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+
+
+
+ 20240517T233956-c99107a2fd469a3dbb05ce7555c009eafcccd1f2
+ 20240517233955
+
+ JOSS Admin
+ admin@theoj.org
+
+ The Open Journal
+
+
+
+
+ Journal of Open Source Software
+ JOSS
+ 2475-9066
+
+ 10.21105/joss
+ https://joss.theoj.org
+
+
+
+
+ 05
+ 2024
+
+
+ 9
+
+ 97
+
+
+
+ EnergyModelsX: Flexible Energy Systems Modelling with
+Multiple Dispatch
+
+
+
+ Lars
+ Hellemo
+ https://orcid.org/0000-0001-5958-9794
+
+
+ Espen Flo
+ Bødal
+ https://orcid.org/0000-0001-6970-9315
+
+
+ Sigmund Eggen
+ Holm
+ https://orcid.org/0009-0007-1782-6326
+
+
+ Dimitri
+ Pinel
+ https://orcid.org/0000-0001-9393-0036
+
+
+ Julian
+ Straus
+ https://orcid.org/0000-0001-8622-1936
+
+
+
+ 05
+ 17
+ 2024
+
+
+ 6619
+
+
+ 10.21105/joss.06619
+
+
+ http://creativecommons.org/licenses/by/4.0/
+ http://creativecommons.org/licenses/by/4.0/
+ http://creativecommons.org/licenses/by/4.0/
+
+
+
+ Software archive
+ 10.5281/zenodo.11164518
+
+
+ GitHub review issue
+ https://github.com/openjournals/joss-reviews/issues/6619
+
+
+
+ 10.21105/joss.06619
+ https://joss.theoj.org/papers/10.21105/joss.06619
+
+
+ https://joss.theoj.org/papers/10.21105/joss.06619.pdf
+
+
+
+
+
+ Julia: A fresh approach to numerical
+computing
+ Bezanson
+ SIAM review
+ 1
+ 59
+ 10.1137/141000671
+ 2017
+ Bezanson, J., Edelman, A., Karpinski,
+S., & Shah, V. B. (2017). Julia: A fresh approach to numerical
+computing. SIAM Review, 59(1), 65–98.
+https://doi.org/10.1137/141000671
+
+
+ Next frontiers in energy system modelling: A
+review on challenges and the state of the art
+ Fodstad
+ Renewable and Sustainable Energy
+Reviews
+ 160
+ 10.1016/j.rser.2022.112246
+ 2022
+ Fodstad, M., Granado, P. C. del,
+Hellemo, L., Knudsen, B. R., Pisciella, P., Silvast, A., Bordin, C.,
+Schmidt, S., & Straus, J. (2022). Next frontiers in energy system
+modelling: A review on challenges and the state of the art. Renewable
+and Sustainable Energy Reviews, 160, 112246.
+https://doi.org/10.1016/j.rser.2022.112246
+
+
+ JuMP 1.0: Recent improvements to a modeling
+language for mathematical optimization
+ Lubin
+ Mathematical Programming
+Computation
+ 10.1007/s12532-023-00239-3
+ 2023
+ Lubin, M., Dowson, O., Dias Garcia,
+J., Huchette, J., Legat, B., & Vielma, J. P. (2023). JuMP 1.0:
+Recent improvements to a modeling language for mathematical
+optimization. Mathematical Programming Computation.
+https://doi.org/10.1007/s12532-023-00239-3
+
+
+ Hydrogen for harvesting the potential of
+offshore wind: A north sea case study
+ Bødal
+ Applied Energy
+ 357
+ 10.1016/j.apenergy.2023.122484
+ 2024
+ Bødal, E. F., Holm, S. E.,
+Subramanian, A., Durakovic, G., Pinel, D., Hellemo, L., Ortiz, M. M.,
+Knudsen, B. R., & Straus, J. (2024). Hydrogen for harvesting the
+potential of offshore wind: A north sea case study. Applied Energy, 357,
+122484.
+https://doi.org/10.1016/j.apenergy.2023.122484
+
+
+ TimeStruct.jl: Flexible time structures in
+optimization modelling
+ Flatberg
+ 10.5281/zenodo.10511399
+ 2024
+ Flatberg, T., & Hellemo, L.
+(2024). TimeStruct.jl: Flexible time structures in optimization
+modelling. Zenodo.
+https://doi.org/10.5281/zenodo.10511399
+
+
+ SpineOpt: A flexible open-source energy
+system modelling framework
+ Ihlemann
+ Energy Strategy Reviews
+ 43
+ 10.1016/j.esr.2022.100902
+ 2211-467X
+ 2022
+ Ihlemann, M., Kouveliotis-Lysikatos,
+I., Huang, J., Dillon, J., O’Dwyer, C., Rasku, T., Marin, M., Poncelet,
+K., & Kiviluoma, J. (2022). SpineOpt: A flexible open-source energy
+system modelling framework. Energy Strategy Reviews, 43, 100902.
+https://doi.org/10.1016/j.esr.2022.100902
+
+
+ Documentation for the TIMES
+model
+ Loulou
+ 2016
+ Loulou, R., Goldstein, G., Kanudia,
+A., Lettila, A., & Remme, U. (2016). Documentation for the TIMES
+model. IEA Energy Technology Systems Analysis
+Programme.
+
+
+ Designing a model for the global energy
+system—GENeSYS-MOD: An application of the open-source energy modeling
+system (OSeMOSYS)
+ Löffler
+ Energies
+ 10
+ 10
+ 10.3390/en10101468
+ 1996-1073
+ 2017
+ Löffler, K., Hainsch, K., Burandt,
+T., Oei, P.-Y., Kemfert, C., & Von Hirschhausen, C. (2017).
+Designing a model for the global energy system—GENeSYS-MOD: An
+application of the open-source energy modeling system (OSeMOSYS).
+Energies, 10(10).
+https://doi.org/10.3390/en10101468
+
+
+ GenX
+ Jenkins
+ 10.5281/zenodo.10846069
+ 2024
+ Jenkins, J., Sepulveda, N.,
+Mallapragada, D., Patankar, N., Schwartz, A., Schwartz, J., Chakrabarti,
+S., Xu, Q., Morris, J., & Sepulveda, N. (2024). GenX. Zenodo.
+https://doi.org/10.5281/zenodo.10846069
+
+
+ Tulipa energy model
+ Tejada-Arango
+ 10.5281/zenodo.8363262
+ 2024
+ Tejada-Arango, D., Morales-España,
+G., Clisby, L., Wang, N., Soares Siqueira, A., Ali, S., Soucasse, L.,
+& Neustroev, G. (2024). Tulipa energy model. Zenodo.
+https://doi.org/10.5281/zenodo.8363262
+
+
+
+
+
+
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+
+
+
+
+
+
+
+Journal of Open Source Software
+JOSS
+
+2475-9066
+
+Open Journals
+
+
+
+6619
+10.21105/joss.06619
+
+EnergyModelsX: Flexible Energy Systems Modelling with
+Multiple Dispatch
+
+
+
+https://orcid.org/0000-0001-5958-9794
+
+Hellemo
+Lars
+
+
+*
+
+
+https://orcid.org/0000-0001-6970-9315
+
+Bødal
+Espen Flo
+
+
+
+
+https://orcid.org/0009-0007-1782-6326
+
+Holm
+Sigmund Eggen
+
+
+
+
+https://orcid.org/0000-0001-9393-0036
+
+Pinel
+Dimitri
+
+
+
+
+https://orcid.org/0000-0001-8622-1936
+
+Straus
+Julian
+
+
+
+
+
+SINTEF Industry, Postboks 4760 Torgarden, 7465
+Trondheim
+
+
+
+
+SINTEF Energy Research, Postboks 4761 Torgarden, 7465
+Trondheim
+
+
+
+
+* E-mail:
+
+
+8
+3
+2024
+
+9
+97
+6619
+
+Authors of papers retain copyright and release the
+work under a Creative Commons Attribution 4.0 International License (CC
+BY 4.0)
+2022
+The article authors
+
+Authors of papers retain copyright and release the work under
+a Creative Commons Attribution 4.0 International License (CC BY
+4.0)
+
+
+
+Julia
+energy
+multi-carrier
+multiple dispatch
+
+
+
+
+
+ Summary
+
EnergyModelsX
+ is a multi-nodal energy system modelling framework written in Julia
+ (Bezanson
+ et al., 2017), based on the mathematical programming DSL JuMP
+ (Lubin
+ et al., 2023). The framework is designed to be flexible and
+ easy to extend, for instance all resources, both energy carriers and
+ materials, may be defined by the user. Furthermore, EnergyModelsX
+ follows a modular design to facilitate extensions through additional
+ packages.
+ EnergyModelsX
+ was developed at the Norwegian research organization
+ SINTEF
+ at the institutes SINTEF Energi and SINTEF Industri. The framework
+ consists of the package EnergyModelsBase and currently provides the
+ following extensions: EnergyModelsGeography, EnergyModelsInvestments
+ and EnergyModelsRenewableProducers.
+
See Bødal et al.
+ (2024)
+ for an example application of
+ EnergyModelsX.
+
+
+ Statement of need
+
The increasing share of renewable energy generation and importance
+ of sector coupling increases the complexity of energy systems, and
+ makes the modelling of these systems more challenging. To meet the
+ demand of energy modelers, energy system models need ever increasing
+ flexibility to analyse the energy systems of tomorrow
+ (Fodstad
+ et al., 2022). While large scale models like TIMES
+ (Loulou
+ et al., 2016) and GENeSYS-MOD
+ (Löffler
+ et al., 2017) are important for modelling large energy systems,
+ they lack the potential for simple modifications in technology
+ descriptions as well as simple incorporation of region specific
+ constraints.
+ SpineOpt
+ (Ihlemann
+ et al., 2022) offers the user with the flexibility, but the
+ monolithic approach of including all functionality in a single package
+ reduces the understandability of the code.
+ GenX
+ (Jenkins
+ et al., 2024) and
+ Tulipa
+ Energy Model
+ (Tejada-Arango
+ et al., 2024) are other recent energy system models developed
+ in Julia with similar goals to EnergyModelsX, but with less focus on
+ extensibility and alternative technology formulations.
+
EnergyModelsX
+ is a modular energy-system modelling framework designed to give
+ modelers a high level of flexibility. The time resolution is decoupled
+ from the technology descriptions by the application of
+ TimeStruct
+ (Flatberg
+ & Hellemo, 2024), facilitating the support of a wide range
+ of time structures with different temporal resolution and to support
+ operational uncertainty. The system is designed from the ground up to
+ support multiple energy carriers, and the modeler may define
+ resources, including energy carriers, materials and emissions freely.
+ The base model is designed to allow extentions with extra
+ functionality such as support for different spatial resolution or more
+ detailed technology description, making the framework well suited to
+ address the needs of modelling integrated energy systems with sector
+ coupling.
+
State-of-the art modelling frameworks have several limitations;
+ they are often built on proprietary algebraic modelling languages with
+ parameter-driven models and often start from a single energy-carrier.
+ EnergyModelsX
+ addresses these shortcomings by using the modern modelling framework
+ JuMP with excellent performance characteristics. Modularity is
+ achieved through Julia’s multiple dispatch functionality, allowing
+ extensions to build on the base package. The results can be made fully
+ reproducible by using an open modelling language and the Julia package
+ manager for simple reproducibility of analyses.
+
With a fast and flexible system, users and developers may iterate
+ rapidly, develop new or modify existing functionalities to adjust
+ analyses to their needs and run multiple sensitivity analyses with
+ ease.
+
+
+ Released packages of EnergyModelsX
+
As part of the initial release of
+ EnergyModelsX,
+ the following packages and extensions are available:
+
+ EnergyModelsBase
+
EnergyModelsBase
+ is the base model, providing an optimal dispatch model for
+ operational analyses of local systems. Reference (linear)
+ implementations are available for a set of different generic node
+ types, including Source (only output), NetworkNode (input and
+ output) and Sink (only input), as well as Availability nodes to
+ serve as a connector, and Storage. EnergyModelsBase is designed to
+ be extendable without changes to the core structure. It provides
+ abstract types that may be extended by additional packages for more
+ specific nodes such that more detailed technology modelling can be
+ applied easily. This allows keeping the size of EnergyModelsBase to
+ a minimum, reducing both the difficulty of understanding the
+ modelling approach and the compilation time.
+
+
+ EnergyModelsGeography
+
EnergyModelsGeography
+ extends EnergyModelsBase with modelling of geographical regions with
+ transmission capacity between regions. Different modes of
+ transmission are provided, allowing to model e.g. power transmission
+ lines and pipelines. EnergyModelsGeography follows the same
+ philosophy as EnergyModelsBase. Hence, users can easily develop new
+ descriptions of transmission modes or special restrictions on
+ regions.
+
+
+ EnergyModelsInvestments
+
To support capacity expansion models,
+ EnergyModelsInvestments
+ allows adding investment decisions to add or increase installed
+ capacity for nodes. The investments can be modelled using a variety
+ of investment modes, including discrete, continuous or
+ semi-continuous. The modeler has full flexibility and may combine
+ available investment modes as best fits the problem at hand, while
+ EnergyModelsInvestments will make sure to only add the needed
+ (binary) variables and constraints for each node or link.
+
+
+ EnergyModelsRenewableProduction
+
EnergyModelsRenewableProducers
+ facilitates the modelling of renewable energy generation, both from
+ non-dispatchable technologies such as wind power and PV and for
+ hydropower with (pumped) storage. It also serves as an example for
+ introducing new technology descriptions to EnergyModelsX and how to
+ reuse constraints of the reference nodes.
+
+
+
+ Example application
+
To illustrate the usage of EnergyModelsX, consider the example of
+ developing cost-effective hydrogen infrastructure for the North Sea
+ Region. The example shows multiple regions with different technologies
+ and different investment options available, including capacities for
+ pipelines and production nodes. Pipeline costs take economies of scale
+ into account, and the figure shows the pipeline capacities suggested
+ by EnergyModelsX after solving with a standard MILP solver, given a
+ set of costs and prices. See also Bødal et al.
+ (2024)
+ for a similar example.
+
+
Example application: hydrogen infrastructure development
+ in the North Sea region
+
+
+
+
+ Acknowledgements
+
The development of EnergyModelsX was funded
+ by the Norwegian Research Council in the project
+ Clean
+ Export, project number
+ 308811.
+ The authors gratefully acknowledge the financial support from the user
+ partners: Å Energi, Air Liquide, Equinor Energy, Gassco, and Total
+ OneTech.
+
+
+
+
+
+
+
+ BezansonJeff
+ EdelmanAlan
+ KarpinskiStefan
+ ShahViral B
+
+ Julia: A fresh approach to numerical computing
+ SIAM review
+ SIAM
+ 2017
+ 59
+ 1
+ 10.1137/141000671
+ 65
+ 98
+
+
+
+
+
+ FodstadMarte
+ GranadoPedro Crespo del
+ HellemoLars
+ KnudsenBrage Rugstad
+ PisciellaPaolo
+ SilvastAntti
+ BordinChiara
+ SchmidtSarah
+ StrausJulian
+
+ Next frontiers in energy system modelling: A review on challenges and the state of the art
+ Renewable and Sustainable Energy Reviews
+ Elsevier
+ 2022
+ 160
+ 10.1016/j.rser.2022.112246
+ 112246
+
+
+
+
+
+
+ LubinMiles
+ DowsonOscar
+ Dias GarciaJoaquim
+ HuchetteJoey
+ LegatBenoît
+ VielmaJuan Pablo
+
+ JuMP 1.0: Recent improvements to a modeling language for mathematical optimization
+ Mathematical Programming Computation
+ 2023
+ 10.1007/s12532-023-00239-3
+
+
+
+
+
+ BødalEspen Flo
+ HolmSigmund Eggen
+ SubramanianAvinash
+ DurakovicGoran
+ PinelDimitri
+ HellemoLars
+ OrtizMiguel Muñoz
+ KnudsenBrage Rugstad
+ StrausJulian
+
+ Hydrogen for harvesting the potential of offshore wind: A north sea case study
+ Applied Energy
+ Elsevier
+ 2024
+ 357
+ 10.1016/j.apenergy.2023.122484
+ 122484
+
+
+
+
+
+
+ FlatbergTruls
+ HellemoLars
+
+ TimeStruct.jl: Flexible time structures in optimization modelling
+ Zenodo
+ 202401
+ https://zenodo.org/records/10511399
+ 10.5281/zenodo.10511399
+
+
+
+
+
+ IhlemannMaren
+ Kouveliotis-LysikatosIasonas
+ HuangJiangyi
+ DillonJoseph
+ O’DwyerCiara
+ RaskuTopi
+ MarinManuel
+ PonceletKris
+ KiviluomaJuha
+
+ SpineOpt: A flexible open-source energy system modelling framework
+ Energy Strategy Reviews
+ 2022
+ 43
+ 2211-467X
+ https://www.sciencedirect.com/science/article/pii/S2211467X22000955
+ 10.1016/j.esr.2022.100902
+ 100902
+
+
+
+
+
+
+ LoulouRichard
+ GoldsteinGary
+ KanudiaAmit
+ LettilaAntti
+ RemmeUwe
+
+ Documentation for the TIMES model
+ IEA Energy Technology Systems Analysis Programme
+ 2016
+
+
+
+
+
+ LöfflerKonstantin
+ HainschKarlo
+ BurandtThorsten
+ OeiPao-Yu
+ KemfertClaudia
+ Von HirschhausenChristian
+
+ Designing a model for the global energy system—GENeSYS-MOD: An application of the open-source energy modeling system (OSeMOSYS)
+ Energies
+ 2017
+ 10
+ 10
+ 1996-1073
+ https://www.mdpi.com/1996-1073/10/10/1468
+ 10.3390/en10101468
+
+
+
+
+
+ JenkinsJesse
+ SepulvedaNestor
+ MallapragadaDharik
+ PatankarNeha
+ SchwartzAaron
+ SchwartzJacob
+ ChakrabartiSambuddha
+ XuQingyu
+ MorrisJack
+ SepulvedaNestor
+
+ GenX
+ Zenodo
+ 202404
+ https://zenodo.org/records/10910030
+ 10.5281/zenodo.10846069
+
+
+
+
+
+ Tejada-ArangoDiego
+ Morales-EspañaGermán
+ ClisbyLauren
+ WangNi
+ Soares SiqueiraAbel
+ AliSuvayu
+ SoucasseLaurent
+ NeustroevGrigory
+
+ Tulipa energy model
+ Zenodo
+ 202403
+ https://zenodo.org/records/10895406
+ 10.5281/zenodo.8363262
+
+
+
+
+
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