Master's assignment
Student: Bart Nijenhuis
Supervisors: Marco Gerards and Johann Hurink
Programme: Sustainable Energy Technology - University of Twente
Finished: August 2020
The total sale numbers of Battery Electric Vehicles (BEV) and Plug-in Hybrid Electric Vehicle (PHEV) in the Netherlands is increasing, just as the amount of (semi-)public charging points and EV home chargers. Due to government policy it is likely that the total number of battery-powered cars will increase even faster in the near future. The latest Dutch government coalition agreement states that by 2030, all newly sold cars have to be ‘zero percent emission' cars. Looking at the current market, there is a high change that a (very) large share of these cars will be battery-electric: current fleet size forecasts range from anywhere between 1 million to 2.8 million battery-electric cars in The Netherlands by 2030. All these cars need to charge, which can put stress on local electricity grids resulting in possible black-outs. The possible implications of this (large) increase in battery powered vehicles in The Netherlands is the main background of this assignment. To what extent is the current network infrastructure fit to handle this increase in EVs? If not, what is necessary for a workable solution?
The basis of this research will, next to literature study on EVs, (smart) charging techniques, grid structures and other relevant information, consist of simulations made in DEMkit. These simulations are used to show different scenarios to study the effects (on power quality and power availability) of increasing (vehicle) electrification in existing grid infrastructure. These effects will differ locally from neighbourhood to neighbourhood depending on its grid structure, type of houses and residents, so the assignment has a technical basis and background combined with demography and user (charging) behaviour. Next to EV charging, other electrical appliances and technologies like heat pumps, PV, batteries and (possible) opportunities for vehicle-to-grid technologies are brought into the scenarios. Once certain maximum EV penetration grades (while applying uncontrolled EV charging) for different types of neighbourhoods are identified, existing smart grid control algorithms are introduced to see by what amount the maximum EV penetration grade can be increased using such technologies on different local situations.