Release 2.2

• IAV incorporation in AEP calculation
• Set power to 0 for windspeeds above and below cutoff in IEC power curve function.
• Split unit tests from regression tests and updated CI pipeline to run the full regression tests weekly.
• Flake8 with Black code style implemented with git hook to run on commit
• Updated long-term loss calculations to weight by monthly/daily long-term gross energy
• Added wind turbine asset data to example ENGIE project
• Reduce amount of time it takes to run regression tests by decreasing number of monte carlo iterations. Reduce tolerance of float comparisons in plant analysis regression test. Linear regression on daily data is removed from test.
• Bugfixes, such as fixing an improper python version specifier in setup.py and replacing some straggling references to the master branch with main.

Release 2.1

• Modify bootstrapping approach for period of record sampling. Data is now sampled with replacement, across 100% of the POR data.
• Cleaned up dependencies for JOSS review. Adding peer-reviewed JOSS paper.
• Add Binder button to Readme which makes running the example notebooks easier.
• Set maximum python version to 3.8, due to an install issue for dependency Shapely on Mac with Python 3.9.

Release 2.0.1

This update resolves a few issues including:

• create workaround for unknow zsh issue
• modifying ENGIE project pathname in exmaples so auto data extract works
• replace GeoPandas with pyproj and Shapely

Release 2.0.0

• Energy Yield Analysis (EYA) to Operational Assessment(OA) Gap Analysis method
• Uncertainty quantification for electrical losses and longterm turbine gross energy
• Implemented open source Engie example data, and complete update of example notebooks
• Switch to standard BSD-3 Clause license
• Automated quality control method to assist with data ingestion. Tools in this method include daylight savings time change detection and - identification of the diurnal cycle.
• Electrical losses method
• Method for estimating long-term turbine gross energy (excluding downtime and underperformance losses)
• User-facing CI pipeline using Github Actions
• Automatic documentation using ReadTheDocs
• Pip Package

Release 1.1

• Python3 Support
• Addition of reanalysis schemas to the Sphinx documentation
• Easy import of EIA data using new module: Metadata_Fetch
• Updated contributing.md document
• Quality checks for reanalysis data
• Improved installation instructions
• Integration tests are now performed in CI
• Performed PEP8 linting

Release 1.0

• Complete refactor of many analysis and toolkit modules.
• Timeseries Table is now an integrated component, no sparkplug-datastructures dependency
• Plant Level AEP method w/ Monte Carlo
• Turbine / Scada level toolkits: Filtering, Imputing, Met, Pandas Plotting, Timeseries, Unit Conversion
• Most toolkits and all methods are fully documented in Sphinx.
• Two example notebooks: Operational AEP Analysis and Turbine Analysis
• All toolkits except for Pandas Plotting have > 80% test coverage.