Simulating Electric Vehicle Diffusion and Charging Activities in France and Germany

Abstract

Plug-in electric vehicles (PEV) are considered to reduce oil dependency, noise, and local air pollution as well as greenhouse gas emissions caused by road transportation. Today, the early market penetration phase has started and can be observed in many countries. But how could the diffusion and adoption of PEV be modeled to create consistent scenarios? With which PEV driving and charging behavior can these scenarios be associated and what load-shifting potentials can be derived? This work provides an answer to these questions by describing a hybrid modeling approach of a PEV diffusion scenario consisting of a top-down macro-econometric Bass model, answering the question as to at what point in time how many PEV will be on the market, and a bottom-up micro-econometric binary logistic PEV adoption model answering who is likely to adopt. This set of methods is applied to representative mobility data sets available for France and Germany in order to simulate driving and charging behaviors of potential French and German PEV adopters. In addition, a sampling method is presented, which reduces computational times while intending to remain representative of the population of PEV adopters considered. This approach enables the consideration of PEV at a detailed level in an agent-based energy system model focusing on European day-ahead markets. Results show that PEV diffusion dynamics are slightly higher in France than in Germany. Furthermore, average plug-in times, average active charging periods, average load-shifting potentials, and average energy charged per PEV differ slightly between France and Germany. Computational times can be reduced by our approach, resulting in the ability to better integrate PEV diffusion, adoption, and representative charging demand in bottom-up energy system models that simulate European wholesale electricity markets.

Heuristic Optimization of Overloading Due to Electric Vehicles in a Low Voltage Grid

“…To study these two approaches further, well-developed studies, measuring the usage of EVs in a European context are used. These show differences in peak charging and discharging distribution over thousands of measured instances [12,13]. Several other charging strategies have been extensively discussed in the literature as well [14].…”

Modelling Electric Vehicle Charge Demand: Implementation for the Greek Power System

“…This case study proposed the rescheduling of EV charging in relation to residential loads so as to flatten the load curve and postpone the investment of network reinforcement. Ensslen et al [28] estimated the future aggregated EV load curves for France and Germany under scenarios of direct (uncontrolled) charging and time-shifted charging. Numerous charges are shifted from the evening hours into the night-time and noon hours due to lower day-ahead market prices in these hours.…”

“…One of them is an extended report about the British National Grid [20]. Several other pieces of research approached different EV charging issues or introduced certain novelties and occasionally ended up in a charging load curve, e.g., [7] for New Zealand, [28], France and Germany, [11], and Texas, but this estimation is obviously simplistic, and it is not the basic aim of the authors.…”

Simulating the Impacts of Uncontrolled Electric Vehicle Charging in Low Voltage Grids

“…Existing studies were used by previous researchers to create synthetic load profile modeling tools, to generate typical load profile behaviors for household electricity consumption [6][7][8]. A large number of countries are now adopting policies to cater to the effects of EV introduction and comprehensive reviews summarizing these studies are available in the literature [9,10]. Typically, these studies target the installation of charging stations at optimized locations or model the increased electricity demand at the medium or high voltage levels [10,11].…”

“…A large number of countries are now adopting policies to cater to the effects of EV introduction and comprehensive reviews summarizing these studies are available in the literature [9,10]. Typically, these studies target the installation of charging stations at optimized locations or model the increased electricity demand at the medium or high voltage levels [10,11]. On the distribution network, no correct answer exists due to a difference in the topologies of the networks.…”