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How Many Charging Stations for Electric-Cars Are Needed in Oslo by 2020?

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How Many Charging Stations for Electric-Cars Are Needed in Oslo by 2020? How many charging stations for Electric-cars are needed in Oslo by 2020? Vlorjan Badallaj Thesis submitted for the degree of Master in Informatics: Programming and Network 60 credits Department of Informatics Faculty of mathematics and natural sciences UNIVERSITY OF OSLO Spring 2019 How many charging stations for Electric-cars are needed in Oslo by 2020? Vlorjan Badallaj © 2019 Vlorjan Badallaj How many charging stations for Electric-cars are needed in Oslo by 2020? http://www.duo.uio.no/ Printed: Reprosentralen, University of Oslo Abstract In the recent years, Electric vehicle‘s has become more popular, and we see a stable increment when it was coming to switching over from fossil vehicle to either PHEV(Plug-in-hybrid) or pure Electric-vehicle(EV). In comparison to before, people see economic benefits of driving an EV instead of fossil, with green taxes as one of the primary reasons. Range and price are factors user looks for when buying their first EV, as uncertainty about if the EV has enough variety to drive people to work/home/shop and other purposes. The last couple of years, different vehicle vendors have started developing and building their own EVs and competes with each other about which one can offer and sell EVs with suitable ranges but also at an affordable price. There has seen an increase not only in the number of chargers added but also different types of chargers which provides a faster-charging speed (semi and superchargers). There are also environmental reasons behind ”forcing” people to change from fossil to EV. Several countries have made goals that within some several years, all EVs sold are going to be electric. Norway‘s realistic goal is that in the year 2025, all EVs sold are going to be pure electric. The Norwegian EV-policy has been quite successful the recent years, and the politicians have been praised for the effort and dedication in trying to create a pollution-free city. Different cities around the world are looking at Oslo as an example of how to improve their policy. The increase in both EVs and chargers will introduce new challenges, in terms of power consumption, distribution of new chargers, space-consumption, user-satisfaction, etc. To be able to reach the goal of a pollution free city with users changing to EV, it is essential to maintain high user-satisfaction. Parts of the thesis will cover different theories which are necessary to know the new challenges introduced by the high number of both chargers and EVs. This means that the current charging stations/points we have in Oslo will be studied, together with the EVs that are most popular in Norway. Performing different simulations and tests on these will help understand the optimal number of extra chargers needed in Oslo. Another major part of the thesis is used to study queueing and network models to analyze numbers of chargers and traffic pattern at different stations. Various research and papers have shown that there is possible to optimize the charging process for different EVs. Different topics, findings, and models will be presented during the thesis and will give proposals on solutions to implement new chargers with a focus on saving cost and space-consumption, which is critical. i ii Acknowledgements This thesis is not just a significant and essential part of my master degree but also a big part of my life, as it has given me a new perspective of the future. From start to finish, it has taken me more than 12 months of work to write the thesis. This part is about acknowledging the people who have helped and backed me through the journey, no matter which way they have done it. I want to start thanking my supervisors, Professor Yan Zhang, Professor Stein Gjessing and especially Professor Sabita Maharjan. They have been contributional in my education as well as personal development, and always been there if to answer questions if needed, helping me to reach different sets of goals. Together, they have made this topic quite interesting, and in the end, I am quite happy I chose this as my thesis. There were several ways I could do this thesis in terms of determining my direction and tools to use, but they have still given me a good recommendation of which tools I should use and paths I should go, which I am delighted for. The ones who also deserves a big thank you, are the staff who works at the research laboratory, Simula. This for giving me the possibility to work there for an extended period of the thesis. They have taken good care of me and supported me with important stuff when I needed it. The environment at Simula is excellent and are one of the primary reasons I have both enjoyed and managed to work with this thesis. I want to thank all my fellow students that I was lucky to get to know and be friends with during the master degree period at the University of Oslo. They have like my supervisors, taught me to do and think in different ways when it comes to finishing projects and tasks. They have also introduced and recommended me various tools and software which have been useful in terms of doing simulations and other things which again, have been necessary for my thesis. Lastly, I also want to thank you for having the backing of both family and friends outside the school. They have been patient with me, and even though they might not have the knowledge and idea about the area I was working in, they have still helped me with motivation and made me believe I could finish the thesis, which would have been quite difficult otherwise. They have taken time to read my thesis, and give me constructive feedback. I hope that the reader, regardless of how much foreknowledge he or she has about the topic, enjoys reading this thesis as this cover several essential themes and areas which also will be a big part of our future. iii iv Contents 1 Introduction 1 1.1 Challenges and Motivation . .3 1.2 Problem Statement . .5 1.3 Limitations and Scope of the thesis . .6 1.3.1 Collecting the data . .6 1.4 Methodology and research . .7 1.5 Related work . .8 1.6 Contribution . .8 1.7 Outline . .8 1.8 Summary . 10 2 General background 11 2.1 Evolution of Electric Vehicles in Norway . 11 2.2 Oslo - Current status and challenges . 13 2.2.1 Capacity Utilization . 14 2.2.2 Statisticial overview . 14 2.2.3 Current charging points and plans . 15 2.2.4 Intreview with Portvik, Sture . 17 2.3 Summary . 19 3 Technical background 21 3.1 Smart Grid- The future electricity grid . 21 3.1.1 Demand response management . 23 3.2 Electric vehicle charging . 23 3.2.1 Charging-point vs. Charging-station . 23 3.2.2 AC & DC charging . 24 3.2.3 Standard ”recipe” for placement of chargers . 25 3.2.4 Charging modes . 27 3.3 Battery Modeling/Characterization/Performance basic terms 29 3.3.1 Depth of Discharge(DoD) . 29 3.3.2 State of Charge(SoC) . 30 3.4 Summary . 31 4 Queueing concepts and theory 33 4.1 Introduction . 33 4.1.1 Queuing process characteristics . 34 4.1.2 Queuing performance . 37 v 4.2 Kendall‘S notation . 37 4.3 Multiserver queues (M/M/c) . 38 4.3.1 Choosing the number of servers . 39 4.4 Poisson process . 40 4.4.1 Poisson distribution . 40 4.4.2 Cumulative Distribution Function . 42 4.4.3 Exponential distribution . 45 4.5 DES of queueing systems . 45 4.6 Summary . 47 5 Network modeling and representation 49 5.1 Network optimization . 49 5.2 Map visualization with GraphTea . 50 5.2.1 Benefits of using Graphtea . 50 5.2.2 ”Type2 + Schuko” problem . 51 5.2.3 Hop in networking . 52 5.2.4 Distance matrixes . 52 5.3 Summary . 54 6 Driving-simulation program 55 6.1 Collection of charging-time in minutes for EVs . 63 6.2 Summary . 65 7 Charging-simulation program 67 7.1 EV attributes . 67 7.2 Charging-station / EVPSS attributes . 67 7.3 Dynamics . 70 7.4 Summary . 71 8 Numerical results and discussions 73 8.1 Results from Charging-simulation program . 73 8.1.1 Average queue length at stations . 73 8.1.2 Average total EVs at stations . 77 8.1.3 Rejected EVs . 80 8.1.4 Dejected EVs . 84 8.2 Summary . 87 9 Optimizing the implementation of new chargers 89 9.1 Reducing the number of rejected EVs & dejected EVs . 89 9.2 Deciding the new number of chargers . 91 9.2.1 Finding the ”net value” . 92 9.3 Detecting bottlenecks . 93 9.4 What optimization problem? . 95 9.5 Optimization solution 1 . 96 9.5.1 Changes in average queue length . 97 9.5.2 Changes in average total EVs at stations . 99 9.5.3 Reduction in Rejected EVs . 101 9.5.4 Advantages of optimization solution 1 . 103 vi 9.5.5 Disadvantages of optimization solution 1 . 104 9.6 Optimization solution 2 . 105 9.7 Discussion . 106 10 Tools used 107 11 Conclusion and future work 111 A Charging-simulation program(Main contribution) 121 B Driving-simulation program 123 C Predict number of EVs in Norway & Oslo 133 D Images from Elbilgrossisten 139 vii viii List of Figures 1.1 Linear regression and AI used to predict EVs by 2020 . .2 2.1 Traffic path from Oslo west and up towards Oslo north-east, approximately 22.2km .
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