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| |Acronym=Maon | | |Acronym=Maon |
| |author_institution=Maon GmbH | | |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 | + | |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_persons=Dr. Mihail Ketov | | |contact_persons=Dr. Mihail Ketov |
| |contact_email=info@maon.eu | | |contact_email=info@maon.eu |
| |website=https://cloud.maon.eu/handbook | | |website=https://cloud.maon.eu/handbook |
− | |source_download=https://apis.cloud.maon.eu/ | + | |source_download=https://apis.cloud.maon.eu |
| |logo=Maon Colors Frontpage Header.png | | |logo=Maon Colors Frontpage Header.png |
− | |text_description=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. | + | |text_description=Maon is a market simulation for fundamental electricity, gas, and emission market analysis. It forecasts the facility-wise quarter-hourly dispatch of all supply and demand in whole Europe. Further, it can predict capacities and uncertainties of generators, interconnectors, storages, and consumers. |
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− | 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. | + | 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. |
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− | 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. | + | 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 thousands of other results. |
| |Support=commercial | | |Support=commercial |
| |User documentation=https://cloud.maon.eu/handbook | | |User documentation=https://cloud.maon.eu/handbook |
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| |data_availability=all | | |data_availability=all |
| |open_future=No | | |open_future=No |
− | |modelling_software=C++, OpenMPI, CPLEX | + | |modelling_software=C++ |
− | |processing_software=Kubernetes, Docker, Ansible, Ceph, MinIO, MongoDB, Preact, Node.js, GraphQL, Python, WebAssembly, cURL | + | |processing_software=Ansible, Ceph, cURL, Docker, GraphQL, Kubernetes, MinIO, MongoDB, Node.js, Preact, Python, TypeScript, WebAssembly |
− | |External optimizer=CPLEX
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| |Additional software=Only browser and internet connection required | | |Additional software=Only browser and internet connection required |
| |GUI=Yes | | |GUI=Yes |
| |model_class=Mixed-Integer Quadratic Programming (MIQP) | | |model_class=Mixed-Integer Quadratic Programming (MIQP) |
− | |sectors=Electricity plus sector couplings (industry, heat, transport, gas) | + | |sectors=Electricity, gas and emissions plus couplings (industry, heat, transport) |
| |technologies=Renewables, Conventional Generation, CHP | | |technologies=Renewables, Conventional Generation, CHP |
| |Demand sectors=Households, Industry, Transport, Commercial sector, Other | | |Demand sectors=Households, Industry, Transport, Commercial sector, Other |
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| |Energy carriers (Renewable)=Geothermal heat, Hydro, Sun, Wind | | |Energy carriers (Renewable)=Geothermal heat, Hydro, Sun, Wind |
| |Transfer (Electricity)=Distribution, Transmission | | |Transfer (Electricity)=Distribution, Transmission |
| + | |Transfer (Gas)=Distribution, Transmission |
| + | |Transfer (Heat)=Distribution, Transmission |
| |Storage (Electricity)=Battery, CAES, Chemical, Kinetic, PHS | | |Storage (Electricity)=Battery, CAES, Chemical, Kinetic, PHS |
| |Storage (Gas)=Yes | | |Storage (Gas)=Yes |
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| |decisions=dispatch, investment | | |decisions=dispatch, investment |
| |Changes in efficiency=Individual efficiency per operating point | | |Changes in efficiency=Individual efficiency per operating point |
− | |georegions=ENTSO-E members | + | |georegions=Europe, North Africa, Middle East |
| |georesolution=Individual power stations | | |georesolution=Individual power stations |
| |timeresolution=Hour | | |timeresolution=Hour |
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| |Observation period=Less than one month, Less than one year, More than one year | | |Observation period=Less than one month, Less than one year, More than one year |
| |math_modeltype=Optimization, Simulation, Other, Agent-based | | |math_modeltype=Optimization, Simulation, Other, Agent-based |
− | |math_objective=Maximization of total social welfare at electricity spot, frequency reserve and emission markets in Europe | + | |math_objective=Minimization of dispatch and investment cost |
| |deterministic=Monte Carlo, preprocessing or sensitivity | | |deterministic=Monte Carlo, preprocessing or sensitivity |
| |is_suited_for_many_scenarios=Yes | | |is_suited_for_many_scenarios=Yes |
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| |computation_time_minutes=1000 | | |computation_time_minutes=1000 |
| |computation_time_hardware=high performance computing cluster | | |computation_time_hardware=high performance computing cluster |
− | |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_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 |
− | |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=Maon GmbH, Handbook, https://cloud.maon.eu/handbook. |
− | |Interfaces=https://apis.cloud.maon.eu/ and web browser interface | + | |report_references=https://maon.eu/publications |
| + | |Interfaces=Front-end at https://cloud.maon.eu and APIS at https://apis.cloud.maon.eu |
| |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 |
| }} | | }} |