Maon

Authors:
Mihail Ketov, Fabian Breitkreutz, Yash Patel, Sangeetha Kadarkarai, Hajar Mouchrik, Nicolai Schmid, Dariush Wahdany, Kaan Gecü, Ömer Bilgin, Esmanur Eryilmaz, Ali Baran Gündüz, Mark Schäfer, Kai Strunz, Albert Moser

Contact:
Dr. Mihail Ketov

Maon is a market simulation for fundamental electricity, gas, and emission market analysis. It forecasts the facility-wise hourly dispatch of all supply and demand in whole Europe.

Web browsers provide access to the data management, simulation, and analysis environment. It enables high-speed, high-resolution, and large-scale foresights. Scenarios can be parameterized by multiple users at the same time, calculated by one click, and collaboratively visually analyzed.

Users get support by work-leveraging parameterization tools, comprehensive quality checks, and interactive visualizations. Maon provides not only results like prices, dispatches, and exchanges, but also revenues, costs, utilizations, capture rates, price distributions, and thousands of other results.

Based on C++. Using Ansible, Ceph, cURL, Docker, GraphQL, Kubernetes, MinIO, MongoDB, Node.js, Preact, Python, TypeScript, WebAssembly 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	Europe, North Africa, Middle East
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 full European region with spot, FCR, aFRR, mFRR, emission, renewable, thermal, hydro, battery, CHP, PtG, DSR, FBMC, AHC, HVDC and on-off decision model, but without facility-wise aggregations)
Objective	Minimization of operational costs for electricity spot and frequency reserve markets considering emission caps
Uncertainty modeling	Monte Carlo, preprocessing or sensitivity
Suited for many scenarios / monte-carlo	Yes

References

Scientific references

Maon GmbH, Handbook, https://cloud.maon.eu/handbook.

Reports produced using the model

https://maon.eu/publications

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Author institution	Maon GmbH +
Authors	Mihail Ketov, Fabian Breitkreutz, Yash Patel, Sangeetha Kadarkarai, Hajar Mouchrik, Nicolai Schmid, Dariush Wahdany, Kaan Gecü, Ömer Bilgin, Esmanur Eryilmaz, Ali Baran Gündüz, Mark Schäfer, Kai Strunz, Albert Moser +
Citation references	Maon GmbH, Handbook, https://cloud.maon.eu/handbook.
Computation time comments	8760 coupled hours for full European region with spot, FCR, aFRR, mFRR, emission, renewable, thermal, hydro, battery, CHP, PtG, DSR, FBMC, AHC, HVDC and on-off decision model, but without facility-wise aggregations
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	Europe, North Africa, Middle East +
Georesolution	Individual power stations +
Is suited for many scenarios	true +
Math modeltype	Optimization +, Simulation +, Other + and Agent-based +
Math objective	Minimization of operational costs for electricity spot and frequency reserve markets considering emission caps +
Model class	Mixed-Integer Quadratic Programming (MIQP) +
Model source public	false +
Modelling software	C++ +
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	Ansible, Ceph, cURL, Docker, GraphQL, Kubernetes, MinIO, MongoDB, Node.js, Preact, Python, TypeScript, WebAssembly +
Report references	https://maon.eu/publications
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 market simulation for fundamenta … Maon is a market simulation for fundamental electricity, gas, and emission market analysis. It forecasts the facility-wise hourly dispatch of all supply and demand in whole Europe. Web browsers provide access to the data management, simulation, and analysis environment. It enables high-speed, high-resolution, and large-scale foresights. Scenarios can be parameterized by multiple users at the same time, calculated by one click, and collaboratively visually analyzed. Users get support by work-leveraging parameterization tools, comprehensive quality checks, and interactive visualizations. Maon provides not only results like prices, dispatches, and exchanges, but also revenues, costs, utilizations, capture rates, price distributions, and thousands of other results.ributions, and thousands of other results.
Timeresolution	Hour +
Website	https://cloud.maon.eu/handbook +

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Help

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Search

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Maon

References

Scientific references

Reports produced using the model