Developing a location model for fast charging infrastructure in settlement areas and on the major highways
- Entwicklung eines Standortfindungsmodells für Schnellladeinfrastruktur in den Siedlungsräumen und auf den Fernverkehrsstraßen
Shirmohammadli, Abdolmatin; Vallée, Dirk Heinrich August (Thesis advisor); Oeser, Markus (Thesis advisor); Huber, Felix (Thesis advisor); Wegener, Michael (Thesis advisor)
Aachen (2017, 2018)
Dissertation / PhD Thesis
Dissertation, RWTH Aachen University, 2017
Electric vehicles, as a components of sustainable mobility development, cleans up the local air pollution, slashes CO2 emission through its efficient energy consumption and allows the growing renewable energies play even more significant role in reducing the fossil fuel dependency. Despite the excessive ecological advantages of electro mobility, its acceptance among people was not so promising due to several issues; beside high purchase price and limited range of EVs, one of the main reasons for low acceptance of EVs is the lack of public charging infrastructures. The usage of EVs is currently limited mainly to short-distance trips and the owners of EV are generally those who have the opportunity of charging their car privately at home or work places (Frenzel et al., 2015). For this reason, the provision of a comprehensive publicly accessible charging infrastructure is necessary for capturing new groups of EV-users. The technical properties of charging infrastructure are very different; however, the charging time is the essential characteristic. Whereas the conventional charging process takes several hours, the fast charging technology could load the battery of EVs within 30 till 60 minutes (depending on efficiency of charging stations and battery capacity) which provides a very good flexibility for the EV users in settlement areas also it gives the possibility of travelling the long inter-city trips. These types of charging infrastructure could be an intermediate solution for the limited range of EVs before it is technically solved. Regarding the high installation cost of these facilities, their location plays a very important role for their long-term functionality and profitability. The goal of this dissertation is to develop an area-covering and demand-oriented location model for Fast Charging Stations (FCSs) based on user’s activities and trip behaviours. The presented location model considers two main use-case scenarios for FCSs in settlement areas (inner-city) and on the major highways (inter-city). Based on these use-cases the location model has been divided into two sub-models of “settlement areas” and “major highways” accordingly. The usage of FCSs in settlement areas is supposed to increase the flexibility of users with their daily routine activities such as shopping and leisure activities, doing personal works etc. The “settlement areas” sub-model makes use of the activity time of EV-users in different facilities in order to charge the battery of EVs. Considering this assumption, analysing the interaction between people’s travel behaviour and urban facilities is the decisive factor in this sub-model. The main relevant criteria in this sub-model are capability of the urban facilities for attracting motorized individual traffic, activity time of users, catchment area of the facilities, land-use type of the area and spatial impact of already existing charging stations. In contrary, the inter-city travellers intend to travel their long journey in shortest possible time therefore, the daily activities such as shopping and personal works do not come into consideration in the “major highways” sub-model. If the distance between origin and destination cities is longer than the range of EVs, the travellers need for take an intermediate stop(s) for charging the battery, which could be also utilized for a small relaxation break during the trip. Considering this use-case scenario, the range of EVs plays an essential role for determining the optimal location in this sub-model. Other main relevant criteria are national and international traffic intensity on the highways, the role of the road segments for connecting the poorly accessible regions, the detour acceptance of travellers on the highways and charging behaviour regarding the state of charge by arrival to and departure from a charging station. The users of location model can assign their desired weights to the employed criteria in each sub-model and have their own individualised scenario-based results depending on the goals of their projects. The last part of the developed location model presents an algorithm for combining the calculated potential of locations in the sub-models. The potentials are combined because some locations can cover the demand for fast charging infrastructure in both settlement areas as well as on the major highways so their potential should be considered for both use-cases simultaneously. Combining the calculated potential of sub-models is performed by determining the weight of each sub-model, in which the assigned weights represent the priority of the corresponding use-cases for the specific project under study. The developed location model is implemented in the platform of Geographic Information System (ArcGIS) software. In order to analyse the geo-referenced layers and couple the different information spatially, this dissertation developed its own customised toolboxes in ArcGIS software by programming in Python. These toolboxes are developed in user-friendly and graphical interfaces which allow to non-programmer users also to utilize the developed location model easily. The location model has been implemented in the study area of Germany and several scenario-based results with different weights to the criteria have been presented in chapter 4. Although the pillar of this research is dedicated to fast charging infrastructure, the location model is developed in a way that is adaptable for determining the optimal location of other fuelling infrastructures such as Hydrogen or CNG (Compressed Natural Gas) as well. The deficits of the model are mainly related to the lack of user-study data which is understandable due to novelty of the topic of study. The last part of this dissertation suggests further research areas to those researches who aim to dedicate their work to this topic and contribute to widespread the electro-mobility as cleaner and more sustainable technology in transport sector.