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Publications and Downloads

In this section you can download the diverse information material, press releases and results produced for NEMO. This area will be updated regularly. Please note that at the moment it is too early to provide any results of the project.

NEMO Project Flyer

Overview and short informations about the NEMO project

PDF document icon Flyer_NEMO-Project_2013.pdf — PDF document, 1.20 MB (1259798 bytes)

PDF document icon Jan-2013_Press-Release_NEMO_Final.pdf — PDF document, 288 KB (294949 bytes)

Fachbeitrag "Integration von eFahrzeugen in Stromnetze" in der Fachzeitschrift "NEUE MOBILITÄT"

Die Elektrifizierung von Fahrzeugen im Sinne einer nachhaltigen Mobilität schreitet voran. Elektrofahrzeuge ermöglichen eine direkte Nutzung des aus regenerativen Quellen stammenden Stroms. Eine Voraussetzung ist die Bereitstellung einer adäquaten Ladeinfrastruktur. Für Netzbetreiber ergibt sich die Herausforderung, die Fahrzeug-Ladeprofile und damit verbundenen Stromflüsse zu prognostizieren, die Netzinfrastruktur an verschiedenste Ladeszenarien anzupassen und Regeln für ein langfristig robustes Zusammenspiel von Elektrofahrzeugen, erneuerbarer Stromerzeugung und Stromnetzen in einem ökonomisch effizienten Rahmen zu schaffen. Im Projekt NEMO entwickelt ein internationales Forschungsteam aus Holland, Deutschland und Dänemark ein Modellierungs-Framework, um die genannten Fragestellungen zu untersuchen.

PDF document icon 201304_NEUE-MOBILITAET_Integration-von-eFahrzeugen-in-Stromnetze.pdf — PDF document, 90 KB (92822 bytes)

Summary of Challenges and Framework Conditions to Integrate Electric Vehicles into Electricity Grids

Deliverable 1.1, report. The work is part of task T1.1 »Description of distribution grid simulation as well as optimization tasks and challenges«, task T1.3 »Framework conditions«, task T1.4 »Gaps and structural problems« and leads into D1.1 »Summary of Challenges and Framework Conditions to Integrate Electric Vehicles into Electricity Grids«.

PDF document icon NEMO_D1.1_Report_V2G-Challenges-and-Framework-Conditions_201305_Final.pdf — PDF document, 1.41 MB (1482024 bytes)

Analysis of the Exploitation of EV Fast Charging to Prevent Extensive Grid Investments in Suburban Areas

Voltage control decreases the need for conventional grid reinforcement: We analyze the extent to which voltage control strategies decrease critical voltage levels compared to uncontrolled charging of EV in suburban low voltage grids. If in the underlying grid at the same time both active and reactive power control is applied for all sub-scenarios the volume and frequency of power limitation is reduced and in most cases a power limitation of 2 kW satisfies the voltage boundaries.


DOI: 10.1002/ente.201300077

Authors: Kilian Dallmer-Zerbe,Thies Stillahn, Thomas Erge, Bernhard Wille-Haussmann, and
Christof Wittwer

Energy Technology

Volume 2, Issue 1, pages 54–63, January 2014

Anticipation and simulative analysis of electric grid problems caused by electric vehicles

Electric vehicles (EV) are one element of the future transition towards a clean and sustainable energy system, since they can be powered by electricity generated by wind, photovoltaics (PV) and other renewable energy sources. With their ability of decentralized storage of electricity they can even contribute to solving the challenge of leveling out fluctuating generation by shifting demand or re-feeding electricity into the grid. For grid operators it is necessary to anticipate grid problems resulting from the new dynamic energy flows between EV, grid and renewables, and to contrive smart and cost effective measures counteracting such problems. A research team in the European project NEMO develops a tool suite able to simulate the grid impact of EV charging stations and helping to tailor technical solutions to different application cases.


Authors: Thomas Erge, Kilian Dallmer-Zerbe, Thies Stillahn, Bernhard Wille-Haussmann, Anders N. Andersen, Jos van der Burgt

8th International Renewable Energy Storage Conference and Exhibition (IRES 2013), Proceedings, Berlin, bcc Berlin Congress Center, November 18-20, 2013

NEMO – a novel techno-economic tool suite for simulating and optimizing solutions for grid integration of electric vehicles and charging stations

With an increasing use of electric vehicles (EV) grid operators need to predict energy flows depending on electromobility use profiles to accordingly adjust grid infrastructure and operation control accordingly. Tools and methodologies are required to characterize grid problems resulting from the interconnection of EV with the grid. The simulation and optimization tool suite NEMO (Novel E-MObility grid model) was developed within a European research project and is currently being tested using realistic showcases. It is a combination of three professional tools. One of the tools aims at a combined techno-economic design and operation, primarily modeling plants on contracts or the spot market, at the same time participating in balancing markets. The second tool is designed for planning grid extension or reinforcement while the third tool is mainly used to quickly discover potential conflicts of grid operation approaches through load flow analysis. The tool suite is used to investigate real showcases in Denmark, Germany and the Netherlands. First studies show that significant alleviation of stress on distribution grid lines could be achieved by few but intelligent restrictions to EV charging procedures.


Authors: Dr. Thomas Erge, Thies Stillahn, Kilian Dallmer-Zerbe, Dr. Bernhard Wille-Haussmann

Internationaler ETG-Kongress 2013 – Energieversorgung auf dem Weg nach 2050 - Symposium 1: Security in Critical Infrastructures Today, 05.11.2013 - 06.11.2013 in Berlin, Deutschland

New report online: Handling abnormal charging situations. Evaluation of tool application, manual and tool set reference

The report summarizes the findings of the “Abnormal charging” use case. These situations are characterized by irregular load requirements which occur only during limited time intervals that lead to singular charging requirements where the requested load profiles are untypical for EV prohibiting application of common grid design tools and methodologies. These situations are characterized by strongly varying load profiles with only limited long-term predictability. Any significant short-term change of the EV charging profiles leads to a serious technical problem. Typical examples are events where a larger number of people are gathering at one spot such as sports or festivals. The report describes how the NEMO tool suite was applied for three different show cases in order to derive implications for manuals for abnormal charging situations. Authors: Dr.-Ing. Bernhard Wille-Haussmann (Fraunhofer ISE), Kilian Dallmer-Zerbe (Fraunhofer ISE), Muhammad Imran (Fraunhofer ISE), Thies Stillahn (Fraunhofer ISE), Jos van der Burgt (DNV GL), Santiago Penate Vera (DNV GL)

PDF document icon NEMO_D6.2-D6.3_report_Fraunhofer_Final_public.pdf — PDF document, 1.68 MB (1764182 bytes)

Report: NEMO Showcase Designer and Simulation Tool Suite

The NEMO process for automized grid planning has been automated in the NEMO showcase designer. The function is implemented in the programming language R and is based on the sub-function design and calculation. Interfacing is possible via com-mand line or graphical user interface. The command line operation requires simulation settings and parameters to be defined within the NEMO showcase simulator script in R. The graphical interface version has basically the same functionality as a front end user inter-face where the parameter settings can be provided in a user friendly manner.

PDF document icon NEMO_White-Paper_Show-Case-Designer.pdf — PDF document, 1.62 MB (1700059 bytes)

Tutorial of the NEMO Show Case Designer for automized grid planning

Within the following tutorial the NEMO Show Case designer is explained for users with potential grid issues in electricity grids and an interest in getting to know innovative tools for automized grid planning.

AVI video icon NEMO_Show-Case-Designer_Tutorial.avi — AVI video, 68.24 MB (71557040 bytes)

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