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| Line 21: |
Line 21: |
| | |open_future=No | | |open_future=No |
| | |modelling_software=C++ | | |modelling_software=C++ |
| − | |processing_software=Kubernetes, Docker, Ceph, MinIO, MongoDB, Preact, Node.js, GraphQL, Python, WebAssembly, GCC, cURL, OpenMPI, IBM CPLEX | + | |processing_software=Kubernetes, Docker, Ceph, Ansible, MinIO, MongoDB, Preact, Node.js, GraphQL, Python, WebAssembly, GCC, cURL, OpenMPI, IBM CPLEX |
| | |External optimizer=IBM CPLEX | | |External optimizer=IBM CPLEX |
| | |Additional software=Only browser and internet connection required | | |Additional software=Only browser and internet connection required |
| Line 52: |
Line 52: |
| | |computation_time_comments=backtesting 2018 with detailed hydro, CHP, DSR and FBMC model in hourly resolution with all ENTSO-E bidding zones | | |computation_time_comments=backtesting 2018 with detailed hydro, CHP, DSR and FBMC model in hourly resolution with all ENTSO-E bidding zones |
| | |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. | | |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. |
| | + | |Interfaces=https://apis.cloud.maon.eu/ and web browser interface |
| | |Model input file format=No | | |Model input file format=No |
| | |Model file format=No | | |Model file format=No |
| | |Model output file format=No | | |Model output file format=No |
| | }} | | }} |
|
Maon
by Maon GmbH
Authors:
Mihail Ketov, Fabian Pfannes, Huangluolun Zhou, Dariush Wahdany, Nicolai Schmid
Contact:
Dr.-Ing. Mihail Ketov
|
Maon is an integrated digital platform for electricity market and system analysis. The included electricity market model simulates the annual dispatch of all supply and demand in every bidding zone in Europe.
Web browsers provide access to the simulation suite that derives electricity price and transmission grid usage forecasts. Runs can be carried out immediately with calibrated input data 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++. Using Kubernetes, Docker, Ceph, Ansible, MinIO, MongoDB, Preact, Node.js, GraphQL, Python, WebAssembly, GCC, cURL, OpenMPI, IBM CPLEX for data processing.
Website / Documentation
|
 Not Open Source
Not directly downloadable
No 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
|
| 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
|
|
|
|
| Variables
|
100000000
|
| Computation time
|
1000 minutes (backtesting 2018 with detailed hydro, CHP, DSR and FBMC model in hourly resolution with all ENTSO-E bidding zones)
|
| Objective
|
Economic welfare at electricity spot, electricity reserve, and emission markets in Europe
|
| Uncertainty modeling
|
|
| Suited for many scenarios / monte-carlo
|
No
|
|
Ketov, Mihail (2019). "Marktsimulationen unter Berücksichtigung der Strom-Wärme-Sektorenkopplung", Print Production, Aachener Beiträge zur Energieversorgung, volume 189, PhD thesis, RWTH Aachen University.
