Name IAEW Marktsimulation
Acronym MarS
Methodical Focus None
Institution(s) Institute of Power Systems and Power Economics (IAEW) at RWTH Aachen University
Author(s) (institution, working field, active time period) Dr. T. Mirbach (developer; 5 years); Dr. T. Drees (developer; 5 years); M. Ketov (developer; 4 years) et al.
Current contact person Mihail Ketov
Contact (e-mail) ke@iaew.rwth-aachen.de
Website
Logo
Primary Purpose price forecasts, nodal dispatch
Primary Outputs power plant dispatch, prices, commercial flows, redispatch potential
Support / Community / Forum
Framework
Link to User Documentation
Link to Developer/Code Documentation
Documentation quality good
Source of funding various projects for the energy industry
Number of developers less than 20
Number of users less than 100
Open Source
Planned to open up in the future
Costs no single use license available
Modelling software not given
Internal data processing software Linux; Fortran; C
External optimizer
Additional software Parametrization GUI of IAEW
GUI
Citation reference "- T. Drees: ""Simulation des europäischen Binnenmarktes für Strom und Regelleistung bei hohem Anteil erneuerbarer Energien"", Aachener Beiträge zur Energieversorgung Bd. 166 - F. Grote, A. Maaz, T. Drees, A. Moser: ""Modeling of Electricity Pricing in European Market Simulations"" 12th International Conference on the European Energy Market (EEM); Lisbon (PRT); 18.05.2015 – 21.05.2015 -T. Drees, A. Moser: ""Macroeconomic Benefit of Integrated Markets for Reserve Balancing in Europe"" EEM 2016 – 13th International Conference on the European Energy Market; Porto (PRT); 05.06.2016 – 08.06.2016"
Citation DOI
Reference Studies/Models German Bedarfsanalyse of the 4 TSOs
Example research questions What is the impact of a growing penetration of renwables on European market prices and the dispatch?
Model usage NDA
Model validation -
Example research questions What is the impact of a growing penetration of renwables on European market prices and the dispatch?
further properties
Model specific properties
Modeled energy sectors (final energy) electricity, heat
Modeled demand sectors Households, Industry, Commercial sector
Modeled technologies: components for power generation or conversion
Renewables PV, Wind, Hydro, Solar thermal
Conventional gas, oil, liquid fuels, nuclear
Modeled technologies: components for transfer, infrastructure or grid
Electricity -
Gas -
Heat distribution
Properties electrical grid DC load flow
Modeled technologies: components for storage battery, kinetic, compressed air, pump hydro, chemical, heat, gas
User behaviour and demand side management demand shifting with given time series of potential in regard to absolute amount and shifting time
Changes in efficiency
Market models -
Geographical coverage
Geographic (spatial) resolution Scope: All Bidding Zones in ENTSO-E region, resolution power stations
Time resolution hour
Comment on geographic (spatial) resolution
Observation period 1 year
Additional dimensions (sector) economic, additional dimensions sector economic text
Model class (optimisation) -
Model class (simulation) -
Other
Short description of mathematical model class MIQP, solved by Lagrangian decomposition
Mathematical objective costs
Approach to uncertainty Deterministic
Suited for many scenarios / monte-carlo
typical computation time less than a day
Typical computation hardware 8 cores of 2 GHz, 75 GB RAM
Technical data anchored in the model
Interfaces
Model file format Other
Input data file format text
Output data file format .csv
Integration with other models linked to IAEW redispatch model
Integration of other models

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