From 7872c611ce304132ed031d0af8b49065fb70d78b Mon Sep 17 00:00:00 2001 From: trevorb1 Date: Wed, 8 Nov 2023 00:31:46 -0800 Subject: [PATCH] paper update --- paper/paper.bib | 22 ++++++++++++++++++++++ paper/paper.md | 2 ++ 2 files changed, 24 insertions(+) diff --git a/paper/paper.bib b/paper/paper.bib index 3b1f392b..9592da1c 100644 --- a/paper/paper.bib +++ b/paper/paper.bib @@ -192,3 +192,25 @@ @book{gamma1994 address = {Boston, MA}, ISBN = {0201633612}, } + +@software{huppmann2021, + author = {Huppmann, Daniel and Gidden, Matthew J. and Nicholls, Zebedee and Hörsch, Jonas and Lamboll, Robin D. and Kishimoto, Paul Natsuo and Burandt, Thorsten and Fricko, Oliver and Byers, Edward and Kikstra, Jarmo S. and Brinkerink, Maarten and Budzinski, Maik and Maczek, Florian and Zwickl-Bernhard, Sebastian and Welder, Lara and Alvarez Quispe, Erik Francisco and Smith, Christopher J.}, + doi = {10.12688/openreseurope.13633.2}, + volume={1}, + journal={Open Research Europe} + title = {pyam: analysis and visualization of integrated-assessment and macro-energy scenarios [version 2; peer review: 3 approved]}, +} + +@article{kiviluoma2021, + title = {Spine Toolbox: A flexible open-source workflow management system with scenario and data management}, + journal = {SoftwareX}, + volume = {17}, + pages = {100967}, + year = {2022}, + issn = {2352-7110}, + doi = {https://doi.org/10.1016/j.softx.2021.100967}, + url = {https://www.sciencedirect.com/science/article/pii/S2352711021001886}, + author = {Juha Kiviluoma and Fabiano Pallonetto and Manuel Marin and Pekka T. Savolainen and Antti Soininen and Per Vennström and Erkka Rinne and Jiangyi Huang and Iasonas Kouveliotis-Lysikatos and Maren Ihlemann and Erik Delarue and Ciara O’Dwyer and Terence O’Donnel and Mikael Amelin and Lennart Söder and Joseph Dillon}, + keywords = {Workflow management, Data management, Modelling, Optimisation, Open source, Scenario}, + abstract = {The Spine Toolbox is open-source software for defining, managing, simulating and optimising energy system models. It gives the user the ability to collect, create, organise, and validate model input data, execute a model with selected data and finally archive and visualise results/output data. Spine Toolbox has been designed and developed to support the creation and execution of multivector energy integration models. It conveniently facilitates the linking of models with different scopes, or spatio-temporal resolutions, through the user interface. The models can be organised as a direct acyclic graph and efficiently executed through the embedded workflow management engine. The software helps users to import and manage data, define models and scenarios and orchestrate projects. It supports a self-contained and shareable entity-relationship data structure for storing model parameter values and the associated data. The software is developed using the latest Python environment and supports the execution of plugins. It is shipped in an installation package as a desktop application for different operating systems.} +} \ No newline at end of file diff --git a/paper/paper.md b/paper/paper.md index 3d9256f4..e33c3821 100644 --- a/paper/paper.md +++ b/paper/paper.md @@ -37,6 +37,8 @@ The Open Source energy MOdelling SYStem, or OSeMOSYS [@howells2011], is a highly Compared to other open energy modelling frameworks that are based around a single (Python) implementation, such as PyPSA [@pypsa2018] and Calliope [@Pfenninger2018], the OSeMOSYS framework does not have standard data processing functions. For example, in PyPSA, users instantiate a `Network` object which has methods to import data (from various formats such as CSV, netCDF, and pypower), manipulate data, build and solve the model, and export results. In contrast, users of OSeMOSYS are required to prepare the input data and process results data themselves. otoole addresses the need in the OSeMOSYS community to standardize data handling functions across multiple different model implementations. +Utilities to facilitate data management in energy system models have existed for as long as the energy system modelling frameworks themselves. For example, see the proprietary solutions [TIMES-VEDA](https://iea-etsap.org/index.php/etsap-tools/data-handling-shells/veda) and [PLEXOS](https://www.energyexemplar.com/), or the open-source solutions pyam[@huppmann2021] and Spine-Toolbox[@kiviluoma2021]. These utilities offer some similar functionality to otoole but are often tailored to specific frameworks (in the case of proprietary solutions), focus on workflow management, or are concerned with result analysis rather than data processing. Given the flexible nature of OSeMOSYS, many different models exist with unique parameters, variables, and constraints. The OSeMOSYS community requires a tool to process input and result data regardless of model structure and implementation. + otoole supports three different input file formats: wide-format Excel files (pivoted on the year index), long-format CSV files, and GNU MathProg files. With otoole, users can convert between any of these formats to meet their skill level and workflow requirements. Furthermore, otoole can process result solution files from the open-source solvers GLPK [@GNULinearProgramming2012] and CBC [@forrest2022], and the commercial solvers Gurobi [@gurobioptimizationllcGurobiOptimizerReference2022] and CPLEX [@ibmCPLEXUsersManual2022], into tabulated CSV results. Additionally, otoole can visualize and validate input data. Through the visualization function, users can create a reference energy system from their input data, as shown in \autoref{fig:res}; this is a common step in energy modelling where a schematic is used to visualize the flow of energy. Moreover, if the input data follows a standardized naming scheme, the user can validate input data to quickly identify improperly named technologies and commodities and ensure energy flow paths are complete.