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| title | chunk | source | category | tags | date_saved | instance |
|---|---|---|---|---|---|---|
| Open energy system models | 9/16 | https://en.wikipedia.org/wiki/Open_energy_system_models | reference | science, encyclopedia | 2026-05-05T03:49:30.157219+00:00 | kb-cron |
AnyMOD.jl is a framework for planning macro‑energy systems at a high level of spatio-temporal detail. The framework covers the expansion and operation of short-term and seasonal storage, fossil and renewable generation, transmission infrastructure, and sector coupling technologies. It can be used to plan long‑term pathways under perfect foresight. AnyMOD.jl is implemented in Julia and relies on the JuMP library for optimization and DataFrames.jl for data management. Models are formulated as linear optimization problems and can be solved with open-source libraries like HiGHS or commercial solvers like CPLEX. To increase accessibility and enable version-controlled development, specific models are fully defined using CSV files. Compared to similar tools, AnyMOD.jl puts an emphasis on innovative methods to achieve high detail and capture intermittent renewables, while maintaining a comprehensive scope in terms of regions and sectors. These methods include varying the spatio-temporal resolution by energy carrier within the same model and a scaling algorithm to improve the properties of the underlying optimization problem. Methods from stochastic programming are now being implemented to better address the uncertainties associated with renewable generation. As of 2022, most studies deploying the tool have focused on the German energy system in a European context, for instance investigating the trade‑offs between centralized and decentralized designs, the role of grid planning, and the potential of sufficiency measures. In addition, AnyMOD.jl has been used to support policy reports from the German Institute for Economic Research (DIW) on the European Green Deal and the coordination of the German Energiewende.
=== Backbone ===
Backbone is an energy system modeling framework that allows for a high level of detail and adaptability. It has been used to study city-level energy systems as well as multi-country energy systems. It was originally developed during 2015–2018 in an Academy of Finland‑funded project 'VaGe' by the Design and Operation of Energy Systems team at VTT. It has been further developed in a collaboration which includes VTT, UCD, and RUB. The framework is agnostic about what is modeled, but still has capabilities to represent a large range of energy system characteristics — such as generation and transfer, reserves, unit commitment, heat diffusion in buildings, storages, multiple emissions and P2X, etc. It offers linear and mixed integer constraints for capturing things like unit start-ups and investment decisions. It allows the modeler to change the temporal resolution of the model between time steps. — and this enables, for example, to use a coarser time resolution further ahead in the time horizon of the model. The model can be solved as an investment model (single or multi-period, myopic, or full foresight) or as a rolling production cost unit commitment model to simulate operations.
Backbone's own wiki page has a tutorial for new users, example models, and user created mods. Open datasets include Northern European model for electricity, heat, and hydrogen and district heating and cooling model for the Finnish capital region.
=== Balmorel ===
Balmorel is a market-based energy system model from Denmark. Development was originally financed by the Danish Energy Research Program in 2001. The codebase was made public in March 2001. The Balmorel project maintains an extensive website, from where the codebase and datasets can be download as a zip file. Users are encouraged to register. Documentation is available from the same site. Balmorel is written in GAMS. The original aim of the Balmorel project was to construct a partial equilibrium model of the electricity and CHP sectors in the Baltic Sea region, for the purposes of policy analysis. These ambitions and limitations have long since been superseded and Balmorel is no longer tied to its original geography and policy questions. Balmorel classes as a dispatch and investment model and uses a time resolution of one hour. It models electricity and heat supply and demand, and supports the intertemporal storage of both. Balmorel is structured as a pure linear program (no integer variables). As of 2016, Balmorel has been the subject of some 22 publications. A 2008 study uses Balmorel to explore the Nordic energy system in 2050. The focus is on renewable energy supply and the deployment of hydrogen as the main transport fuel. Given certain assumptions about the future price of oil and carbon and the uptake of hydrogen, the model shows that it is economically optimal to cover, using renewable energy, more than 95% of the primary energy consumption for electricity and district heat and 65% of the transport. A 2010 study uses Balmorel to examine the integration of plug-in hybrid vehicles (PHEV) into a system comprising one quarter wind power and three quarters thermal generation. The study shows that PHEVs can reduce the CO2 emissions from the power system if actively integrated, whereas a hands-off approach – letting people charge their cars at will – is likely to result in an increase in emissions. A 2013 study uses Balmorel to examine cost-optimized wind power investments in the Nordic-Germany region. The study investigates the best placement of wind farms, taking into account wind conditions, distance to load, and the generation and transmission infrastructure already in place.
=== Calliope ===