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Systems","sub_category":"Energy System Modeling Frameworks","monthly_downloads":0,"total_dependent_repos":0,"total_dependent_packages":0,"readme":"## energyRt \u003ca href=\"https://energyrt.org/articles/logo.html\"\u003e\u003cimg src=\"man/figures/logo.png\" align=\"right\" height=\"120\" alt=\"Logo-search\" /\u003e\u003c/a\u003e\n\n**energyRt** (*energy* system modeling *R-t*oolbox /ˈɛnərdʒi ɑrt/) is a\nset of classes, methods, and functions that define a macro-language for\nenergy system modeling within the R environment. This package offers a\nhigh-level, user-friendly interface that simplifies the development and\nanalysis of complex energy models. By abstracting much of the underlying\ncomplexity, **energyRt** allows users to concentrate on strategic and\nanalytical aspects rather than the technical details of coding.\n\n**Key Features:**\n\n-   **User-Friendly Interface: energyRt** enables users to define energy\n    systems, input data, and configure scenarios using intuitive,\n    domain-specific commands. It is designed to be accessible for both\n    experienced modelers and those new to the field.\n-   **Seamless R Integration:** The package integrates seamlessly with\n    R’s extensive ecosystem of packages, allowing users to utilize\n    powerful data handling and visualization tools within their energy\n    modeling projects.\n-   The **energyRt** optimization\n    [model](https://energyrt.github.io/book/model.html) is implemented\n    in four widely-used mathematical programming languages, both\n    proprietary and open-source: [GAMS](http://www.gams.com/),\n    [GLPK/Mathprog](https://www.gnu.org/software/glpk/),\n    [Python/Pyomo](http://www.pyomo.org/),\n    [Julia/JuMP](http://www.juliaopt.org/JuMP.jl/stable/). The package\n    is designed to work seamlessly with any of these versions, allowing\n    users to solve models using their preferred software while ensuring\n    consistent and equivalent results across all platforms.\n-   **Modular Model Construction: energyRt** supports the construction\n    of models in a modular fashion, enabling incremental development,\n    individual component testing, and code reuse across different\n    projects. This modularity, combined with R’s interactive\n    environment, promotes an iterative approach to modeling where\n    assumptions can be tested, and results explored in real-time.\n-   **Applications: energyRt** is designed to facilitate the creation of\n    sophisticated energy system models, offering both flexibility and\n    depth for detailed analysis. It is an essential tool for\n    researchers, policymakers, and industry professionals engaged in\n    long-term energy system planning, energy transition, and\n    decarbonization efforts.\n\nThe package website: \u003chttps://energyrt.org\u003e\\\nDocumentation in progress: \u003chttps://energyrt.github.io/book/\u003e\n\n### Development status\n\n**energyRt** is currently in preparation for its first release and\npublication on [CRAN](https://cran.r-project.org/). The major milestone\nfor the package is the version **v0.50** (*\"half-way-there\"*), a proof\nof concept with a full-featured and efficient model written in four\nmath-prog languages, with R-interface for the model design, processing\nresults, and producing reports. This version will have frozen model\ncode, classes and methods. Any updates will address only potential fixes\nand new features with minimal impact on already existing modeling\nprojects.\n\nFurther development, versions starting from **v0.9** towards the\n**v1.0** will have fully reviewed model and classes with the goal to\nfurther increase efficiency, reduce memory footprint and computational\nburden for both the model and its R interface, and significantly extend\nfeatures.\n\n## Installation\n\nAssuming that R is already installed (if not, please download and\ninstall from \u003chttps://www.r-project.org/\u003e), we also recommend RStudio\n(\u003chttps://www.rstudio.com/\u003e), a powerful IDE (Integrated Development\nEnvironment) for R. The installation of the package is done via the\n`pak` or `remotes` packages:\n\n`pak::pkg_install(\"energyRt/energyRt@v0.50\")`\\\nor\\\n`remotes::install_github(\"energyRt/energyRt\", ref = \"v0.50\")`\n\nThe next step would be to install at least one of the solvers: GAMS,\nGLPK, Python/Pyomo, Julia/JuMP. Please refer to the respective websites\nfor installation instructions. More detaileds is available on the\n[IDEEA](https://ideea-model.github.io/IDEEA/articles/install.html) model\nwebsite, a project based on the **energyRt** package.\n","funding_links":[],"readme_doi_urls":[],"works":{},"citation_counts":{},"total_citations":0,"keywords_from_contributors":[],"project_url":"https://ost.ecosyste.ms/api/v1/projects/19940","html_url":"https://ost.ecosyste.ms/projects/19940"}