Maon

Revision as of 20:30, 24 November 2022

Maon

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

Contact:
Dr. Mihail Ketov

Maon is a fundamental simulation environment for electricity market and system analysis. The model simulates the annual coupled dispatch of all supply and demand for 8760 hours in all bidding zones in Europe.

Web browsers provide access to the simulation and data management suite that derives electricity price and transmission grid usage forecasts. Runs can be carried out immediately with inputs for historical and future scenarios.

Users get support by processing tool kits, data quality checks and geographical visualizations. Unit commitment and market price results are prepared for applications like social welfare analysis or power-flow simulations.

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 plus sector couplings (industry, heat, transport, gas)
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 total social welfare at electricity spot, frequency reserve 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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@@ Line 3: / Line 3: @@
 |Acronym=Maon
 |author_institution=Maon GmbH
-|authors=Mihail Ketov, Fabian Pfannes, Huangluolun Zhou, Nicolai Schmid, Dariush Wahdany, Yash Patel, Stefan Junk, Martin Mitev, Kaan Gecü, Ömer Bilgin, Esmanur Eryilmaz, Ali Baran Gündüz, Marios Morfopoulos, Mark Schäfer, Sangeetha Kadarkarai, Kai Strunz, Albert Moser
+|authors=Mihail Ketov, Fabian Pfannes, Huangluolun Zhou, Nicolai Schmid, Dariush Wahdany, Yash Patel, Stefan Junk, Martin Mitev, Kaan Gecü, Ömer Bilgin, Esmanur Eryilmaz, Ali Baran Gündüz, Marios Morfopoulos, Sangeetha Kadarkarai, Kai Strunz, Albert Moser
 |contact_persons=Dr. Mihail Ketov
 |contact_email=info@maon.eu

Author institution	Maon GmbH +
Authors	Mihail Ketov, Fabian Pfannes, Huangluolun Zhou, Nicolai Schmid, Dariush Wahdany, Yash Patel, Stefan Junk, Martin Mitev, Kaan Gecü, Ömer Bilgin, Esmanur Eryilmaz, Ali Baran Gündüz, Marios Morfopoulos, Sangeetha Kadarkarai, 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 total social welfare at electricity spot, frequency reserve 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 plus sector couplings (industry +, heat +, transport + and gas) +
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 market and system analysis. The model simulates the annual coupled dispatch of all supply and demand for 8760 hours in all bidding zones in Europe. Web browsers provide access to the simulation and data management suite that derives electricity price and transmission grid usage forecasts. Runs can be carried out immediately with inputs for historical and future scenarios. Users get support by processing tool kits, data quality checks and geographical visualizations. Unit commitment and market price results are prepared for applications like social welfare analysis or power-flow simulations.elfare analysis or power-flow simulations.
Timeresolution	Hour +
Website	https://cloud.maon.eu/handbook +

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Revision as of 20:30, 24 November 2022

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Help

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Search

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Maon

Revision as of 20:30, 24 November 2022

References

Scientific references