moepy 0.0.6

Code and analysis used for calculating the merit order effect of renewables on price and carbon intensity of electricity markets

Merit-Order-Effect

Code and analysis used for calculating the merit order effect of renewables on price and carbon intensity of electricity markets

Repo Publishing - To Do

Notebook Polishing Changes:

• Add docstrings (can be one-liners unless shown in the user-guides or likely to be used often)
• Add a mini sentence or two at the top of each nb explaining what it's about
• Ensure there is a short explanation above each code block
• Move input data to a raw dir
• Check all module imports are included in settings.ini
• Re-run all of the notebooks at the end to check that everything works sequentially

Completed Notebooks:

• Retrieval
• EDA
• LOWESS (start with the biggy)
• Price Surface Estimation
• Price MOE
• Carbon Surface Estimation and MOE
• Prediction and Confidence Intervals
• Hyper-Parameter Tuning
• Tables and Figures

New Code:

• Separate the binder and development environment.yml files
• Re-attempt LIGO fitting example as part of a user-guide
• Add in the prediction and confidence interval plots
• Add a lot more to the EDA examples
• Every week re-run a single analysis (could be in the user-guide) and show the generated fit at the top of the ReadMe
• Try to speed things up, e.g. with Numba (one person has already started doing this)
• Get the models saved on S3 or figshare and pulled into binder via a postBuild script

External/ReadMe

• Add the GH action for version assignment triggering pypi push and zenodo update
• Just before the paper is published set the version to 1.0.0 and have a specific Binder link that builds from that version as stored in the Zenodo archive
• Could link the zotero collection
• Add citations for both the external data I use and the resulting time-series I generate
• Add bibtex citation examples for both the paper and the code (could use this)
• Publish the latest version to PyPi
• Mention the new module in the gist that some of the basic regression code was inspired by