Package: nemseer
nemseerA package for downloading and handling historical National Electricity Market (NEM) forecast data produced by the Australian Energy Market Operator (AEMO).InstallationpipinstallnemseerManynemseeruse-cases requireNEMOSIS, which can also be installed usingpip:pipinstallnemosisOverviewnemseerallows you to access historical AEMOpre-dispatchandProjected Assessment of System Adequacy (PASA)forecast[^1] data available through theMMSDM Historical Data SQLLoader.nemseercan then compile this data intopandas DataFramesorxarray Datasets.Source:Reserve services in the National Electricity Market, AEMC, 2021Whereas PASA processes are primarily used to assess resource adequacy based on technical inputs and assumptions for resources in the market (i.e. used to answer questions such as"can operational demand be met in the forecast horizon with a sufficient safety (reserve) margin?"), pre-dispatch processes incorporate the latest set of market participant offers and thus produce regional prices forecasts for energy and frequency control ancillary services(FCAS). Overviews of the various pre-dispatch and PASA processes can be found in theglossary.[^1]: We use the term"forecast"loosely, especially given that these"forecasts"change once participants update offer information (e.g. through rebidding) or submit revised resource availabilities and energy constraints. Both of these are intended outcomes of these"ahead processes", which are run to provide system and market information to participants to inform their decision-making. However, to avoid confusion and to ensure consistency with the language used by AEMO, we use the terms"forecast"(or outputs) and"forecast types"(or ahead processes) innemseer.nemseerenables you to download and work with data for the following forecast types. Where available, AEMO process and table descriptions are linked:5-minute pre-dispatch (P5MIN:Table descriptions)Pre-dispatch(PREDISPATCH:Table descriptions)Pre-dispatch Projected Assessment of System Adequacy (PDPASA:Tables and Descriptions)Short Term Projected Assessment of System Adequacy(STPASA:Table descriptions)Medium Term Projected Assessment of System Adequacy(MTPASA:Table descriptions)Another helpful reference for PASA information is AEMO'sReliability Standard Implementation Guidelines.ST PASA Replacement ProjectNote that the methodologies for PD PASA and ST PASA are being reviewed by AEMO. In particular, the ST PASA Replacement project will combine PD PASA and ST PASA into ST PASA. For more detail, refer to thefinal determination of the rule changeand theAEMO ST PASA Replacement Project home page.UsageGlossaryTheglossarycontains overviews of the PASA and pre-dispatch processes, and descriptions of terminology used innemseer.Quick startCheck out theQuick startfor guide on to usenemseer.ExamplesSome use case examples have been included in theExamplessection of the documentation.SupportIf you are having an issue with this software that has not already been raised in theissues register, pleaseraise a new issue.ContributingInterested in contributing? Check out thecontributing guidelines, which also includes steps to installnemseerfor development.Please note that this project is released with aCode of Conduct. By contributing to this project, you agree to abide by its terms.CitationIf you usenemseer, please cite the package via theZenodo DOI.If you use code or analysis from any of the demand error and/or price convergence examples in the documentation, please also citeNEMOSISviathis conference paperLicensesnemseerwas created by Abhijith Prakash. It is licensed under the terms ofGNU GPL-3.0-or-later licences.The content within the documentation for this project is licensed under aCreative Commons Attribution 4.0 International License.Creditsnemseerwas created withcookiecutterand thepy-pkgs-cookiecuttertemplate.Development ofnemseerwas funded by theUNSW Digital Grid Futures Institute.Contributor AcknowledgementsThanks to:Nicholas Gorman for reviewingnemseercodeDylan McConnell for assistance in interpreting PASA run typesDeclan Heim for suggesting improvements tonemseerexamples