Presentations

Abstract

Wind farm operation faces challenges of noise compliance, particularly when co-located with other energy sources that emit noise such as PV plants and batteries. This study presents an innovative noise curtailment optimizer designed to maximize energy output while meeting regulatory noise limits. The optimization approach differs from traditional curtailment methods by accommodating diverse noise models, accounting for weather variability, and managing complex turbine interactions. Additionally, it addresses the challenge posed by co-located energy infrastructure, which compete for noise budgets, constraining the flexibility in minimizing production loss. The proposed method aims to demonstrate that the consideration of co-location scenarios can be essential for an economic viability analysis of a wind farm project when competing for a common noise budget. This research utilizes a two-phase heuristic optimization framework to tackle the turbine curtailment problem, which is NP-hard. First, a global search employing a noise-violation-per-production-gradient metric evaluates operational strategies to balance noise compliance against energy output. The second phase refines the identified candidate solutions through local neighbourhood optimization. The method incorporates various acoustic propagation models (ISO 9613-2, NORD2000), accounts for non-linear wake effects, and adjusts for meteorological changes across different operational modes. Key to this study is addressing co-location complexities, ensuring turbines navigate shared noise budgets effectively amongst all noise-emitting sources, including additional infrastructure in hybrid energy setups. We analyse the interaction of external noise levels with the reduced AEP that comes with more curtailed wind farms. The application of this optimization method reveals that with the added noise from co-located sources, the curtailment optimizer has restricted flexibility to achieve maximum annual energy production solutions. The competition for allowable noise levels from various energy-producing plants is especially strong when both turbines and other noise sources are noisy on the low frequency end of the spectrum. The study underscores a balance is often achievable but depends strongly on the noise constraints of the project. The studied optimization algorithm is effective in complex co-location scenarios, allowing wind farm operators to maximize energy production while adhering to noise regulations. It demonstrates that even when integrating other noise-producing installations, it's possible to maintain regulatory compliance. The potential increase in production through optimized noise management can significantly enhance the business case for wind farms in noise-sensitive environments, opening opportunities for co-located energy production. The work was conducted within the DECOWIND project with contributions from DTU, Siemens Gamesa Renewable Energy, FORCE Technology, and EMD International A/S.