than optimizing either dimension alone. However, the added flexibility increases algorithmic complexity and introduces an additional curtailment decision layer that slows the search. This study quantifies the advantages the method. Using fixed-time optimization runs on test scenarios with varying constraint strengths with different noise receptor counts and allocations, we evaluate performance trends across these search spaces. This study outlines the trade-offs between search space complexity and Annual Energy Production (AEP) under different noise constraint scenarios. This provides insight into which strategy yields the best balance of search efficiency and solution quality for noise-constrained wind farm design. Results demonstrate that continuous formulations consistently outperform grid-based approaches by 2.6% on average on the presented problems, and that joint optimization with curtailment provides additional gains of 3.1%. Each search space formulation offers unique strengths, and no single method is best for all cases. Joint optimization and hybrid sequential strategies achieve especially strong AEP in highly constrained noise scenarios, while continuous and grid-based approaches are favorable first exploration phases.