TY  - CHAP
A1  - Stollenwerk, Dominik
A1  - Franzke, Till
A1  - Maurer, Florian
A1  - Reinkensmeier, Sebastian
A1  - Kim, Franken
A1  - Tambornino, Philipp
A1  - Haas, Florian
A1  - Rieke, Christian
A1  - Hermanuz, Andreas
A1  - Borchert, Jörg
A1  - Ritz, Thomas
A1  - Sander, Volker
ED  - Proff, Heike
T1  - Smarte Ladesäulen : Netz- und Marktdienliches öffentliches Laden
T2  - Towards the New Normal in Mobility : Technische und betriebswirtschaftliche Aspekte
N2  - Stand 01.01.2022 sind in Deutschland 618.460 elektrisch angetriebene KFZ zugelassen. Insgesamt sind derzeit 48.540.878 KFZ zugelassen, was einer Elektromobilitätsquote von ca. 1,2 % entspricht. Derzeit werden Elektromobile über Ladestationen oder Steckdosen mit dem Stromnetz verbunden und üblicherweise mit der vollen Ladekapazität des Anschlusses aufgeladen, bis das Batteriemanagementsystem des Fahrzeugs abhängig vom Ladezustand der Batterie die Ladeleistung reduziert.
Y1  - 2023
SN  - 978-3-658-39437-0 (Print)
SN  - 978-3-658-39438-7 (Online)
U6  - http://dx.doi.org/10.1007/978-3-658-39438-7_18
SP  - 287
EP  - 304
PB  - Springer Gabler
CY  - Wiesbaden
ER  - 
TY  - JOUR
A1  - Maurer, Florian
A1  - Rieke, Christian
A1  - Schemm, Ralf
A1  - Stollenwerk, Dominik
T1  - Analysis of an urban grid with high photovoltaic and e-mobility penetration
JF  - Energies
N2  - This study analyses the expected utilization of an urban distribution grid under high penetration of photovoltaic and e-mobility with charging infrastructure on a residential level. The grid utilization and the corresponding power flow are evaluated, while varying the control strategies and photovoltaic installed capacity in different scenarios. Four scenarios are used to analyze the impact of e-mobility. The individual mobility demand is modelled based on the largest German studies on mobility “Mobilität in Deutschland”, which is carried out every 5 years. To estimate the ramp-up of photovoltaic generation, a potential analysis of the roof surfaces in the supply area is carried out via an evaluation of an open solar potential study. The photovoltaic feed-in time series is derived individually for each installed system in a resolution of 15 min. The residential consumption is estimated using historical smart meter data, which are collected in London between 2012 and 2014. For a realistic charging demand, each residential household decides daily on the state of charge if their vehicle requires to be charged. The resulting charging time series depends on the underlying behavior scenario. Market prices and mobility demand are therefore used as scenario input parameters for a utility function based on the current state of charge to model individual behavior. The aggregated electricity demand is the starting point of the power flow calculation. The evaluation is carried out for an urban region with approximately 3100 residents. The analysis shows that increased penetration of photovoltaics combined with a flexible and adaptive charging strategy can maximize PV usage and reduce the need for congestion-related intervention by the grid operator by reducing the amount of kWh charged from the grid by 30% which reduces the average price of a charged kWh by 35% to 14 ct/kWh from 21.8 ct/kWh without PV optimization. The resulting grid congestions are managed by implementing an intelligent price or control signal. The analysis took place using data from a real German grid with 10 subgrids. The entire software can be adapted for the analysis of different distribution grids and is publicly available as an open-source software library on GitHub.
KW  - distribution grid simulation
KW  - smart-charging
KW  - e-mobility
Y1  - 2023
U6  - http://dx.doi.org/10.3390/en16083380
SN  - 1996-1073
N1  - This article belongs to the Special Issue "Advanced Solutions for the Efficient Integration of Electric Vehicles in Electricity Grids"
N1  - Corresponding author: Florian Maurer
VL  - 16
IS  - 8
PB  - MDPI
CY  - Basel
ER  -