POMATO - Power Market Tool

Main Branch:

Construction Branch:

Documentation Status:

Overview

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.

Documentation

Comprehensive documentation is available at pomato.readthedocs.io.

Installation

POMATO is written in python and julia. Python takes care of the data processing
and julia runs the economic dispatch and N-1 redundancy removal algorithm.

The recommended way to install POMATO with python and pip:

• Install python for your operating system. On linux
  based operating systems python is often already installed and available under the python3
  command. For Windows install python into a folder of your choice. POMATO is written and tested
  in python 3.10.

• Install julia for your operating system. POMATO is
  written and tested with 1.9.

• Add python and julia to the system Path, this allows you to start python and julia
  directly for the command line without typing out the full path of the installation. PLattform
  specific instructions on how to do this are part of the julia installation
  instructions and work analogous for the python .

• Install POMATO through pip in python. It is recommended to create a virtual environment and
  install pomato into it, but not necessary:

  python -m venv pomato
  ./pomato/Scripts/activate
  pip install git+https://github.com/richard-weinhold/pomato.git
  

This will not only clone the master branch of this repository into the local python environment, but
also pull the master branch of the MarketModel and RedundancyRemoval julia packages which are
required to run POMATO. This process can take a few minutes to complete.

After this is completed pomato can be imported in python:

from pomato import POMATO

See the POMATO Documentation for
further information on the installation process.

Examples

This release includes two examples in the examples folder. Including the contents of this folder
into a pomato working directory will allow their execution:

• The IEEE 118 bus network, which contains a singular timestep. The data is available under
  open license at https://power-grid-lib.github.io/ and re-hosted in this repository.

  $ python /run_pomato_ieee.py
  

• The DE case study, based on data from openly available data sources. The file can be run via

  $ python /run_pomato_de.py
  

See more in depth descriptions of this two case studies along with a FBMC and chance constrained
examples, part of the POMATO
Documentation.

The examples folder also contains the two examples as Jupyter notebooks. Another possibility to
access the functionality of POMATO with an online REPL/Console when running POMATO inside a IDE with
an interactive IPython Console (e.g. Spyder) to access POMATO objects and variables.

Release Status

POMATO was part of my PhD that has concluded in 2021. The dissertation is available from
TU-Berlin and the
slides of the defence here in this repository
Link.

This means the model is no longer actively developed, although I try to have an eye on things. So
please feel free to contact me, but also know that POMATO is now a hobby that exists beside work.

I have tried to make everything robust by including a documentation and testing, but I am not a
software engineer, thus the "program" is not written with robustness in mind and our experience is
limited when it comes to common best practices. Expect errors, bug, funky behavior and code
structures from the minds of two engineering economists.

Related Publications

• Weinhold and Mieth (2023), Uncertainty-Aware Capacity Allocation in Flow-Based Market
  Coupling
• Weinhold (2022), Dissertation, Open-source modeling of flow based market
  coupling (Dissertation - Available from TU - Berlin).
• Weinhold (2021), Dissertation, Open-source modeling of flow based market
  coupling
  (Defence Slides).
• Weinhold (2020), Evaluating Policy Implications on the Restrictiveness of Flow-based Market
  Coupling with High Shares of Intermittent Generation: A Case Study for Central Western
  Europe
• Weinhold and Mieth (2021), Power Market Tool (POMATO) for the Analysis of Zonal
  Electricity Markets
• Weinhold and Mieth (2020), Fast Security-Constrained Optimal Power Flow through
  Low-Impact and Redundancy Screening
• 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

POMATO was also presented as part of the 2021 JuliaCon JuMP-dev train. The talk is available on
JuliaCon2021 youtube channel.

Acknowledgments

Richard and Robert would like to acknowledge the support of Reiner Lemoine-Foundation, the Danish
Energy Agency and Federal Ministry for Economic Affairs and Energy (BMWi). Robert Mieth was funded
by the Reiner Lemoine-Foundation scholarship. Richard Weinhold was funded by the Danish Energy
Agency through parts of the project. The development of POMATO and its applications was also funded
by BMWi in the project “Long-term Planning and Short-term Optimization of the German Electricity
System Within the European Context” (LKD-EU, 03ET4028A) and the project “Modellierung (De-)Zentraler
Energiewenden: Wechselwirkungen, Koordination und Lösungsansätze aus systemorientierter Perspektive”
(MODEZEEN, 03EI1019B).