Mihail Ketov, Fabian Breitkreutz, Yash Patel, Elias El Abd, Mihael Nikolić, Nicolai Schmid, Dariush Wahdany, Aiwen Wang, Mark Schäfer, Anton Kucherenko, Söhnke Hartmann, Huangluolun Zhou, Kai Strunz, Albert Moser
Maon GmbH, Documentation, https://docs.cloud.maon.eu.
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, without facility-wise aggregations
Monte Carlo, preprocessing or sensitivity
Minimization of dispatch and investment cost
Mixed-Integer Quadratic Programming (MIQP)
Ansible, Ceph, cURL, Docker, GraphQL, Kubernetes, MinIO, MongoDB, Node.js, Preact, Python, tusd, TypeScript, WebAssembly
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 measures.