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| |citation_doi=0.1109/TPWRS.2020.2994764 | | |citation_doi=0.1109/TPWRS.2020.2994764 |
− | |report_references= | + | |report_references=Schönheit, Weinhold, Dierstein (2020), The impact of different strategies for generation shift keys (GSKs) on the flow-based market coupling domain: A model-based analysis of Central Western Europe. DOI: 10.1016/j.apenergy.2019.114067 |
− | Schönheit, Weinhold, Dierstein (2020), The impact of different strategies for generation shift keys (GSKs) on the flow-based market coupling domain: A model-based analysis of Central Western Europe. DOI: 10.1016/j.apenergy.2019.114067 | + | |
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Revision as of 11:04, 23 October 2020
Power Market Tool
by TU Berlin
Authors: Richard Weinhold, Robert Mieth
Contact: Richard Weinhold
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POMATO stands for (POwer MArket TOol) and is an easy to use tool for the comprehensive analysis of the modern electricity market. It comprises the necessary power engineering framework to account for power flow physics, thermal transport constraints and security policies of the underlying transmission infrastructure, depending on the requirements defined by the user. POMATO was specifically designed to realistically model Flow-Based Market-Coupling (FBMC) and is therefore equipped with a fast security constrained optimal power flow algorithm and allows zonal market clearing with endogenously generated flow-based parameters, and redispatch.
Based on Julia/JuMP. Using Python for data processing.
Website / Documentation
Download
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Open Source GNU Library or "Lesser" General Public License version 3.0 (LGPL-3.0)
Directly downloadable
Some input data shipped
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Model Scope |
Model type and solution approach |
Model class
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Network-constrained Unit Commitment and Economic Dispatch
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Sectors
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Electricity Market, Heat
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Technologies
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Renewables, Conventional Generation, CHP
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Decisions
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dispatch
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Regions
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User-dependent
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Geographic Resolution
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Nodal resolution
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Time resolution
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Hour
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Network coverage
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transmission, DC load flow, net transfer capacities
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Model type
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Optimization
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Linear Economic Dispatch. Linear Optimal Power Flow. Linear Security Constrained Optimal Power Flow
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Variables
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Computation time
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minutes
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Objective
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Cost minimization
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Uncertainty modeling
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Chance Constrained
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Suited for many scenarios / monte-carlo
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No
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References
Scientific references
Weinhold and Mieth (2020), Fast Security-Constrained Optimal Power Flow through Low-Impact and Redundancy Screening.
https://dx.doi.org/0.1109/TPWRS.2020.2994764
Reports produced using the model
Schönheit, Weinhold, Dierstein (2020), The impact of different strategies for generation shift keys (GSKs) on the flow-based market coupling domain: A model-based analysis of Central Western Europe. DOI: 10.1016/j.apenergy.2019.114067
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