Documentation of POMATO

POMATO stands for (POwer MArket TOol).

POMATO stands for (POwer MArket TOol), it is very good 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.

Model Structure

The model is structured in three interconnected parts:

  • Data Management: Data input, processing and result analysis.

  • Market Model: Calculation of the economic dispatch based on the dataset and chosen grid representation.

  • Grid Model: Providing grid representation for economic dispatch calculation in chosen granularity (N-0, N-1, FBMC, NTC, copperplate) and analysis for ex-post analysis of the market result.

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 julia components MarketModel and RedundancyRemoval are housed in their separate repositories and will be installed with POMATO.

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 3.7 by any version >= 3.6 should be compatible.

  • Install julia for your operating system. POMATO is written and tested with 1.5, but the newest version 1.6 works as well, but throws some warnings.

  • 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 the 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 ELMOD-DE which is openly available and described in detail in DIW DataDocumentation 83 which represents a more complex system and can be run for longer model horizon (although shortened to allow to host this data in this git):

    $ python /run_pomato_de.py

See more in depth descriptions of this two case studies part of the POMATO Documentation <https://pomato.readthedocs.io/en/latest/running_pomato.html>`_.

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 is part of my PhD and actively developed by Robert and myself. This means it will keep changing to include new functionality or to improve existing features. The existing examples, which are also part of the Getting Started guide in the documentation, are part of a testing suite to ensure some robustness. However, we are not software engineers, 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.

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 is funded by the Reiner Lemoine-Foundation scholarship. Richard Weinhold is funded by the Danish Energy Agency. The development of POMATO and its applications was 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).

Description of the Modules