User:RobbieIanMorrison/sandbox/work in progress ush7Fa

Development for lead up material for Open energy system models


 * prior diff: 3 November 2016 diff

eGo
eGo is a transparent grid planning tool to investigate economically viable grid expansion scenarios considering alternative flexibility options such as storage units and redispatch over all voltage levels in Germany. It simulates the basic functioning of the electricity market taking into account the physical AC load flow behavior. eGo combines eTraGo - a tool for optimizing flexibility options for transmission grids based on PyPSA - and eDisGo - a toolbox to evaluate flexibility measures as an economic alternative to conventional grid expansion in medium and low voltage grids.

eGo is a software project that was developed by the Reiner Lemoine Institut, Berlin, Germany in cooperation with the Center for Sustainable Energy Systems (CSES or ZNES) at the University of Flensburg, the German Aerospace Center and the Otto von Guericke University Magdeburg, as part of the research project open_eGo.

Within this project, the OpenEnergy Platform was developed, which the eGo toolbox relies upon to get and store in- and output data.

MODEX project on resolution and disaggregation.

Ding0
Ding0, the DIstribution Network GeneratOr, was developed as part of the reasearch project open_eGo by the Reiner Lemoine Institut, Berlin, Germany. The open_eGo project was funded by the Federal Ministry for Economic Affairs and Climate Action in the context of the funding initiative „Optimization of the Energy Supply System“. The goal of that project was to create a transparent, inter-grid-level operating grid planning tool to investigate economic viable grid expansion scenarios considering alternative flexibility options such as storages or redispatch. Ding0 itself is a tool to generate synthetic medium voltage (MV) and low voltage (LV) power distribution grids based on open (or at least accessible) data. It provides MV-grids with open ring topologies for suburban and rural German areas. The fundamental data basis is decribed in [Huelk2017] and its extension is detailed by [Amme2017].

Potential references

 * Wienholt et al (work in progress) on waypoint modeling
 * Bartels (2018) on a data-model for the German electricity network
 * Schachler (2018) on distribution network planning
 * Amme (2018) on synthetic network generation
 * Müller and Büttner (2018) on high-voltage transmission optimization
 * Bunke (2018) on project overview
 * Hülk et al (2017) on grid modeling
 * Liere-Netheler et al (2021) on open_eGo datasets
 * Peters et al (2020) on a high voltage grid model
 * Amme et al (2018) on medium voltage modeling