NEMO (SEI)

Next Energy Modeling system for Optimization

Authors:
Jason Veysey, Charlie Heaps, Eric Kemp-Benedict

Contact:
Jason Veysey

NEMO is a high performance, open-source energy system optimization modeling tool developed in Julia. It is intended for users who seek substantial optimization capabilities without the financial burden of proprietary software or the performance bottlenecks of common open-source alternatives. It can be used in stand-alone mode or with the Low Emissions Analysis Platform (LEAP) as a front-end.

Based on Julia. Using SQLite for data processing.

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Open Source
Apache License 2.0 (Apache-2.0)

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Model Scope

Model type and solution approach

Model class	Full energy system optimization, flexible geographic and sectoral scope
Sectors	All
Technologies	Renewables, Conventional Generation, CHP
Decisions	dispatch, investment
Regions	All
Geographic Resolution	Flexible - user-defined regionalization
Time resolution	Hour
Network coverage	transmission, distribution, DC load flow, net transfer capacities

Model type	Optimization
	Constrained cost optimization with perfect foresight
Variables	100
Computation time	From 1 second to several hours, depending on model complexity"secondtoseveralhours,dependingonmodelcomplexity" is not declared as a valid unit of measurement for this property. minutes (Natively supports parallel processing, so multi-core processors are an advantage)
Objective	Minimize total discounted costs
Uncertainty modeling	Deterministic but can readily be applied in Monte Carlo analyses
Suited for many scenarios / monte-carlo	Yes

References

Scientific references

In preparation

Reports produced using the model

https://doi.org/10.1016/j.apenergy.2022.118580 https://doi.org/10.1016/j.est.2021.103474

Example research questions

Climate change mitigation, net-zero pathways, national energy strategies

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Author institution	Stockholm Environment Institute +
Authors	Jason Veysey, Charlie Heaps, Eric Kemp-Benedict +
Citation references	In preparation
Computation time comments	Natively supports parallel processing, so multi-core processors are an advantage
Computation time minutes
Contact email	jason.veysey@sei.org +
Contact persons	Jason Veysey +
Data availability
Decisions	dispatch + and investment +
Deterministic	Deterministic but can readily be applied in Monte Carlo analyses +
Example research questions	Climate change mitigation, net-zero pathways, national energy strategies
Full Model Name	Next Energy Modeling system for Optimization +
Georegions	All +
Georesolution	Flexible - user-defined regionalization +
Is suited for many scenarios	true +
License	Apache License 2.0 (Apache-2.0) +
Math modeltype	Optimization +
Math modeltype shortdesc	Constrained cost optimization with perfect foresight +
Math objective	Minimize total discounted costs +
Model class	Full energy system optimization + and flexible geographic and sectoral scope +
Model source public	true +
Modelling software	Julia +
Network coverage	transmission +, distribution +, DC load flow + and net transfer capacities +
Number of variables	100 +
Open future	false +
Open source licensed	true +
Processing software	SQLite +
Report references	https://doi.org/10.1016/j.apenergy.2022.118580 https://doi.org/10.1016/j.est.2021.103474
Sectors	All +
Source download	https://github.com/sei-international/NemoMod.jl +
Technologies	Renewables +, Conventional Generation + and CHP +
Text description	NEMO is a high performance, open-source en … NEMO is a high performance, open-source energy system optimization modeling tool developed in Julia. It is intended for users who seek substantial optimization capabilities without the financial burden of proprietary software or the performance bottlenecks of common open-source alternatives. It can be used in stand-alone mode or with the Low Emissions Analysis Platform (LEAP) as a front-end.s Analysis Platform (LEAP) as a front-end.
Timeresolution	Hour +
Website	https://www.sei.org/projects-and-tools/tools/nemo-the-next-energy-modeling-system-for-optimization/ +

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NEMO (SEI)

References

Scientific references

Reports produced using the model

Example research questions