Markus Gödde

Methodical approach for analyzing the impact of a mass introduction of electric vehicles on the electricity networks in Europe

Electric and plug-in hybrid vehicles (EV, PHEV) have the potential to contribute significantly to solving contemporary and future environmental and economic challenges of mobility. Different EU member states are currently addressing the subject in an isolated manner. The G4V consortium consisting of major European electric utilities and distinguished academic institutions are now adopting a holistic European approach to analyze the impact of a mass introduction in detail in order to optimize the grid infrastructure and make use of the inherent opportunities this represents for the operation of smart grids and energy efficiency. This paper will present a new probabilistic approach that was used to calculate the effects of electric vehicles on a large basis of European distribution grids. Simulation results will confirm the necessity of the chosen approach.

Impact of different electric vehicle charging strategies onto required distribution grid reinforcement

Electric and plug-In hybrid electric vehicles are expected to rapidly enter the market throughout the next decade and will become an important part of the intelligent energy supply of the future. This paper describes the key results of the Grid for Vehicles (G4V) project demonstrating a methodology to assess the grid impact of different EV charging strategies and what consequences have to be expected for distribution grids in five different European countries. It focuses on a methodology for automatic approximation of grid reinforcement costs and shows exemplary results regarding the expected need for reinforcement and related costs and gives recommendations for the design of future EV charging strategies.

Dynamic capacitor for HV applications

Dynamic capacitive VARs are becoming more important in the modern power system. This paper gives an examination of the behavior of a dynamic capacitor based on buck and boost cells. The principle of operation and the characteristics are explained. The basic principle is extended to the series connection of cells to reach higher voltages. A simulation case is provided to demonstrate the effectiveness of the concept. Design issues and principle of control are briefly discussed.

Approach and main results of the G4V project analyzing the impact of a mass introduction of electric vehicles on electricity networks in Europe

The Grid 4 Vehicles project (G4V) has analyzed the effects of a mass integration of electric and plug-in hybrid electric vehicles (EV and PHEV) into some distribution grids in Europe. A consortium consisting of six European research institutions and six European utilities has developed a methodology to investigate the effects of EV and PHEV in distribution grids and has proposed different options for intelligent and “grid-friendly” EV charging. This paper introduces the algorithms used for grid calculation, describes intelligent charging methodologies and demonstrates the most significant results of these calculations.

Determination of the potential to provide reactive power from distribution grids to the transmission grid using optimal power flow

This paper addresses the subject of determining the potential of distribution grids to provide reactive power to the transmission grid. A method based on optimal power flow is developed in order to determine the reactive power potential Day-Ahead taking meteorological data into account that decisively affects the contribution of distributed energy resources. The developed method is validated by simulations on the basis of a realistic low voltage grid with load measurements and meteorological (forecast and measurements) data. It can be summarized that the forecast of the reactive power potential that can be provided is of low quality due to forecast errors when the inverter of the of distributed energy resources is operated according to guidelines. By exploiting the theoretical potential of PVs inverter to a greater extent the reactive power potential is rather high and the forecast errors are less significant. The method enables for an improved predictability for transmission system operators with respect to reactive power balancing in the future and the results give first indications about the reactive power potential from the distribution grid for the transmission grid.

Modelling the charging probability of electric vehicles as a gaussian mixture model for a convolution based power flow analysis

This paper presents an approach for modelling the charging probability of electric vehicles as a Gaussian mixture model. The model is built up by assembling adapted multivariate normal probability density functions. This is done because the expectation maximization algorithm fails finding maximum likelihood estimates in respect of the charging power of the generated charging profiles. This Gaussian mixture model enables for capturing the charging profiles comprehensively with a few parameters and therefore it enables for calculating the charging probability dynamically for individual parameter intervals. The underlying assumptions about battery capacity, consumption, charging infrastructure, type of weekday and settlement structure determine the generation of the charging profiles. The proposed approach makes these parameters available for the density. Thereby, the provision of the charging profiles gets obsolete. This density can be used for a convolution based power flow analysis which offers benefits regarding the computational effort and random access memory usage compared to Monte Carlo-like simulations.