Changelogs » Openoa

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Openoa

2.0.1

- Replaced `GeoPandas` functionality with `pyproj` and `Shapely` for coordinate
  reference system conversion and distance measurements.
  - Moved and renamed tests and updated the documentation accordingly.

2.0.0

- Switch to [semantic versioning](https://semver.org) from this release forward.
  - Efficiency improvements in AEP calculation
  - Energy Yield Analysis (EYA) added to Operational Assessment (OA) Gap Analysis method
  - Uncertainty quantification for electrical losses and longterm turbine gross energy
  - Implemented open source Engie example data
  - 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.
  - Add electrical losses method
  - Method for estimating long-term turbine gross energy (excluding downtime and underperformance losses)
  - CI pipeline using Github Actions includes regression testing with Pytest, code coverage reporting via CodeCov, packaging and distribution via Pypi, and automatic documentation using ReadTheDocs.

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

1.0

- Refactor many analysis and toolkit modules to make them conform to a standard API (init, prepare, and run method).
  - 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.