Although v0.1.0 was released more than 2 years ago, I finally want to share our package here.
AnyMOD.jl builds on JuMP.jl and creates capacity expansion problems optimizing the transformation of macro-energy systems towards renewable energy. Compared to similar Python tools, AnyMOD.jl puts an emphasis on innovative methods that achieve high temporal detail to capture fluctuations of renewables while maintaining a comprehensive scope in terms of regions and sectors. These methods often require extensive pre-processing and depend on Julia’s performance to be practical.
There are two related working papers and six peer-reviewed publications, but highlights from a Julia perspective are:
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A SoftwareX paper introducing the package and describing how it stores JuMP.jl objects in DataFrames to efficiently construct linear problems using SQL-like commands.
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A recent working paper on stochastic optimization with AnyMOD.jl proposing a novel refinement for Benders decomposition.
There is also a documentation and a short JuliaCon presentation of the tool.