Maon

Authors:
Mihail Ketov, Fabian Pfannes, Huangluolun Zhou, Nicolai Schmid, Dariush Wahdany, Yash Patel, Kaan Gecü, Ömer Bilgin, Esmanur Eryilmaz, Ali Baran Gündüz, Marios Morfopoulos, Sangeetha Kadarkarai, Mark Schäfer, Kai Strunz, Albert Moser

Contact:
Dr. Mihail Ketov

Maon is a fundamental simulation environment for electricity, gas and emission market analysis. The model simulates the annual coupled dispatch of all supply and demand for 8760 hours in whole Europe.

Web browsers provide access to the data management, simulation and analysis environment. It enables high-speed, large-scale and cross-organizational market forecasts. Runs can be efficiently parameterized, carried out by one click and visually analyzed for historical and future scenarios.

Users get support by various tool kits, comprehensive data quality checks and geographical visualizations. Results like market prices, unit-wise volumes and exchanges are prepared for social welfare analysis, power-flow simulations and techno-economic assessments.

Based on C++, OpenMPI, CPLEX. Using Kubernetes, Docker, Ansible, Ceph, MinIO, MongoDB, Preact, Node.js, GraphQL, Python, WebAssembly, cURL for data processing.

Website / Documentation
Download

Not Open Source

Not directly downloadable

Input data shipped

Not planned to open up further in the future

Model Scope

Model type and solution approach

Model class	Mixed-Integer Quadratic Programming (MIQP)
Sectors	Electricity, gas and emissions plus couplings (industry, heat, transport)
Technologies	Renewables, Conventional Generation, CHP
Decisions	dispatch, investment
Regions	ENTSO-E members
Geographic Resolution	Individual power stations
Time resolution	Hour
Network coverage	transmission, distribution, AC load flow, DC load flow, net transfer capacities

Model type	Optimization, Simulation, Other, Agent-based

Variables	1000000000
Computation time	1000 minutes (8760 coupled hours for ENTSO-E region includig renewable, thermal, hydro, battery, CHP, PtG, DSR, FBMC and on-off decision model)
Objective	Maximization of social welfare at electricity spot, frequency reserve, natural gas and emission markets in Europe
Uncertainty modeling	Monte Carlo, preprocessing or sensitivity
Suited for many scenarios / monte-carlo	Yes

References

Scientific references

Ketov, Mihail (2019). "Marktsimulationen unter Berücksichtigung der Strom-Wärme-Sektorenkopplung", Print Production, Aachener Beiträge zur Energieversorgung, volume 189, PhD thesis, RWTH Aachen University.

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Author institution	Maon GmbH +
Authors	Mihail Ketov, Fabian Pfannes, Huangluolun Zhou, Nicolai Schmid, Dariush Wahdany, Yash Patel, Kaan Gecü, Ömer Bilgin, Esmanur Eryilmaz, Ali Baran Gündüz, Marios Morfopoulos, Sangeetha Kadarkarai, Mark Schäfer, Kai Strunz, Albert Moser +
Citation references	Ketov, Mihail (2019). "Marktsimulationen unter Berücksichtigung der Strom-Wärme-Sektorenkopplung", Print Production, Aachener Beiträge zur Energieversorgung, volume 189, PhD thesis, RWTH Aachen University.
Computation time comments	8760 coupled hours for ENTSO-E region includig renewable, thermal, hydro, battery, CHP, PtG, DSR, FBMC and on-off decision model
Computation time minutes	1,000 +
Contact email	info@maon.eu +
Contact persons	Dr. Mihail Ketov +
Data availability	all +
Decisions	dispatch + and investment +
Deterministic	Monte Carlo, preprocessing or sensitivity +
Full Model Name	Maon +
Georegions	ENTSO-E members +
Georesolution	Individual power stations +
Is suited for many scenarios	true +
Math modeltype	Optimization +, Simulation +, Other + and Agent-based +
Math objective	Maximization of social welfare at electricity spot, frequency reserve, natural gas and emission markets in Europe +
Model class	Mixed-Integer Quadratic Programming (MIQP) +
Model source public	false +
Modelling software	C++, OpenMPI, CPLEX +
Network coverage	transmission +, distribution +, AC load flow +, DC load flow + and net transfer capacities +
Number of variables	1,000,000,000 +
Open future	false +
Open source licensed	false +
Processing software	Kubernetes, Docker, Ansible, Ceph, MinIO, MongoDB, Preact, Node.js, GraphQL, Python, WebAssembly, cURL +
Sectors	Electricity +, gas and emissions plus couplings (industry +, heat + and transport) +
Source download	https://apis.cloud.maon.eu/ +
Technologies	Renewables +, Conventional Generation + and CHP +
Text description	Maon is a fundamental simulation environme … Maon is a fundamental simulation environment for electricity, gas and emission market analysis. The model simulates the annual coupled dispatch of all supply and demand for 8760 hours in whole Europe. Web browsers provide access to the data management, simulation and analysis environment. It enables high-speed, large-scale and cross-organizational market forecasts. Runs can be efficiently parameterized, carried out by one click and visually analyzed for historical and future scenarios. Users get support by various tool kits, comprehensive data quality checks and geographical visualizations. Results like market prices, unit-wise volumes and exchanges are prepared for social welfare analysis, power-flow simulations and techno-economic assessments.mulations and techno-economic assessments.
Timeresolution	Hour +
Website	https://cloud.maon.eu/handbook +

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