Come meet the poster presenters to ask them questions and discuss their work
Check the programme for our poster viewing moments. For more details on each poster, click on the poster titles to read the abstract.
PO077: WindKit: a Python framework for wind resource assessment applications
Bjarke Tobias Olsen, Researcher, DTU Wind Energy
WindKit is a free and open-source Python framework developed by DTU Wind Energy for handling and exploring common data structures for wind resource assessment. The library supports wind climate, topography, and turbine-related objects through a flexible data model and functions to perform basic data operations, including geographic referencing and spatial transformations. WindKit has been developed over several years internally, but in April 2022 it will be openly released to the scientific community. The framework is built on powerful Python libraries from the scientific computing ecosystem, most notably the flexible xarray library that supports N-D labeled arrays, enabling an intuitive user experience with great extensibility and performance. The aim of WindKit is to serve as a basic wind resource assessment library for developers to build their own applications upon, making it easier to standardize data formats and workflows, and to share and compare results. WindKit already serves as the backbone for a number of other DTU Wind Energy developed packages, such as wind-validation and PyWAsP. Wind-validation standardizes and simplifies validation of wind climate data, and PyWAsP is a wrapper around the WAsP and WAsP Engineering core libraries, used extensively for wind resource assessment throughout the wind energy industry. PyWAsP enables a flexible and scriptable experience that makes it straightforward to incorporate the WAsP functionality into any workflows and tools. The development of WindKit and PyWAsP has been used to produce the large-scale wind climate maps, the New European Wind Atlas (NEWA), the Global Wind Atlas version 3 (GWA3), and the Global Atlas for Siting Parameters (GASP). In addition to their calculation, WindKit provides the backbone of the data APIs that provide subsets of these maps to end-users through another DTU developed tool, daTap. The PyWAsP annual energy production (AEP) calculator uses the DTU developed PyWake package to model wind farm wakes and blockage effects, making it seamless to try out many different wake and blockage models. In this presentation, WindKit will be presented, some of its design decisions highlighted, and its functionality will be demonstrated. Finally, a demonstration will be made of PyWAsP to show how it benefits from WindKit's framework.