WindAnalysis: A Reproducible Computational Framework for Coastal Wind Resource Assessment

Wind resource assessment increasingly depends on integrating heterogeneous reanalysis, turbine data, geospatial operations, and persistent computational services. This article presents WindAnalysis, a containerized web framework for coastal wind studies in the Colombian Caribbean. Its novelty is architectural and operational: rather than introducing new wind models, the framework integrates scheduled ERA5 and MERRA-2 ingestion, persistent PostgreSQL storage, typed FastAPI services, an authenticated React geospatial interface, experiment retention, turbine-level power curves, and inverse-distance-weighted (IDW) interpolation within a single reproducible workflow. The evaluated database state comprised 32,633,302 ERA5 and 3,941,280 MERRA-2 records. Controlled benchmarks showed a 3962-fold acceleration for planner-based row counts and a 19.4-fold acceleration for 1% block-sampled mean queries, with 0.39% mean absolute relative error. Internal leave-one-grid-point-out IDW cross-validation yielded a 10 m wind-speed RMSE of 0.366 m/s for the deployed p = 2, 50 km configuration. The documented La Guajira case, using direct ERA5 wind at 100 m, produced a gross AEP of 8.901 GWh/year and a gross capacity factor of 61.58% for a Vestas V82 turbine. The evaluation further includes 2839 archived automated tests and release-level UI-to-runner parity. WindAnalysis therefore provides an inspectable, repeatable integration layer for regional wind-resource assessment while keeping computational reproducibility distinct from external physical validation.