Wind-farm decision-making increasingly requires balancing energy yield and economic value against structural fatigue and component wear, across operating strategies and site-dependent conditions. This paper presents a modular, open-source methodology for wind-farm health evaluation that couples operational strategies with wake-aware farm response prediction and surrogate-based turbine response. The framework is designed to accommodate interchangeable, multi-fidelity model components for intra-farm flow, turbine inflow representation, and turbine response under different control and operational states, while maintaining a unified evaluation workflow. To enable consistent comparisons across strategies and sites, turbine-level outputs are mapped to relative metrics using explicit baseline budget definitions and are further condensed into a small set of farm-level indicators on a system level. These condensed metrics provide a practical basis for decision support and offer an interface for optimization where health objectives or constraints can be expressed in a low-dimensional space and calculated in a computationally efficient manner. The methodology is demonstrated in two simplified example applications whose primary aim is energy improvement: wake steering evaluation and layout-control co-design. The proposed framework is used to quantify and compare the impacts on various health metrics.
Link to paper: https://zenodo.org/records/22030149