abiola-adeoye / AWERA

Airborne Wind Energy Resource Analysis tool (AWERA) is meant to provide wind resource classification/representation and power harvesting estimation for AWES. It builds on wind profile clustering techniques used by Mark Schelbergen (TU Delft).

AWERA - AWE Resource Analysis

Installing and running the code

Creating the conda environment

To create the conda environment run

conda create -c conda-forge -p [path/envName] --file requirements.txt

Then activate the environment to be able to work with AWERA.

Run AWERA

There are a few example scripts on how to run AWERA. The structure is always: import, initialise with configuration (Config() class) and call functions as needed.

Components

If only parts of the toolchain are needed, other independent parts can be excluded from the import in AWERA/init.

Wind Resource Analysis

(See README in folder for now.)

Wind Profile Clustering

Developed from (https://github.com/markschelbergen/wind-profile-clustering)

QSM Power Production

Using Kitepower V3 prototype specifications (or kitepower 100kW or kitepower 500kW), a quasi-steady model simulation is run for a given wind profile. Power curve and single profile power production functionality is available.

Evaluation