Maon

Authors:
Mihail Ketov, Fabian Breitkreutz, Yash Patel, Sangeetha Kadarkarai, Hajar Mouchrik, Nicolai Schmid, Dariush Wahdany, Kaan Gecü, Ömer Bilgin, Ali Baran Gündüz, Anton Kucherenko, Söhnke Hartmann, Kai Strunz, Albert Moser

Contact:
Dr. Mihail Ketov

Maon is a market simulation for fundamental electricity wholesale market analysis. It forecasts the facility-level quarter-hourly dispatch of all supply and demand across a continent. Further, it can predict capacities and uncertainties of generators, interconnectors, storages, and consumers.

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 capacities, but also capture rates, costs, price distributions, revenues, utilizations, and many other parameters.

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

Website / Documentation

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 plus couplings (industry, commercial, households, 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 (dispatch for 8760 coupled hours in 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 dispatch and investment cost
Uncertainty modeling	Monte Carlo, preprocessing or sensitivity
Suited for many scenarios / monte-carlo	Yes

References

Scientific references

Maon GmbH, Documentation, https://docs.cloud.maon.eu.

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, Ali Baran Gündüz, Anton Kucherenko, Söhnke Hartmann, Kai Strunz, Albert Moser +
Citation references	Maon GmbH, Documentation, https://docs.cloud.maon.eu.
Computation time comments	dispatch for 8760 coupled hours in 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 dispatch and investment cost +
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 plus couplings (industry +, commercial +, households + and transport) +
Source download
Technologies	Renewables +, Conventional Generation + and CHP +
Text description	Maon is a market simulation for fundamenta … Maon is a market simulation for fundamental electricity wholesale market analysis. It forecasts the facility-level quarter-hourly dispatch of all supply and demand across a continent. Further, it can predict capacities and uncertainties of generators, interconnectors, storages, and consumers. 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 capacities, but also capture rates, costs, price distributions, revenues, utilizations, and many other parameters., utilizations, and many other parameters.
Timeresolution	Hour +
Website	https://maon.eu +

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References

Scientific references

Reports produced using the model