An Economic Analysis of Electric Road System Technology an Electrification of Södertörn Crosslink

DEGREE PROJECT IN THE FIELD OF TECHNOLOGY VEHICLE ENGINEERING AND THE MAIN FIELD OF STUDY INDUSTRIAL MANAGEMENT, SECOND CYCLE, 30 CREDITS STOCKHOLM, SWEDEN 2020

An Economic Analysis of Electric Road System Technology An Electrification of Södertörn Crosslink

OSCAR NILSMO

ERIC WRANNE

KTH ROYAL INSTITUTE OF TECHNOLOGY SCHOOL OF INDUSTRIAL ENGINEERING AND MANAGEMENT DEGREE PROJECT IN THE FIELD OF TECHNOLOGY MECHANICAL ENGINEERING AND THE MAIN FIELD OF STUDY INDUSTRIAL MANAGEMENT, SECOND CYCLE, 30 CREDITS STOCKHOLM, SWEDEN 2020

An Economic Analysis of Electric Road System Technology An Electrification of Södertörn Crosslink

OSCAR NILSMO

ERIC WRANNE

KTH ROYAL INSTITUTE OF TECHNOLOGY SCHOOL OF INDUSTRIAL ENGINEERING AND MANAGEMENT

An Economic Analysis of Electric Road System Technology

An Electrification of Södertörn Crosslink

Oscar Nilsmo Eric Wranne

Master of Science Thesis TRITA-ITM-EX 2020:204 KTH Industrial Engineering and Management Industrial Management SE-100 44 STOCKHOLM

Ekonomisk analys av elvägssystemteknik

Elektrifiering av Tvärförbindelse Södertörn

Oscar Nilsmo Eric Wranne

Examensarbete TRITA-ITM-EX 2020:204 KTH Industriell teknik och management Industriell ekonomi och organisation SE-100 44 STOCKHOLM

Master of Science Thesis TRITA-ITM-EX 2020:204

An Economic Analysis of Electric Road System Technology An Electrification of Södertörn Crosslink

Oscar Nilsmo Eric Wranne

Approved Examiner Supervisor 2020-09-24 Bo Karlsson Lars Uppvall Commissioner Contact person SWECO Thomas Sjöström

Abstract The following paper is a master thesis written at KTH Royal Institute of Technology in Stockholm, Sweden. This master thesis is done in a collaboration with a Swedish Consulting Company SWECO. The main focus of this master thesis is to investigate if an implementation of Electric Road System (ERS) on Södertörn Crosslink is profitable, and if so, approximate the payback period for the investment. Additionally, the costs associated with the electrification of the bus fleet, currently operating on road 259, will be determined. There are three different ERS technologies, inductive (wireless), conductive overhead, and conductive rail have been compared, looking at advantages and disadvantages, with regard to the implementation of ERS on Södertörn Crosslink. To accompany this, case study methods have been used, where the results are based on interviews, theory and calculations. The result shows that the payback period for both inductive and conductive rail, based on this study’s forecast, is 7 years and 9,3 years respectively with regard to a discount factor of 9,0 percent. However, the conductive overhead solution does not seem to be profitable as this technology is limited to heavy trucks and buses capable of connecting to the overhead wires. The inductive ERS solution seems to be the best suitable option for Södertörn Crosslink, viewed from an economical and technological perspective. while also considering other factors such as aesthetics.

Key-words: Electric Road System, Electric Road Operator, Södertörn Crosslink, Profitability, Public Transport

Examensarbete TRITA-ITM-EX 2020:204

Ekonomisk analys av elvägssystemteknik

Elektrifiering av framtida Tvärförbindelse Södertörn

Oscar Nilsmo Eric Wranne

Godkänt Examinator Handledare 2020-09-24 Bo Karlsson Lars Uppvall Uppdragsgivare Kontaktperson SWECO Thomas Sjöström

Sammanfattning Denna rapport är ett examensarbete skrivet på KTH, Kungliga Tekniska Högskolan, i Stockholm, Sverige. Denna masteruppsats gjordes i samarbete med ett svenskt konsultföretag, SWECO. Det huvudsakliga syftet av denna masteruppsats är att ta reda på vilka möjligheter det finns för en elektrifiering av framtida motorvägen Tvärförbindelse Södertörn i södra Stockholm, Sverige. Syftet med masteruppsatsen är att undersöka om det finns lönsamhet i implementeringen av ett elvägssystem på Tvärförbindelse Södertörn och därefter approximera hur lång den eventuella återbetalningstiden skulle vara. Kostnader för en elektrifiering av bussflottan, som kör för närvarande på väg 259, ska också bestämmas. Tre olika tekniker för elvägssystem, induktiv (trådlös), konduktiv via luftledningar, och konduktiv via spår, jämförs med avseende på deras för och nackdelar, för att därefter kunna bestämma den mest lämpliga lösningen för Tvärförbindelse Södertörn. För att jämföra dessa tekniker har en fallstudie genomfört. Resultatet visade att återbetalningstiden för de induktiva och konduktiva (via spår) lösningarna, utifrån egen prognos, är 7 år respektive 9,3 år, med hänsyn till diskonteringsränta på 9,0 procent. Den konduktiva lösningen (via luftledningar) visade sig dock inte lönsam i och med att denna teknik är begränsad då endast högre fordon, lastbilar eller bussar, kan ansluta sig till luftledningen. Utifrån olika perspektiv, bland annat ekonomisk och tekniska mognad, visade det sig att den induktiv trådlösa elvägstekniska lösningarna kan vara bäst lämpade, utifrån ett lönsamhetsperspektiv, att implementeras på den framtida vägen, Tvärförbindelse Södertörn.

Nyckelord: Elvägssystem, Elvägsoperatör, Tvärförbindelse Södertörn, Lönsamhet, Kollektivtrafik

Acknowledgement We would like to begin by thanking SWECO for giving us the opportunity to do our master thesis with them, especially our supervisor Thomas Sjöström who shared valuable insights. We would also like to greatly thank our supervisor, at KTH Royal Institute of Technology, Lars Uppvall for helpful guidance. We also want to thank our seminar leader, Thomas Westin, and all the other master thesis students in our seminar group, for useful feedback.

Oscar Nilsmo and Eric Wranne Stockholm, Sweden, June 2020

Foreword We are originally from different engineering programs at KTH Royal Institute of Technology: Mechanical Engineering (Oscar Nilsmo) and Vehicle Engineering (Eric Wranne). We ended up in the same master’s program Industrial Management and we have chosen to do this master thesis together.

List of Content

1. Introduction 1 1.1 Background 1 1.2 Problem Statement 3 1.3 Purpose 3 1.4 Research Questions 3 1.5 Delimitations 4 1.6 Disposition 4

2. Research Context 6 2.1 ERS technology 6 2.1.1 Inductive Technology 7 2.1.2 Conductive Technology 8 2.1.2.1 Conductive Overhead 8 2.1.2.2 Conductive Rail 9 2.1.3 Summary 11 2.1.4 Costs Comparison 11 2.2 Electric Road Operator 12 2.3 Payment Model 13 2.4 Electric Buses 15 2.4.1 Depot Charging 16 2.4.2 Additional Charging 16 2.4.3 Charging while Driving (ERS) 17 2.5 BRT 17 2.5.1 Advantages and Disadvantages of the BRT System 18 2.6 Batteries 18 2.6.1 Life Expectancy 19

3. Literature Review on Economic Models Used for Calculating Electric Road Systems 20 3.1 Earlier studies 20 3.2 Investment and Calculation Theory 22

4. Methodology 24 4.1 Research Design 24 4.2 Research Process 24 4.3 Literature Review 25 4.4 Data Gathering 26 4.4.1 Primary and Secondary Sources 26 4.4.2 Data 27 4.4.3 Interviews 27 4.4.4 Assumptions 27 4.5 Data Analysis 28 4.6 Research Quality 29 4.6.1 Validity 29 4.6.2 Reliability 30 4.6.3 Generalizability 30 4.7 Research Ethics 30

5. Empirics 32 5.1 The Case 32 5.2 Road 259 32 5.3 Energy Consumption 33 5.4 The Bus Traffic on Road 259 34 5.4.1 Bus and Fuel Types 35 5.4.2 Bus Line 172 36

5.4.3 Bus Line 709 37 5.4.4 Bus Line 740 38 5.4.5 Bus Line 865 39 5.5 Costs 40 5.5.1 Bus and Maintenance Costs 40 5.5.2 Battery Costs 41 5.6 General Traffic on Road 259 42 5.7 Chapter Summary 42

6. Results 44 6.1 Calculations 44 6.1.1 Electric Road Operator Costs 44 6.1.1.1 ERS Costs 44 6.1.1.2 Charges, Incomes and Forecasts 45 6.1.1.3 Payback Period and Net Present Value 46 6.1.2 Battery Capacity Requirement 48 6.1.3 Bus and Component Transitioning Costs 49 6.1.3.1 Fuel Costs 49 6.1.3.2 Battery, Receiver & Buses Costs 49 6.1.3.3 Mechanical Arm Costs 50 6.1.3.4 Pantograph Costs 51 6.1.3.5 Lifetime Cost 51 6.2 Findings 51 6.2.1 Electric Road Operator 51 6.2.1.1 ERS Costs 51 6.2.1.2 Charges, Incomes and Forecasts 52 6.2.1.3 Payback Period 55 6.2.1.3.1 Comparisons 56 6.2.2 Battery Capacity Requirement 58 6.2.3 Bus and Component Transitioning Cost 61 6.2.3.1 Fuel Costs 61 6.2.3.2 Battery, Receiver & Bus Costs 62 6.2.3.3 Mechanical Arm Costs 63 6.2.3.4 Pantograph Costs 63 6.2.3.5 Lifetime Cost 64 6.2.4 Subsection Summary 65

7. Analysis & Discussion 67 7.1 Sensitivity Analysis 67 7.2 ERS Technology, Charges, Incomes and Payback Period 69 7.3 Battery Capacity Requirement 70 7.4 Energy Saving Potential and Vehicle Lifetime Costs 71

8. Conclusion 73 8.1 Answer to the Research Questions 73 8.2 Research Contribution 75 8.3 Limitations 76 8.4 Recommendations for Future Work 76

List of References 78

Appendix 89 Currencies 89 Payback Periods 89 Bus Lines 95

List of Figures

Figure 1. The Concept of Inductive ERS (Tongur, 2018) 7

Figure 2. The Concept of Conductive Overhead (Nashed, 2018) 9

Figure 3. The Concept of Conductive Rail (Bateman et al., 2018; Nashed, 2018) 10

Figure 4. The Payment Model (Hasselgren et al., 2018) 14

Figure 5. The Research Process 25

Figure 6. Tvärförbindelse Södertörn (Huddinge - Tvärförbindelse Södertörn, 2020) 33 Figure 7. Skarpnäck - Norsborg 37 Figure 8. Huddinge Station - Länna Handelsplats (Truckvägen) 38 Figure 9. Kungens Kurva - Huddinge Station 39

Figure 10. Handen - Skarpnäck 40

Figure 11. The Pricing Development (Goldie-Scot, 2019) 41

Figure 12. Payback Period for Inductive 55

Figure 13. Payback Period for Conductive Rail 56

Figure 14. Payback Period for Conductive Overhead 56

Figure 15. The Energy Consumption of Bus Line 172 58

Figure 16. The Energy Consumption of Bus Line 709 59

Figure 17. The Energy Consumption of Bus Line 740 59

Figure 18. The Energy Consumption of Bus Line 865 60

Figure 19. The Comparison between Fuel and Electric 62

Figure 20. Lifetime Cost 64

Figure 21. Cost Comparison between Fuel and Electric 64

Figure 22. Payback Period for Inductive 1 89

Figure 23. Payback Period for Inductive 2 90

Figure 24. Payback Period for Inductive 3 90

Figure 25. Payback Period for Inductive 4 91

Figure 26. Payback Period for Conductive Rail 1 91

Figure 27. Payback Period for Conductive Rail 2 92

Figure 28. Payback Period for Conductive Rail 3 92

Figure 29. Payback Period for Conductive Rail 4 93

Figure 30. Payback Period for Conductive Overhead 1 93

Figure 31. Payback Period for Conductive Overhead 2 94

Figure 32. Payback Period for Conductive Overhead 3 94

Figure 33. Payback Period for Conductive Overhead 4 95

List of Tables

Table 1. The Disposition of the Paper 5

Table 2. Comparisons through Advantages and Disadvantages 11

Table 3. Cost Comparisons (Jonsson, 2019) 12

Table 4. Actor Investment (Hasselgren et al., 2018) 15

Table 5. Pros and Cons of ERS Technologies when using Additional Charging 17

Table 6. Pros and Cons of Using Charging while Driving 17

Table 7. Interview Participants 27

Table 8. Comparison of Energy Consumption per km 34

Table 9. Standard Bus 35

Table 10. Bogie Bus 35

Table 11. Articulated Bus 36

Table 12. Bus Line 172 - Most Demanding Route 37

Table 13. Bus Line 709 - Most Demanding Route 38

Table 14. Bus Line 740 - Most Demanding Route 39

Table 15. Bus Line 865 - Most Demanding Route 40

Table 16. Historical Data of the Price for Lithium Batteries (Bateman et al., 2018) 41

Table 17. Forecasts of the Future Price for Lithium Batteries (Bateman et al., 2018) 41

Table 18. The Number of Vehicles in Sweden (Transportstyrelsen - Fordonsstatistik, 2020) 42

Table 19. Number of Electric Vehicles in Sweden (Elbilsstatistik, 2020) 42

Table 20. Implementing Costs 52 Table 21 Forecast in Sweden 2021-2030 52 Table 22. Forecast on Road 259 2018-2030 53

Table 23. Electric Vehicles and Trucks on road 259 53

Table 24. Annual Income 53

Table 25. Other Forecasts 54 Table 26. Income of Using Inductive 54 Table 27. Income of Using Conductive Rail 54

Table 28. Income of Using Conductive Overhead 55

Table 29. Comparisons with Forecasts (Inductive) 57

Table 30. Comparisons with Forecasts (Conductive Rail) 57

Table 31. Comparisons with Forecasts (Conductive Overhead) 57

Table 32. Battery Capacities and Number of Receivers 60 Table 33. Energy Consumptions and Costs 61 Table 34. Energy Consumption of Using Electric 61 Table 35. The Battery Costs 62 Table 36. The Receiver Costs 63 Table 37. The Total Cost 63 Table 38. Comparison between ERS technologies (Ezer & Tongur, 2020) 74

Table 39. Bus Line 172 - Details 96

Table 40. Bus Line 172 97

Table 41. Bus Line 709 - Details 98

Table 42. Bus Line 709 98

Table 43. Bus Line 740 - Details 99

Table 44. Bus Line 740 100

Table 45. Bus Line 865 - Details 101

Table 46. Bus Line 865 102

List of Abbreviations BRT - Bus Rapid Transit DOD - Depth of Discharge ERO - Electric Road Operator ERS - Electric Road System FAME - Fatty Acid Methyl Ester NPV - Net Present Value RME - Rapsmetylester SL - Storstockholms Lokaltrafik SOC - State of Charge

1. Introduction This chapter will provide background information to the research topic. Further, the problem formulation, purpose, the research questions, and the delimitations of the thesis will be presented. Additionally, the disposition is also presented in order to show the structure of the thesis.

1.1 Background The carbon dioxide emissions in Sweden were estimated to 51.8 million tonnes in the year 2018 whereas 31 percent of the total weight, i.e. 16 million tonnes, was due to emissions from the transport sector (Morfeldt, 2019). According to Naturvårdsverket (2017), road transportation accounts for 94 percent of the transport sector emissions, where passenger cars account for the largest contribution of 65 percent. The Swedish Government has set a target to become carbon neutral before year 2045. This means that carbon dioxide emissions have to be reduced by about 5-8 percent per year, during the period 2015-2045, in order to reach that target. (Morfeldt, 2019). This target would bring on major changes and technological shifts within the transport sector in order to manage the requirements related to zero net carbon dioxide emissions in the year 2045 (Nashed, 2018).

Electric Road System (ERS) is a technology that transfers the electrical power from roads to both standing-still and driving electric vehicles. Similar technologies have already existed and have been used by other vehicles, such as trams and trolleybuses. ERS technology has the potential to overcome environmental challenges and issues, such as the use of fossil fuels and air pollution. (Tongur, 2018).

The ERS technologies that are available today can be split into three different categories; inductive (wireless), conductive overhead and conductive rail (Bateman et al., 2018). The three methods provide comparable and unique advantages and disadvantages in terms of capacity, aesthetics and safety. The wireless solution of charging electric vehicles consists of coils, placed under the road at the center of the traffic lane, and a receiver located under the vehicle chassis. The power from the grid is converted to high-frequency AC power creating a magnetic field that generates current in the coil installed under the vehicle. (Electreon, 2020). The conductive solutions, conductive overhead and conductive rail, rely on direct contact between the power source and the vehicle. The overhead solution uses a pantograph, located on the top of the vehicle, which automatically extends to make contact with overhead wirelines. The rail solution uses electrified rails installed in or on the top of the road surface where the energy is transferred to the vehicle by using a mechanical arm, located under the vehicle chassis, that automatically extends to connect with the rail. (Hasselgren et al., 2018). Currently, there are several ongoing or completed ERS development projects in Sweden, such

as eRoadArlanda (conductive rail), Elväg E16 (conductive overhead) (Hasselgren et al., 2018), SmartRoad Gotland (inductive) (Electreon, 2020b).

A transition to an electrified transportation system will create new business opportunities whereas information regarding costs, payback time and risks will be essential to all actors involved in the transition. The transition to an electrified transportation system will also create a new actor: the electric road operator (ERO). The electric road operator will most likely work as an interconnecting link between road, electricity, vehicles and infrastructure, and be responsible for the costs and investment associated to the implementation and maintenance of ERS infrastructure. (Hasselgren et al., 2018).

Currently, ERS projects are mostly financed by the government due to high investment risks as a result of an unready market. However, a future “full scale development” of ERS will require private actor investments. (Hasselgren et al., 2018). In order to reduce risks, there must be an established market ready to use and pay for the use of ERS technology. Due to an initial small scale development, it is important to locate actors that consistently use the road which is about to be electrified and create business opportunities for both the user and the investor. (Pettersson et al., 2017).

Today, all public transport buses in Stockholm, used by Storstockholms Lokaltrafik (SL, a Region Stockholm owned company), are powered by renewable fuels, namely; HVO, RME, ethanol and biogas. However, within 10 years SL is aiming to replace 70 % of the existing bus fleet to instead be powered by electricity. Consequently, this will put pressure on bus companies currently running the public transportation in Stockholm. By introducing electric buses, Region Stockholm takes another step towards an emission free public transport and a major step for climate responsibility. In order to achieve the national climate targets set to 2030, a major share of the bus traffic needs to be replaced by buses powered by electricity. (SLL - Elbussar i kollektivtrafiken, 2020). Additionally, according to SLL and Trafikverket (2020), Stockholm is currently making investments in Bus Rapid Transits systems (BRT). BRT systems include dedicated lanes for buses, faster and more frequent operations, reduced operating costs and safer transportation. Thus, an implementation of the BRT system would provide a reliable alternative to private vehicles, in which could further reduce the environmental impact. (TransForm, 2020).

This master thesis is done in collaboration with the company SWECO that is involved in the project of autonomous and electric bus rapid transits (BRT) on Södertörn Crosslink, will replace current road 259, together with Trafikverket (Swedish Transport Administration), Keolis, Volvo, Scania and KTH Royal Institute of Technology. According to Trafikverket, road 259 is often exposed to heavy traffic and the accident rates are high (Trafikverket - Near You, 2020). Additionally, Södertörn municipality is not growing according to the regional development plan, issued by Region Stockholm. The availability of traveling within Södertörn, between the city centers of; Vårby Backe in Kungens Kurva, Flemingsberg and

Haninge centrum, is inadequate, consequently limiting the opportunities of growth in the region. Therefore, a new road, namely Södertörn Crosslink, will be built in order to link the Southern and Northern parts of the county together. This will create business opportunities, growth, and faster & safer transportation. (Trafikverket - Near You, 2020). However, before Södertörn Crosslink can be completed, the profitability of the investment for an electric road operator will need to be studied.

1.2 Problem Statement The implementation of Electric Road Systems (ERS) entails uncertainties connected to politics and financing. According to Pettersson et al. (2017), the Swedish Government will account for a maximum of 300 MSEK and not more than 50 % of the total costs related to ERS pilot project developments. Thus, in the future, a large scale implementation of ERS will require private actor participation and financing. (Hasselgren et al., 2018). According to Bateman et al. (2018) there is limited knowledge regarding; the comparative performance of ERS solutions, costs, and implementation.

1.3 Purpose This master thesis aims to investigate the costs associated with the implementation of ERS on Södertörn Crosslink. The three ERS solutions, namely: inductive, conductive overhead and conductive rail, are discussed and compared in order to provide the best suitable solution for Södertörn Crosslink, from an economical and technological perspective. Additionally, as an electric road operator will be responsible for the costs associated with implementing and maintaining ERS roads, the thesis aims to determine an approximation of the payback period for different ERS technologies. The BRT system will also be affected by the implementation of ERS and, therefore, the bus traffic may need to replace all current buses by electric buses. Therefore, the thesis also aims to study cost comparison between non-electric buses and electric buses.

1.4 Research Questions In order to fulfill the purpose of this master thesis, the two following research questions have to be answered:

RQ1: For the electric road operator, which ERS technology is most suitable for Södertörn Crosslink from an economical and technological perspective, considering other aspects, such as aesthetics, technical maturity and safety?

The first research question is supported by two scenarios, concerning the economic perspective, formulated as follows:

- Scenario 1: All bus traffic currently operating on road 259 is electrified.

- Scenario 2: All traffic (private cars, commercial trucks, and buses) currently operating on road 259 is electrified.

The idea of these two scenarios is to find out the profitability of the investment on Söderörn Crosslink. The first scenario is to find out if it would be sufficiently profitable by using the current bus traffic. The second one is to find out if it would also require a large traffic volume, including private vehicles and trucks, in order to increase the profitability of the investment. All three ERS technologies will be studied each in both scenarios. Payback and net present value (NPV) methods will be used in order to calculate profitability.

RQ2: Is it profitable in the long term for a bus operator to transition to an electrified bus fleet, assuming the use of ERS technology?

The idea of this research question is to study the cost comparison that was mentioned at the end of 1.3 Purpose. The cost comparison will be included by, for example, fuel, battery, receiver/pantograph/mechanical arm, bus, and maintenance costs.

1.5 Delimitations In this study, the electric road system is defined as a dynamic electricity transmission, in other words, the ability to charge vehicles while traveling. Further, this research report will only investigate the possibilities of using ERS technologies to support public and private transportation on Crosslink Södertörn, currently road 259, in Stockholm, Sweden. Therefore, other roads in Sweden will not be included in this research study. The research is focused on investigating actors assumed to consistently use the road. This, in order to provide a plausible timeframe for the payback period for the investment made by the electric road operator.

1.6 Disposition The structure of this master thesis is presented in Table 1. The first part of the study is an introduction, consisting of background, problem statement, purpose, research questions, and delimitations. The introduction is followed by a chapter on the research context, where includes a description of the Electric Road System, electric road operator, payment model, electric buses, Bus Rapid Transit, and batteries. This is followed by a literature review chapter, where earlier studies and investment & calculation theory are presented. Thereafter, the methodology of this thesis is presented describing the research process. This is followed by empirics that include a description of Södertörn Crosslink, energy consumption, bus traffic, and general traffic on road 259. Thereafter, the results, including calculations (payback, NPV & cost comparison) and findings, are presented. This is followed by an Analysis & Discussion, where results are analyzed and discussed. Finally, there is a

conclusion providing results, answers to the research questions, and suggestions for future researches.

Table 1. The Disposition of the Paper 1. Introduction

2. Research Context

3. Literature Review on Economic Models Used for Calculating Electric Road System

4. Methodology

5. Empirics

6. Results

7. Analysis & Discussion

8. Conclusion

2. Research Context This chapter is introduced by providing information regarding the electric road system (ERS technologies). Further, comparisons are made in order to increase understanding of ERS technologies' characteristics. Thereafter, information regarding the electric road operator (ERO) as well as a feasible payment model for ERS is presented. Finally, information regarding electric buses, BRT systems, and battery capacities are provided.

2.1 ERS technology The basic idea of ERS technology is to transfer electrical power from roads to driving electric vehicles. This requires electric vehicles to have an ERS powertrain in order to receive electrical power. (Tongur, 2018). A powertrain is a system that makes sure that the vehicle moves with the aid of different components, such as an electric engine and an energy transmission system (Stevens, 2016). Electric roads will not only apply to electric vehicles with ERS powertrain, but also for other vehicles using conventional fossil-fuels. However, in order for electric vehicles to drive on roads without ERS technology, an additional power source, such as a small battery or a small diesel engine will be required. (Tongur, 2018). According to Jelica et al. (2018), an implementation of ERS technology could reduce carbon dioxide emission, from the Swedish road transportation sector, by 19 percent per year while the transportation efficiency can increase from 33 percent to 77 (Jelica et al., 2018).

Radical innovations that have potential to address environmental or societal challenges, today, often receive public financing. Many of these innovations are initially developed in research and development activities in order to later be validated in pilot projects. However, many innovations fail to reach the commercial market due to high market uncertainty and the requirement of large capital investment, consequently, ending up in the “valley of death”. (Sundelin & Tongur, 2016). Dacey (2014) also mentions that a company has resources for the product but often lacks resources for commercialization and therefore ends in the “valley of death”. Bateman et al. (2018) mention that ERS technologies are currently in the testing and demonstration phases. In order to proceed a large-scale deployment, it has to manage four types of risks: technology risks, market risks, regulatory risks, and system risks. Technology risk concerns a technology’s capability of reaching efficiency improvements and expected performance levels. Market risk is connected to market demands and can be affected by political decisions consequently affecting the entire market. The system risks occur at changes in existing technology, i.e. discontinuous innovation, which can influence technological and institutional systems. (Sundelin & Tongur, 2016).

2.1.1 Inductive Technology The idea of dynamic inductive power transmission was developed by Hutin and Leblanc already in the late 19th century (Bateman et al., 2018). The idea was to provide propelled vehicles with power without any mechanical contact between receiver and powerline. However, it was not until the late 1990s, this technology was developed and applied to modern road transport. The first demonstration occured in New Zealand where a shuttle bus was successfully charged while standing still. During the last 8 years, research and development of inductive technology has significantly increased due to several factors such as; climate change, air quality, inconvenience of static charging, limitations in driving range, weight and size of vehicle batteries. (Bateman et al., 2018).

The inductive charging technology components can be divided into three categories; in-road, on-vehicle, and roadside. The in-road components consist of coils placed under the road (at the center of the traffic lane) and power cables providing electricity from the energy source. The on-vehicle components consist of secondary coils that are placed under the vehicle chassis, an electric engine (ERS powertrain) and battery. The roadside component consists of grid connections, power stations and transformers. (Sundelin & Tongur, 2016; Bateman et al., 2018; Tongur, 2018). To fully understand how the components are linked together, an illustration of ERS is provided in Figure 1.

Figure 1. The Concept of Inductive ERS (Tongur, 2018)

The implementation of inductive charging technology brings advantages and disadvantages. Firstly, there are barely any visual impacts since the technology is installed underneath the road. Secondly, the inductive solution is suitable for all vehicle types, such as private cars, trucks and buses. (Tongur, 2019; Hasselgren et al., 2018). Thirdly, it does not occur any friction between vehicles and road, i.e. no mechanical contact, reducing the need for road maintenance (Ezer & Tongur, 2020). Fourthly, the energy transfer efficiency is considered high (Tongur, 2019; Hasselgren et al., 2018). Finally, the wireless solution can be used in all

weather conditions (Singh, 2016). However, there are a few minor challenges regarding the inductive ERS-solution, such as technical maturity and power. The inductive technology has not been implemented beyond test and demonstration projects, consequently, the readiness of the technology is considered low. However, two pre-commercial demonstration projects, Smartroad Gotland and Tel Aviv, are currently in progress and will be tested during 2020. Additionally, wireless ERS is expected to move beyond demonstration phase in 2021. Regarding power transmission, the receiver, located under the vehicle chassi, has not reached its full potential. The receiver currently has a power energy transfer of 20 kW, however, this is expected to improve and reach 30 kW this upcoming year. (Ezer & Tongur, 2020)

2.1.2 Conductive Technology The conductive technology can be split into two categories: conductive overhead and conductive rail. Unlike inductive ERS, the conductive technical solutions require a contact to the road (presumably overhead or rail) in order to receive electricity. The conductive overhead solution is considered to be the most established technology since it has existed in more than 100 years. The first road transport, a trolley bus, with a conductive solution was introduced in Berlin by the company Siemens Elektromoto in 1882. (Bateman et al., 2018). These two conductive technologies (overhead and rail) are explained separately in the next two subsections.

2.1.2.1 Conductive Overhead The conductive overhead (or catenary) uses overhead lines when driving on electric roads. The development of overhead lines is far ahead of the other ERS solutions, considering technology readiness level. (Hasselgren et al., 2018). The energy is transferred to the vehicle by using a pantograph, installed on the top of the vehicle, that automatically extends to make contact with the overhead lines. The conductive charging technology components can be divided into two categories: on-vehicle and roadside. The first mentioned component, on-vehicle, consists of pantograph, control electronics, battery and electric engine. The roadside component consists of power transformers, masts that support power cables, rectifiers, switchgear at substations, communication system and controlled inverters. (Bateman et al., 2018). This technology is illustrated in Figure 2.

Figure 2. The Concept of Conductive Overhead (Nashed, 2018)

Nashed (2018) mentions that there are regulations in Sweden regarding high and low voltage wires, stated by the Swedish National Electricity Safety Board. The high voltage wires have to be at least 6 meter above the ground while the low voltage wires have to be at least 5,1 meter above the ground due to security reasons. Singh (2016) mentions that ERS vehicles has to be able to connect as well as disconnect to the overhead lines. When disconnecting from the overhead lines, vehicles should have secondary source, for example batteries or hybrid-diesel engine in order to continue driving on roads.

Conductive overhead is considered to have high maturity and capable of supporting heavy vehicle traffic due to high energy efficiency and power transmission. However, the overhead wires visually affect the surrounding environment. Further, conductive overhead requires continuous maintenance and the mechanical wear is high. (Ezer & Tongur, 2020). Additionally, the technology can not be used by normal (private) cars since the overhead wires are located 5.1-6 meter above the ground. (Hasselgren et al., 2018; Nashed, 2018). Implementing conductive overhead wires on bridges and in tunnels can be challenging (Bateman et al., 2018).

2.1.2.2 Conductive Rail The in-road rail solution has a similar function as the conductive overhead. The difference is that conductive rail has a direct contact to the power source underneath the vehicle. This technical solution requires three components: in-road, on-vehicle and roadside. The in-road component consists of power cables, rail and drainage systems. The on-vehicle component has a mechanical arm (or pantograph) as a pick-up unit, control electronics, electric motor and battery. The roadside component consists of, almost like conductive overhead,

transformers, communication system and grid connections. (Bateman et al., 2018). This technical solution is illustrated in Figure 3.

Figure 3. The Concept of Conductive Rail (Bateman et al., 2018; Nashed, 2018)

Hasselgren et al. (2018) discusses the advantages of using the conductive rail solution. One of the advantages is that this technology is suitable to all types of vehicles, compared to conductive overhead. Addiotionally, this technology does not have as much visual impact on road as the conductive overhead solution (Nashed, 2018). However, there are some disadvantages; this technology is somewhat newer and has not been tested as much as the other technical solutions, i.e. inductive and conductive overhead, friction between vehicles and road can generate particle generation and bad weather conditions can cause problems to the rails. It is still relatively unknown how well the technology can cope with different weather conditions. (Hasselgren et al., 2018). Further, conductive rail requires continuous maintenance and the mechanical wear is high (Ezer & Tongur, 2020). Bateman et al. (2018) mention that conductive rail creates a raised surface profile on roads, which is dangerous for motorcyclists.

2.1.3 Summary This subsection includes a short summary considering the advantages and disadvantages of the three ERS solutions discussed in subsection 2.1.1 and 2.1.2 [Tab. 2].

Table 2. Comparisons through Advantages and Disadvantages ERS Technology Advantages Disadvantages

Inductive - No visual impact - The readiness of the - Suitable to all types of technology is vehicles considered low. - Can be used at all - The receiver, located weather conditions - High efficiency under the vehicle chassi, - no need for road has not reached its full maintenance potential. - No mechanical wear (no friction) - Energy metering system

Conductive Overhead - High maturity - Requires maintenance - high energy efficiency - Mechanical wear is high and power transmission - Not suitable to private cars - Huge visual impact - Bridges and tunnels can be a challenge

Conductive Rail - Minimal visual impact - A few performed tests - Suitable to all types of and experiments vehicles - Weather’s impact - high energy efficiency - Friction and wear that and power transmission can generate particles - Dangerous for motorcyclists due to raised surface profile on roads - Requires high maintenance - Mechanical wear is high

2.1.4 Costs Comparison The cost of ERS implementation varies between the three technologies. However, something that all technologies have in common is that an electrical grid needs to be built alongside the road. The construction of an electricity grid costs about 4 000 000 - 8 000 000 SEK per km

(Jonsson, 2019). Regarding the construction of an electricity grid, it is likely that the grid owner is responsible for the cost. (Hasselgren et al., 2018). The following table [Tab. 3] presents the costs of implementing ERS technology for each of the three solutions.

Table 3. Cost Comparisons (Jonsson, 2019) ERS Technology Inductive Conductive Overhead Conductive Rail

Cost (MSEK per km) 10-35 9-14 5-10

Maintenance 0,150-0,525 0,135-0,210 0,075-0,150 (MSEK per km)

Jonsson (2019) mentions that inductive wireless solution costs 10-35 MSEK per km, both directions. However, according to interviewee 1 (2020), the price is closer to 10 MSEK per km (both directions). A receiver costs 15 000 SEK and the number of receivers for each vehicle varies depending on the size of vehicle (interviewee 1, 2020). According to interviewee 2 (2020), the construction of conductive rail, built by Elways, will cost about 6 000 000 SEK per km at a larger scale implementation, consequently, shorter distances is expected to be more costly. Singh (2016) also mentions the electrification at a larger scale of the conductive overhead can cost about 6 000 000 SEK per km. According to interviewee 3 (2020), the construction of conductive rail, built by ElonRoad, will cost about 5-6 MSEK per km (one direction). A full-scale implementation of ERS technologies would lead to lower prices due to economies of scale (Singh, 2016). The maintenance costs of ERS is about 1,5% of the initial investment cost per km and year [Tab. 3]. However, the costs for implementation of ERS technology can vary depending on surrounding conditions. (Jonsson, 2019). A pantograph, for conductive overhead technology, is estimated to cost 30 000 - 80 000 SEK (Singh, 2016). The mechanical (or pick-up) arm, used for conductive rail technology, costs about 10 000 - 15 000 SEK for private cars and around twice that price for buses and trucks (interviewee 2, 2020).

2.2 Electric Road Operator An electric road operator is an actor who is responsible for the electric roads. The electric road operator can be described as the interconnecting link between road, electricity, vehicles, and infrastructure. This through several business relationships with other actors within the electric road system. (Hasselgren et al., 2018). Gustavsson et al. (2015) mention that actors within electric road system can correspond to the infrastructure of telecom, where actors are allocated responsibilities, for example an actor is responsible for the electricity grid while the other actor is responsible for the sales of services. However, the role is not yet formally defined as the electric road system as well as the associated market is not developed and tested in its entirety. Nonetheless, Hasselgren et al. (2018) have found three categories

regarding the role of an electric road operator, namely:

1. To be responsible for taking part in the investment for the construction of the electric road infrastructure. 2. To be responsible for measuring customer energy consumption, debiting vehicles by providing an automated payment solution and identifying and collecting information to determine whether a vehicle has the right to use the electric road or not. 3. To be responsible for the operation and maintenance of the electric road.

According to Hasselgren et al. (2018), it is reasonable to assume that more than one actor will be identified as road operators since the responsibilities are different and therefore suitable for different kinds of actors. For instance, certain actors might be more suitable for having responsibilities connected to construction, operation, and maintenance of the electric road while others will have responsibilities connected to measurements, billing, and customer interactions. This paper will only focus on the first and third categories.

2.3 Payment Model Future electric roads will require a payment model in order to pay for the use of infrastructure and energy (Gustavsson et al., 2015; Nashed, 2018). There is currently no established payment model for ERS. Additionally, a future payment model for ERS will require participation of several actors, namely: Shipper (Swedish: Transportköpare), conveyor (Swedish: transportör), electric road operator, vehicle manufacturer, energy provider and grid owner. [Fig. 4]. Interactions and responsibilities between these different roles has to be taken into consideration. (Gustavsson et al., 2015). Hasselgren et al. (2018) has developed a possible payment model [Fig. 4] for the implementation of ERS. When designing an appropriate payment model for ERS, there are four components that has to be taken into consideration, namely, the cost for; road infrastructure, electric road system infrastructure, energy (electrical power and electrical grid) and vehicle & collector (receiver). The first-mentioned component, road infrastructure, is commonly financed by the state. Therefore, only the other three components mentioned needs to be included in a future payment model. The payment model is illustrated in Figure 4.

Figure 4. The Payment Model (Hasselgren et al., 2018)

The conveyor receives payments from the shipper, for example, for carrying goods from point A to point B. Similarly, the Swedish Traffic Administration (shipper), procuring all public transportation (SL) in Stockholm county, pays traffic contractors (conveyor) for passenger transport. In order to use the electric road, the conveyor needs to use a vehicle that is adapted to it. These vehicles are provided by the Vehicle Manufacturer. Further, the electric road operator receives payment from the conveyor, charging for electricity usage, grid fee and an additional user fee. In turn, the electric road operator pays the grid owner and the energy provider for the usage of the grid and for the electricity. (Hasselgren et al., 2018). As mentioned above, the electric road operator charge money for electricity usage, grid fee and user fee. The cost for electricity usage, including grid fee and taxes, is about 0,7-1,60 SEK per km, depending on specific energy consumption for the vehicle. The cost for electricity usage will be assumed to be 1,60 SEK per km for heavy truck traffic, i.e SL buses. The user fee is the cost for using the electric road. The idea behind the user fee is to cover the infrastructure investment costs made by the electric road operator. The user fee is assumed to be around 1 SEK per km. (Jonsson, 2019).

According to Hasselgren (2018), it is difficult to draw conclusions regarding how investments and risks will be divided between actors due to an unestablished market. However, four plausible business packages, on the development of ERS, are presented. The actor, responsible for measuring customer energy consumption by developing an automated payment solution, could either be provided by the electric road operator or by a new actor. However, it is reasonable to assume that the road operator will be responsible for infrastructure investments and maintenance while an additional actor has responsibility for the payment system. (Hasselgren, et al., 2018).

The following table [Tab. 4] provides information regarding how responsibilities and investment cost, most likely, will be divided between actors (Hasselgren et al., 2018).

Table 4. Actor Investments (Hasselgren et al., 2018) Actor Electric Road Grid Owner Vehicle New Actor Operator Manufacturer

Investment Electric road Grid Vehicle Payment system and infrastructure infrastructure Responsibility

Components Infrastructure for Grid and Vehicle adapted to - power transmission connection ERS, between road and points Receiver vehicle (inductive (transformer or conductive) stations)

2.4 Electric Buses Today, all buses used by SL are powered by renewable fuels. Through the introduction of electric buses, Region Stockholm takes another step towards an emission-free public transport and a major step for climate responsibility. To achieve the national climate targets set to 2030, a major share of the bus traffic needs to be replaced by buses powered by electricity. (SLL - Elbussar i kollektivtrafiken, 2020)

There are three different categories of electric buses; hybrid, plug-in hybrid, and fully electrical. Hybrid buses are mainly powered by a combustion system, in other words, generate mechanical power by combustion of a fuel. Additionally, an electric engine is installed to support the vehicle with electrical power. The battery used in a hybrid vehicle is charged through regenerative braking. (Törnqvist, 2019; SLL - Strategisk Utveckling, 2017). The battery in a plug-in hybrid is bigger than the battery used in a hybrid vehicle. The battery can externally be charged by using a wall outlet or a charging station. Therefore, plug-in hybrid vehicles can rely to be powered by electricity a further distance compared to the hybrid solution. Finally, a fully electric vehicle is solely powered by electricity. (Törnqvist, 2019).

The purchase cost of an electric bus is higher than a comparable conventional bus, however, many operating costs are estimated to be lower. Additional initial costs are charging infrastructure, vehicles, electricity supply, and training of mechanics and drivers. (Lundström et al., 2019). The variable costs are considerably lower due to two main reasons:

1. Reduced energy consumption 2. The electricity price (SEK/ KWh) is significantly lower than the price for biogas.

However, due to the high initial costs for vehicles and infrastructure, the total costs for implementing electric vehicles are usually higher than for conventional vehicles (SLL - Strategisk Utveckling, 2019a).

The ways of charging electric buses can roughly be divided into 3 categories; depot charging, additional charge, and charging while driving. Which technology that is favorable to choose depends on several factors, such as tediousness, bus line travel distance, passenger capacity, and need for flexibility. (Lundström et al., 2019). 2.4.1 Depot Charging Depot charging requires buses to be standing still in a depot for a longer period, usually during nighttime. Thus, this charging technique requires greater batteries to cover the vehicle’s energy needs while driving. By the use of depot charging, the bus can be used without any concerns regarding the transportation route, as it does not require any charging infrastructure to travel. Consequently, the route, in which the bus travels, can be very flexible. (Energimyndigheten, 2019). The batteries are charged on low effects, usually 40-80 kW. Depot charged buses usually have batteries with capacities up to 600 kWh enabling a driving range up to 150-200 km. (Törnqvist, 2019).

Advantages: - High flexibility, no need for implementation of charging infrastructure in traffic (Törnqvist, 2019). - Suitable for traffic with shorter driving range requirements (Törnqvist, 2019).

Disadvantages - Limited driving range. It requires the bus to charge during the day. Might lead to a need for extra vehicles. (Beekman & van den Hoed, 2016). - The location of the depot is of high importance since it may result in long “empty bus trips” to and from the depot to recharge (Törnqvist, 2019). - A depot is charging several vehicles at the same time which can put high demands on the electricity grid’s capacity and power outlets, as well as the maximum power outlet allowed in the depot (Lundström, A et al. 2019).

2.4.2 Additional Charging Additional charging is another charging technology that is implemented usually at bus stations, or end stations, along the bus line. Batteries in buses are adapted to high effects, up to 1 000 kW, in order to be charged fastly and be charged several times daily. It will be enough by using smaller batteries when using the additional charging technology. (Törnqvist, 2019). The effect can vary depending on which charging technology is chosen, presumably conductive or inductive technology. By using conductive technology, an additional charging

station can provide an effect of 300-600 kW. The inductive technology can provide an effect of 200 kW (SLL - Strategisk Utveckling, 2019a).

Törnqvist (2019) and SLL - Strategisk Utveckling (2019a) discusses the advantages and disadvantages of using additional charging in Table 5.

Table 5. Pros and Cons of using Additional Charging Advantages Disadvantages

- Smaller batteries - Higher maintenance - The ability to withstand costs due to charging high effects time - No need of extra buses - Visual impact in cities - Electric buses might have to be locked to any infrastructure due to small batteries

2.4.3 Charging while Driving (ERS) In motion charging requires lower effects, compared to an additional charging, an effect of 120 kW is said to be enough for a bus. At stand-stilled situations (static), a bus can need an effect of 90 kW. The low effects provide lower requirements for the electricity grid. (SLL - Strategisk Utveckling, 2019a). According to Törnqvist (2019), charging while driving is more suitable for the bus traffic that has a high frequency or has a high need for capacity. Unlike the two charging technologies (depot charging and additional charging), there are no needs of using huge battery capacities and it is enough by a battery capacity of 60 kW (applies to a 12m bus). The advantages and disadvantages of using motion charging are presented in Table 6. (SLL - Strategisk Utveckling, 2019a).

Table 6. Pros and Cons of Using Charging while Driving Advantages Disadvantages

- Stable technology - Visual impact - Lower battery capacity - Less flexible - Fewer losses

2.5 BRT Bus rapid transits (BRT) (Swedish: stombuss) are blue buses that frequent a core network (Swedish: stomnät) in a town (SLL & Trafikverket, 2020). The basic idea of BRT is to offer faster bus travels compared to common city buses. BRT buses also have a high frequency

(Swedish: turtäthet) and characteristics: trustworthiness, rapidity, and clearness. (SLL & Trafikverket, 2020; Bösch et al., 2013). However, BRT can be defined as buses with high-quality services and includes similar capacities as urban rail systems (Bergman, 2017). BRT is a faster system than conventional city buses. An adapted infrastructure and technical solution are needed to make this possible. It also means that BRT buses get priority over other traffic. The BRT system has similar advantages as trams but with lower costs as well as a shorter implementation process. (Bösch et al., 2013; Volvo Buses, 2020; WSP, 2011). If both the BRT system and the tram system had the same budget, the BRT system would be able to provide 60% longer distances compared to the tram system (WSP, 2011). Additional advantages of using BRT, BRT buses will be able to manage heavy traffic commuting (Scania - BRT, 2020).

According to Volvo Buses (2020), an increased number of BRT will bring on a reduced number of cars in cities. Thus, the air quality will be better and also the noise in cities will be decreased. Zhang (2010) mentions that the BRT System can also provide lower energy consumption.

2.5.1 Advantages and Disadvantages of the BRT System This subsection summarizes and presents what advantages and disadvantages of the BRT System. The previous subsections mentioned several advantages of the BRT system and the advantages include :

- Similar characteristics as the tram system - Lower implementation costs and shorter implementation process compared to the tram system - Providing a high frequency - The ability to manage heavy traffic community - The priority over other traffic - Reduced environmental impact

The BRT system includes more advantages than disadvantages. However, the disadvantages of the BRT system can be, for example, single bus lanes, where the BRT system can need extra space on roads. If a BRT bus is broken, it can cause traffic congestion to other BRT buses and it can provide limited opportunities for overtaking. (Zhang, 2010).

2.6 Batteries One of the biggest challenges that comes along with the implementation of electric buses is that batteries can store considerably less energy per unit weight compared to liquid fuels. (SLL - Strategisk Utveckling, 2018). Thus, this entails challenges for the transition from conventional fuels to batteries. The amount of energy a battery can provide, energy capacity, is usually expressed in kWh (SLL - Strategisk Utveckling, 2019a). Also, energy density,

usually expressed as kWh/kg, describes how much energy that is possible to store in relation to the battery’s weight. (Lantz & Aldenius, 2020).

The choice of battery för an electric vehicle varies depending on the circumstances in which the vehicle will operate. Electric buses adapted to slow charging in depots should for instance use a battery optimized for high energy storage capacity. On the other hand, electric buses using additional charging, and therefore have to be capable of recharging quickly, should be optimized too a high power transfer. In general, the better the battery is to recharge quickly the less energy storage capacity it has, vice versa. (SLL - Strategisk Utveckling, 2019c).

Further, to describe how fast the energy stored in the battery can be used, the parameter C-rate has to be defined. If a battery has c-rate 1, it means the battery can be discharged within an hour. However, if the battery has c-rate 5, this means the battery can be discharged within one-fifth of an hour.

State of charge (SOC) is the available capacity left in the battery in relation to the battery’s full capacity potential. Depth of discharge (DOD) is the percentage of the capacity that has been removed from the fully charged battery. (Spiers, 2012). In other words, if the SOC is 80 % the Dod is 20 %. SOC is defined as follows:

SOC(t) = cap(t) cap max

where cap(t) is the capacity left in the battery and cap max the full capacity potential. For instance, if the battery has a capacity potential ( cap max ) of 100 kWh and the battery has 80 kWh left, the SOC is 80 %. (Lantz & Aldenius, 2020).

2.6.1 Life Expectancy According to Energimyndigheten (2019) and Törnqvist (2019), the battery life expectancy is estimated to be 5 to 7 years and needs to be exchanged when the capacity is less than 80 percent of the initial capacity. The battery capacity reduces over time both due to calendar aging (affected by year of use and temperature) and cycling aging (occurring when the battery is charged or discharged). (Energimyndigheten, 2019). The battery life decreases if the battery is charged more than 80 % of its full capacity or discharged less than 20 %. Therefore, in order to maximize the battery life expectancy, the SOC span should be as small as possible. In other words, the SOC span should neither be more than 80 % nor less than 20 %. (Törnqvist, 2019).

3. Literature Review on Economic Models Used for Calculating Electric Road Systems This chapter presents the literature review of this master thesis. A review of earlier studies and investment & calculation theory are presented.

3.1 Earlier studies Hasselgren (2019) has provided a calculation model that can be used to assess the costs associated with the implementation of electric road system. The model is used to calculate the financial effect on actors assumed to be involved in such a system, namely: electric road operator, grid operator, vehicle manufacturer, the government, and the Swedish Transport Administration. The calculation consist of three stages:

1. Input data 2. Calculation 3. Results

The input data used in the model provided by Hasselgren (2019) consists of information regarding daily average traffic flows, annual vehicle kilometers on ERS, number of transactions per year, cost per payment transaction, truck premiums for the purchase of electric trucks, prices for fuels (electricity and diesel) etc.

The calculation section is divided into three categories: investment, costs, and revenues. Within these sections, actor responsibilities are divided. In other words, the amount of money invested and the percentage of money received from user fees are divided and distributed between involved actors. Finally, a summation of costs and incomes are calculated in order to receive the final results. (Hasselgren, 2019).

The calculation model, provided by Hasselgren (2019), is a tool that can be used by actors in order to create a greater understanding of the financial consequences of involvement in an electric road system. However, the model lacks certain aspects. For instance, the calculation model only provides revenues and results for a given year. In other words, there is no forecast made regarding the increase and development of ERS vehicles. Consequently, the model does not consider discounted cash flows into the calculation. Further, only heavy goods vehicles are considered as input data.

Nashed (2018) explores the possibilities of implementing ERS technology for passenger cars and the corresponding benefits for society. This is performed as a case study on road E6, reaching between Helsingborg and Malmö, in Southern Sweden. Road E6 is one of the

busiest roads in Sweden and is considered to be of high importance viewed from a national and international perspective. The studied route is 64 km in each direction whereas 50 percent of this distance is assumed to be electrified. Consequently, this would result in 32 km of ERS in each direction. (Nashed, 2018).

Nashed (2018) made a few assumptions and limitations in order to calculate the net present value (NPV) of the ERS investment. Input values, such as average annual daily traffic, driven annual distance, and vehicle energy consumption have been assumed to be constant. However, the share of electric vehicles is expected to grow according to a growth curve. Further, all electric vehicles suitable for ERS technology are assumed to fully utilize the electric road system. In this study, an overall cost analysis was done in order to determine the profitability of the ERS investment. The cost analysis compares savings and expenditures with regard to the cost of the technology, the cost of fuels, and the cost of emissions.

By using the assumptions presented above, the cost analysis showed that the net present value, using a discount factor of 3,50 percent and an economic lifespan of 20 years, would be 350 MSEK (Nashed, 2018).

Sundelin et al., (2017), provides a calculation model intended to provide a cost analysis for all actors involved in an electric road system. The cost components examined in the calculation model are costs for ERS implementation, Grid costs, additional cost for vehicle equipment, and costs for fuels (diesel and electricity). The focus has mainly been on the electrification of trucks over 3.5 tons. The study defines the meaning of closed and open systems. During the development phase of ERS technology, implementation of ERS will mostly be considered from a closed system perspective. An example of a closed system could for instance be a road that is consistently used by certain actors, for example, bus - or road freight transport companies. In an open system, ERS technology has been implemented on a larger scale where a large variety of transportation alternatives, adopted to the technology, is developed.

The study has made the following assumptions: ERS technology has a life expectancy of 40 years where the discount rate is set to 3.50 percent. Additionally, the annuity method has been used in order to determine if the investment will become profitable. Based on data received from earlier studies, three scenarios have been provided: a best-case scenario, a most reasonable scenario, and a worst-case scenario. The results show that closed systems require high traffic volumes in order to reach profitability. An implementation of ERS could, therefore, be profitable for certain roads depending on the average annual traffic volume. Further, the study provides information for a few specific roads in Sweden. This information consists of data regarding the average annual daily traffic requirement in order for an ERS implementation on these roads to become profitable. (Sundelin et al., 2017)

Another study, provided by Taljegard et al., (2020), investigates the possibilities of a full-scale ERS implementation in Sweden and Norway. The study identifies several roads in both Sweden and Norway considered having a good potential of being implemented by ERS technology. Additionally, the study examines how much of each road that has to be electrified as well as the vehicle types best suitable to be adopted to ERS technology. This, by determining traffic volumes, infrastructure investment costs, and the potential reduction of carbon dioxide emissions. This study took all European and National roads in both Sweden and Norway into consideration. The result showed that a high average daily traffic would provide a low cost of infrastructure investment. In other words, the average daily traffic is the most crucial factor for bringing down ERS infrastructure investment costs. (Taljegard et al., 2020).

The calculation model, provided by Hasselgren (2019), shows costs, revenues, and results for a given year. Future deployment and increase of ERS vehicles are not considered. Consequently, the model can not be used for determining business opportunities viewed from a long term perspective. Therefore, it may be argued that the model does not provide sufficient information in order for potential investors to make a well-founded decision. On the other hand, the study provided by Nashed (2018), examines future scenarios and ERS development. However, the cost-benefit analysis is used for weighing and comparing project costs and benefits in order to determine whether to go ahead with a project or not. This information can be used from a societal point of view but not by private investors.

Consequently, additional information and knowledge concerning business opportunities, viewed from a long term perspective, is required for actors involved in the transition to an electrified transport system. Additionally, since ERS technology is not commercialized, a close system deployment of ERS technology requires potential actors, consistently using the road, have to be identified. Consequently, a case study will be required in order to provide reliable results regarding payback periods and potential profits. This, by providing future scenarios of ERS vehicle deployment and by the use of calculation methods using NPV and discount factors.

3.2 Investment and Calculation Theory The Swedish Transport Administration has developed a socio-economic calculation model which is based on both current and future conditions. The calculation model consists of four steps: investigation & comparison alternatives, measure & value effects, net present value calculation and interpretation of results. The idea of this model is to make profitability assessments for any infrastructure investment. (Trafikverket, 2020c). Each step in this process is briefly described below:

- The first step is to define the phenomenon in which it is about to be investigated. Thereafter, a comparison alternative needs to be defined. Usually, the comparison

alternative is the scenario where no actions are taken, in other words, if business continues as usual. (Trafikverket, 2020c).

- The second step of this process is to study and calculate effects. The effects depend on the length of the calculation period. The calculation period starts at the traffic opening year and ends at a decided year. Regarding the economic life factor, the length of the calculation period usually is decided by the investment’s economic life. The economic life for investment can vary greatly depending on the type of investment. There are factors, such as price level & base year for monetary value and economic life, that should be taken into consideration. Regarding the price level & base year for monetary value, incomes and costs have to be valued as real terms in order to relate to the general price level at the base year. This means that all future incomes and expenditures have to be discounted to present value in order to be comparable. (Trafikverket, 2020c).

- The third step of this process is to determine the net present value by looking at future costs and incomes. When incomes and costs for each year are calculated, the net present value can be measured. The net present value is used in order to calculate the present value of future cash inflows and cash outflows. This, by using the discount factor. The Swedish Transport Administration recommends that the discount factor should be around 3,50 percent. (Trafikverket, 2020c; Trafikverket, 2020d). The equation of the net present value is presented in subsection 6.1.1.3.

- The fourth and final step of this process is the interpretation of results. The measurement of profitability is the net present value and if the net present value is positive, i.e. net present value > 0, the investment is considered profitable. (Nashed, 2018; Trafikverket, 2020c).

The calculation model, stated by the Swedish Transport Administration, has most partly been used in this master thesis. The first step will be used according to the instructions, where the phenomenon is Crosslink Södertörn. Regarding the second step, the start of the calculation period will be the year when Crosslink Södertörn is expected to be finished, i.e. year 2030. There is no decided end year in calculations due to limited information on the economic life of ERS. The third step will be used according to the instructions. However, the discount factor will be higher than the recommended 3,50 percent. Since the ERS investment will be handled by a private actor or several private actors, the discount factor should be between 6,0 and 12,0 percent according to Nashed (2018). Therefore, a discount factor of 9,0 percent (an assumption) will be used in this master thesis. The final step will be used according to the instructions stated by the Swedish Transport Administration.

4. Methodology This chapter presents the research design, research process as well as what kind of methods that have been used in order to collect and analyse data. Further, reliability, validity and ethics are discussed with the intention to describe how these have been taken into account in the research process.

4.1 Research Design The research design is a model of how to make a problem statement researchable. Choosing a suitable research design depends on what empirical material that will be collected in order to increase understanding of a certain phenomenon. The phenomenon can be described as something that needs to be understood, which corresponds to the purpose of the research. The research design of this master thesis is a case study. The case study is a way to deepen into a phenomenon, i.e. an in-depth inquiry. Conducting a case study requires gathering of extensive data, such as interviews, written documents, reports, emails and videos, and so on. (Saunders et al., 2012; Blomkvist & Hallin, 2015).

On behalf of SWECO, a Swedish Engineering Consultancy company, a phenomenon (an electrification of road 259 in Southern Stockholm, Sweden) was examined by analysing existing theories in the area of research. The case study in this master thesis is Södertörn Crosslink.

As said, the research design of this master thesis is a case study. This paper includes a literature review and empirical studies. The methods of this master thesis are qualitative interview study and quantitative data collection which is taken from secondary empirical sources. The quantitative calculations will be performed using secondary sources.

4.2 Research Process This research has been carried out on the behalf of a Swedish consultancy company, SWECO, in this study, referred as to the “case company”. This arrangement between the researchers and the case company was initiated by a representative at KTH, Royal Institute of Technology, namely the supervisor of this project. The area of research was limited to the interest of the company. The case company provided a project description in which had been broken down into several sub-projects for which this study has focused on one of these sub-projects. In order to create a more straightforward research direction, several meetings were held with the case company, involving discussions about the description of the sub- project.

The research process was introduced by reviewing existing literature and earlier studies within the research area. This in order to gain a broader understanding of electric road systems and its challenges and uncertainties. Thereafter, a research question was developed and formulated based on the project description and knowledge gained from existing theory. The research was investigated based on two viable scenarios. Further, the next step in the research process was empirics. In this section numerical data was collected, analysed and used as input data in different calculations in order to calculate and provide results. Finally, the findings gathered from empirics and theory were used to answer the research question. Initially, the research started out as a qualitative study, however, as the project proceeded, additional information from theory and empirics as well as feedback from peers resulted in a reconsideration of the research design. As Blomkvist and Hallin (2015) mention, a research project is not a linear process. With this said, this research process has been iterative, where the content and structure of the report constantly has improved over time due to feedback from peers and supervisors. In the following Figure 5, the structure of the process is shown.

Figure 5. The Research Process

4.3 Literature Review As said, this master thesis focuses on a phenomenon, i.e. Södertörn Crosslink. According to Blomkvist & Hallin (2015), it can require a lot of readings since the phenomenon can be so complicated and this means that many fields can need to be read out. It is called “über

reading up” and this is a way to read as many literature as possible in order to find something relevant to this study (Blomkvist & Hallin, 2015).

The literature and theories in this master thesis were found by using search engines or databases such as Google, Google Scholar, KTH Primo and Digital Scientific Archive (Swedish: Digitala Vetenskapliga Arkivet). The literature was also collected by contacting concerned persons from, SWECO, the Swedish Transport Administration and the Administrative Authority in Stockholm (Region Stockholm). The most common search words in this study were, for example, “Electric Road Systems”, “Crosslink Södertörn” and “Bus Rapid Transit”. 4.4 Data Gathering The data gathering methods used in this research were chosen based on what was best believed to assist in answering the formulated research question. This research has mainly collected numerical data through email contact with the Administrative Authority in Stockholm, through telephone interviews and mail conversations with actors having an important connection to the investigated topic, and from earlier studies. By the use of quantitative data, this research has been able to provide new facts and insights to the investigated research area. The following subsection presents how the data was gathered and managed, including primary, secondary sources and data that were assumed to be able to answer the research question.

4.4.1 Primary and Secondary Sources This study is built upon both primary and secondary sources. Secondary sources were mainly used in the first steps of this research process and consisted of previous studies, articles and journals. The literature gathered was critically reviewed, compared and examined and provided relevant knowledge and concepts within the research area, such as; ERS technology, business models and BRT systems. Hence, the collected data was not only used to understand what current research already concluded, but also to find gaps in the literature in which could be further investigated. Consequently, comparing data from both literature and empirics eventually provided several findings in which this study could make its conclusions upon. Secondary sources were mainly collected from web pages, articles and journals that had not only been critically reviewed by the researchers of this paper, but also by others and therefore perceived as trustworthy. The empirical data collected from the Administrative Authority in Stockholm was also considered as secondary sources. These sources consisted of data particularly concerning four bus lines operating on road 259 in Southern Stockholm County. The collected data provided information regarding time tables, bus types, distances between stations, frequencies between departures etc. Regarding data on such as costs of ERS, and characteristics of the ERS technology solutions were found through interviews and this data was considered as primary sources.

4.4.2 Data This master thesis used a document gathering as a data gathering method. The document gathering-method is a way to collect data, such as mails and official documents, in order to establish empirical materials. (Blomkvist & Hallin, 2015). The data were, as said, collected through the Administrative Authority in Stockholm County, Sweden, from interviews and from earlier studies. Further, data concerning the number of non-electric and electric vehicles in Sweden were found through statistics compiled by the Swedish Transport Agency and Elbilsstatistik.

4.4.3 Interviews This subsection presents the interviewees involved in this study as well as how the interviews have been executed. Information gathered from interviews was used to validate the information obtained from earlier studies, e.g. advantages & disadvantages and costs, of each technical ERS solution. Mainly closed-ended questions were asked in which could be answered by a simple yes or now, or by providing a straight answer. For example, questions regarding efficiency, electricity transmission capacity and cost estimates were asked where simple and straight answers were obtained. The interviews were done by mails and telephone conservations during the master thesis-period (February - May) [Tab. 7].

Table 7. Interview Participants Interviewee Name Role/Company Interaction

Interviewee 1 Stefan Tongur Business Mail and Telephone Development Manager/Electreon Interviewee 2 Gunnar Asplund CEO and Telephone founder/Elways

Interviewee 3 Dan Zethraeus Innovation Mail manager/ElonRoad

The company Electreon develops the inductive solution while both Elways and ElonRoad develop the conductive (rail) solution.

4.4.4 Assumptions This subsection presents the assumptions used in this research study. The assumptions are presented in a bulleted list, with brief descriptions to mention why they were used:

- The Number of Electric Vehicles on Södertörn Crosslink The number of electric and non- electric vehicles will increase in Sweden. Several

scenarios from earlier studies provide information regarding the number of electric and non-electric vehicles in the future. The ratio between electric vehicles and non-electric vehicles in Sweden is assumed to apply to Södertörn Crosslink as well.

- Energy Consumption of Electric Buses and Non-Electric Buses The energy consumption is assumed to be constant, i.e. the energy consumption is assumed to only be dependent on the driven distance. However, in real life, the energy consumption varies. This was used to simplify calculations.

- Electric Road Operator The role of the electric road operator is not yet formally defined. However, in this paper, the electric road operator is assumed to be responsible for the implementation of ERS technology (category 1, see 2.2 Electric Road Operator) as well as the maintenance costs that come with it (category 3). The second category, i.e. the responsibility of measuring customer, debiting, identifying, and collecting information will not be part of this paper.

- Bogie Buses replaced by Articulated Buses Bogie buses (buses that are 14 m long) are assumed to be replaced by articulated buses (buses that are 18 m long ) due to population growth in Stockholm County. According to SLL - Verksamhet (2020), the population growth will be increased by 33 500 people annually in Stockholm county. Therefore, an increased need for public transport capacity.

- The Payback Period The number of electric vehicles was forecasted for 2030, the same year Södertörn Crosslink is estimated to be finished. The number of electric vehicles was assumed to be constant after 2030. This, to calculate the payback period from a worst-case scenario. The payback period includes a discount factor and according to Nashed (2018), the discount factor is 6-12 percent. Due to the large margin, a discount factor of 9 percent is used in this study.

- Maintenance Cost The maintenance cost of diesel buses is about 120 000 SEK per year (Misanovic et al., 2018). Buses with other propellant types should have the same components as diesel buses, since many parts are still the same e.g. engines and oil filters. Thus, maintenance cost is assumed to apply to buses with other types of propellants as well.

4.5 Data Analysis For this research, quantitative numerical data was gathered from interviews, primary resources and from earlier studies. In order to analyse the obtained data, mathematical models

were developed. These models were used with the aim to provide results in which could be analysed and compared to earlier studies. There are two types of quantitative data: discrete and continuous. Continuous data is the data that falls on a continuum and that can be measured. (Saunders et al., 2012; Zangre, 2019). Some examples of continuous data obtained in this study is time, energy consumption and distance. Discrete data is data that has distinguishable spaces between values. (Saunders et al., 2012; Zangre, 2019). Some examples of discrete data obtained in this study could be the number of buses, number of departures or the number of vehicles on road 259.

In order to get a good overview of the collected data, it was all organised into different tabs in the computer program Excel. By using Excel, results could easily be changed by adjusting the input data to the equations. Since telephone interviews and email conversations have mainly consisted of concrete and closed questions, there has been no need for coding the data. However, all data gathered from interviews has been compared and analysed by looking at results from earlier studies. This in order to achieve as reliable results as possible.

4.6 Research Quality The research quality has to be taken into consideration in order to avoid the possibility of incorrect content in the research paper (Saunders et al., 2012). Reducing the possibility of incorrect content can be done by increasing the research quality with the aid of validity and reliability. According to Blomqvist and Hallin (2015:52-53) validity and reliability can briefly be explained as “...validity entails studying the right thing while reliability entails studying it in the right way”. The validity and reliability are described in subsections separately.

4.6.1 Validity In order to increase validity, this study has sought to diminish misleading findings by always discussing and analyzing their relevance to the research. This, in order to ensure that the findings reflect the studied phenomenon. (Blomkvist & Hallin, 2015). Using more than one method to collect data, such as interviews, observations, and literature, adds validity to the study as it captures different dimensions of the same phenomenon. Further, by having feedback sessions with supervisors and other researchers, impartial and objective advices were given to the research, consequently affecting the validity positively. (Blomkvist & Hallin, 2015; Creswell, 2009; Eisenhardt, 1989; Yin, 2003). The literature was carefully chosen and critically reviewed by analyzing and evaluating many sources to the investigated topic. In order to create additional validity to the research, interviewees/numbers were chosen carefully to ensure they all had experience that could provide relevant information to the research study. (Eisenhardt, 1989). However, there are weaknesses of validity in this research study. The ERS technology is somewhat new concept and is mostly in the development phases. This can provide limited information about the exact cost and characteristics of each technical solution.

4.6.2 Reliability The research reliability is the degree to which a research may be repeated and still produce stable and consistent results (Research-Methodology, 2019). In other words, independent researchers should be able to replicate the process and arrive at the same results as the original study. (Blomkvist & Hallin, 2015). The collected data is assumed to have high reliability as it has been collected from different sources still providing same or similar results. Since all collected data has been systematically compared to each other, one may argue that the reliability is increased. However, some of the collected data, such as battery prices, fuel prices, bus prices etc, will most likely change in the future. Therefore, the reliability of the results will reduce over time. However, the input data in the Excel program can easily be changed. Therefore, the program developed will be reliable to use in future scenarios.

4.6.3 Generalizability Generalizability, or external validity, is to what extent the findings of the study can be used at other studies (Shantikumar, 2018). In other words, how well the theory will be able to apply to other settings (Gibbert et al., 2008). As said, a case study is chosen as the research approach for this master thesis. Blomkvist and Hallin (2015) and Gibbert et al. (2008) mention that one or more case studies cannot result in statistical generalizability since findings from a specific case many times cannot apply to other case studies even if they are of the same nature. However, this does not mean that case studies are devoid of generalization and should therefore be overlooked. The type of generalizability for a case study is analytical generalizability. The analytical generalizability means that the results, supported by the discussion section, can be applicable to other studies. (Blomkvist & Hallin, 2015). The findings in this master thesis only apply to the case study Södertörn Crosslink since the parameters only apply to this master thesis. However, the results of the master thesis can be applicable to other case studies when it comes to the profitability and the choice of ERS technology.

4.7 Research Ethics This master thesis follows the four principal requirements that were stated by the Swedish Research Council: the information requirement, the consent requirement, the confidentiality requirement, and the good use requirement (Blomqvist & Hallin, 2015; Vetenskapsrådet, 2020). These four requirements are described separately below and how each requirement was treated in the research approach.

The information requirement entails that the people you are studying must be informed about the purpose of the study. (Vetenskapsrådet, 2020). This was ensured by informing all the participants about the purpose of the interview as well as to what extent their information will be used.

The consent requirement is to let participants to determine themselves on their participation. It means that participants’ approval is required in order to obtain information. (Blomkvist & Hallin, 2015; Vetenskapsrådet, 2020). This was ensured by asking all participants for permission before using them in the study.

Further, there is the confidentiality requirement which entails that the material collected when conducting an investigation has to be treated confidentially. In other words, Participants’ private personal data will not be shared with non-involved people in the research approach. (Vetenskapsrådet, 2020). The participants in this study, as well as the company’s they are representing, have, if permission has been given, been presented by names. If nothing else is decided, participating companies have been presented in a way that does not make them identifiable.

Lastly, the good use requirement entails that the material you collect may only be used for the purpose that you have stated when collecting it. (Vetenskapsrådet, 2020). This has been ensured by not giving participants any misleading information or by keeping valuable information from them. No results from research have been manipulated to support a desired outcome for the study.

The idea of these four requirements is to minimize risks of leading to negative consequences (Vetenskapsrådet, 2020). Blomkvist and Hallin (2015) mentions that there are risks of using ethics. For example, the entire research content can reveal whether the ethics have been followed or not.

5. Empirics This chapter presents information on the case, Södertörn Crosslink which will replace the existing road 259, energy consumption, the bus traffic on road 259, costs, and also general traffic on road 259. This chapter is concluded with a short summary.

5.1 The Case Currently, several actors have decided to collaborate with the intention of investigating how future self-driving electric buses can be utilized for public transportation, in line with agenda 2045. This work is carried out as a case study for the Södertörn Crosslink where the project description has been divided into five sub-projects for which this study has focused on sub-project number four.

Sub-project number four aims to generate information regarding cost estimates for adjustments in the infrastructure on Södertörn Crosslink as well as to determine when the investment becomes profitable.

5.2 Road 259 Road 259 road has one of the highest rates of car accidents in Stockholm (Trafikverket - Near You, 2020). According to the Swedish Transport Administration’s statistics, an average of 17 027 vehicles are driving on road 259 every day in 2017. The new road, Södertörn Crosslink, reaches between Vårby Backe, E4/E20, and Jordbro, 73, Haninge County. The road will also be able to apply to cyclists and pedestrians, where a bike lane and walkway will be built separately in order to increase the safety. The new road will consist of several wildlife crossings, designed to make it easier for animals to move freely. (Trafikverket - Near You, 2020). The total length of Södertörn Crosslink will be 20 km, including a 5 km tunnel (Trafikverket, 2020b). Road 259 (Red line) and Södertörn Crosslink (black line) is illustrated in Figure 6 below.

Figure 6. Södertörn Crosslink (Huddinge - Tvärförbindelse Södertörn, 2020)

Figure 6 shows where Södertörn Crosslink (black line) will be built, replacing most parts of the existing road 259 (red line). The construction of the road will begin around 2022 with an estimated construction time of 8 years, in other words, Södertörn Crosslink will be finished in 2030. The new road will consist of two lanes in each direction with a speed limit of 80-100 km/h. (Huddinge - Tvärförbindelse Södertörn, 2020; Trafikverket, 2020b).

5.3 Energy Consumption The estimated energy consumption for an electric bus varies between existing studies. The energy use depends on many different parameters such as driver behavior, road quality, passenger load, topography and climate. Therefore, the energy consumption in Sweden will vary depending on season. Since electric buses do not provide any residual heat like conventional fossil powered engines do, additional heat is required to maintain a stable indoor temperature. Usually and most commonly, a diesel heater (using HVO or FAME fuels) is used for heating. Electric buses are mainly heated by diesel-powered auxiliary heaters since using electric heating significantly increases the energy output from the battery which can limit the range and availability of the bus under cold temperature conditions. (Energimyndigheten, 2019). However, air conditioning requires less energy output compared to heating and therefore the air conditioning system, it is usually powered by electricity from the battery. According to earlier studies made in Gothenburg, an outdoor temperature of 0 celsius degrees creates, on average, an additional energy need of 0,75 kWh/km. (Energimyndigheten, 2019). Consequently, this entails an average annual additional energy

consumption of 0,34 kWh/km. The additional energy need for heating varies between 0-50 % of the total operational energy requirement and around 10-27 % for air conditioning. The annual average energy requirement for cooling is estimated to be about one-tenth of the energy used for heating. (Energimyndigheten, 2019)

According to Vattenfall (2015), the energy consumption for a 12-meter electric bus is approximately 1.4 kWh/km. Similarly, Energimyndigheten (2019) assumes the average energy consumption for a 12-meter electric bus to be 1.4-1.6 kWh/km, including heating. Jobson (2015), provides a best and worst case scenario where the energy use of a 12-meter bus is estimated to be around 0.8 kWh/km to 2.82 kWh/km. Further Beekman and Van den Hoed (2016), assumes 2 kWh/km for a 12-meter electric bus and 3 kWh/km for an 18-meter electric bus. Andersson (2017) assumes the maximal energy use for a 12 meter electric bus to be 1,6 kWh/km and 2,3 kWh/km for a 18-meter long electric bus. Rogge et al. (2015) assumes 18-meter long electric buses to use on average 2,26-2,69 kWh/km inclusive air conditioning while Public Transport Administration (Swedish: Trafikförvaltningen), assumes the average energy consumption to be 1,9 kWh/km heating and AC included. The average of energy consumption in Huddinge-, Söderort- and Botkyrka county is 1,5 kWh per km when using electric buses according to SLL - Strategisk Utveckling (2019b). A comparison between electric bus types is shown in Table 8.

Table 8. Comparison of Energy Consumption per km Electric bus type Earlier studies

12 meter 0,8-1,6 kWh/km

18 meter 1,9-3,0 kWh/km

5.4 The Bus Traffic on Road 259 According to SL’s maps, there are several bus lines currently using road 259, namely: bus line 172, 709, 740 and 865. (SL - kartor, 2020). In the following subsection, details on each bus line are presented, including starting stations, end stations, number of departures, total distance, distance on road 259 and plausible percentage on ERS. The data is presented with the intention of later using it to calculate the annual energy saving potential, battery requirement for the bus lines and costs & payback period for the inductive technology. The data are found by looking at SL’s timetables (SL - Reseinfo, 2020), data from the Administrative Authority in Stockholm, SL’s maps and Google Maps. Note that the number of departures can be fewer during summer periods (SL - Reseinfo, 2020). As said, the bus lines are presented in tables and figures separately.

5.4.1 Bus and Fuel Types This subsection provides an overview of the different bus types and fuels that SL is currently using. However, the fuels marked with red are currently not at use on road 259 [Tab. 9, Tab. 10 & Tab. 11].

According to the Administrative Authority in Stockholm, there are three bus types operating on road 259, namely: Standard bus, Bogie bus and Articulated bus. These buses differ in length and weight, where articulated buses are the longest and heaviest. The bus types are presented in tables separately where each table presents fuel type, energy consumption per km and cost per energy consumption. Standard bus [Tab. 9] has a length of 12 m and a weight of 18 000-19 500 kg. Bogie bus [Tab. 10] has a length of 14,60-14,80 m and a weight of 23 150-24 600 kg. Articulated bus [Tab. 11] has a length of 18-18,70 m and a weight of 24 700-30 000 kg.

The energy consumption per km [Tab. 9, Tab. 10 & Tab. 11] are collected from SLL - Strategisk Utveckling (2019b) and this data only apply to Huddinge-, Söderort- and Botkyrka county. The cost of energy consumption, for each fuel type, is determined by looking at a table created by Circle K (Circle K, 2020). The red-marked in tables 9 and 11 means that buses do not use these fuel types.

Table 9. Standard Bus Bus index Fuel Energy consumption (kWh/km) Cost (SEK/kWh)

1 Natural Gas Vehicle 6,3 1,27

2 RME 3.5 1,20

3 Diesel (HVO100) 3,5 1,55

4 Etanol E85 4,1 1,76

Table 10. Bogie Bus Bus index Fuel Energy consumption (kWh/km) Cost (SEK/kWh)

5 Natural Gas Vehicle 6,9 1,27

6 RME 4,4-4,7 1,20

7 Diesel (HVO100) 4,4-4,7 1,55

8 Etanol E85 4,6 1,76

Table 11. Articulated Bus Bus index Fuel Energy consumption (kWh/km) Cost (SEK/kWh)

9 Natural Gas Vehicle 6,4 1,27

10 RME 4,7-5,2 1,20

11 Diesel (HVO100) 4,7-5,2 1,55

12 Etanol E85 5,5 1,76

The energy consumption per km for fuel type RME was not found in Strategisk Utveckling (2019b). However, according to Swea Energi (2016), the energy density of RME is approximately 4 % lower compared to diesel. Since the difference in energy density is small, RME is assumed to have the same energy consumption as diesel.

SLL - Strategisk Utveckling (2019b) mentions that the buses operating on line 172, 740, 709 and 865 are divided into two different classes (Class I and Class II), with differences in energy consumption. For example, for diesel buses, the energy consumption differs between 4,7 kWh/km and 5,2 kWh/km depending on which class the bus belongs to. However, regardless of fuel type and bus size, class I buses are estimated to have an average energy consumption of 5,0 kWh/km and class II buses have an average of 5,5 kWh/km (SLL - Strategisk Utveckling, 2019b). Since there is no available information regarding the number of class I respectively class II busses operating on road 259, the average energy consumption is assumed to be 5,25 kWh/km.

In the following subsections, each bus line is presented in details, including routes, distances (entire route and driven route on road 259).

5.4.2 Bus Line 172 Bus line 172 offers a route between Skarpnäck and Norsborg [Fig. 7]. The red-circled area [Fig. 7] represents the part of the route in which ERS infrastructure will be implemented. The total route distance between Norsborg and Skarpnäck is approximately 27 km.

Figure 7. Skarpnäck - Norsborg

The following table [Tab. 12] presents the most demanding route for line 172 (1b & 2b), namely, the route between Skarpnäck and Norsborg. The table shows how much time and distance that will be spent on ERS respectively on the conventional road (R). The intention of the data presented in the table below [Tab. 12], is to later use it to calculate the battery capacity requirement for bus line 172, see subsection 7.1.2.

Table 12. Bus Line 172 - Most Demanding Route

Road R ERS R ERS R

km 3.3 5.4 4 0.4 12

Time 12 min 11 min 7 min 2 min 28 min

5.4.3 Bus Line 709 Bus line 709 offers a route between Huddinge and Länna Handelsplats [Fig. 8] & [Tab. 13]. The red circled areas [Fig. 8] represent which parts of the route that will be implemented by ERS infrastructure. The total route distance between Huddinge and Länna is approximately 28 km.

Figure 8. Huddinge Station - Länna Handelsplats (Truckvägen)

The following table [Tab. 13] presents the most demanding route for line 709 (1a & 2a), between Huddinge Station and Länna. The table shows how much time and distance that will be spent on ERS respectively on the conventional road (R).

Table 13. Bus Line 709 - Most Demanding Route

Road R ERS R ERS R ERS R ERS R ERS R

km 0.41 0.71 1.32 3.7 1.0 0.2 4.6 3.35 6.6 1.1 4.5

Time 2 min 4 min 2 min 9 min 2 min - 7 min 6 min 10 min 2 min 5 min

5.4.4 Bus Line 740 Bus line 740 offers a route between Kungens kurva and Huddinge station. The red circled areas [Fig. 9] represent which parts of the route that will be implemented by ERS infrastructure. The total route distance between Huddinge and Länna is approximately 28 km.

Figure 9. Kungens Kurva - Huddinge Station

The following table [Tab. 14] presents the most demanding route for line 740 (1a & 2a), namely, the route between Huddinge and Lindvreten. The table shows how much time and distance that will be spent on ERS respectively on the conventional road (R)

Table 14. Bus Line 740 - Most Demanding Route

Road R ERS R ERS

km 7.8 4.2 3.6 1.4

Time 20 min 9 min 10 min 6 min

5.4.5 Bus Line 865 Bus line 865 offers a route between Handen and Skärholmen. The red circles [Fig. 10] represent which parts of the route will be implemented by ERS infrastructure. The total route distance between Handen and Skärholmen is approximately 32 km.

Figure 10. Handen - Skarpnäck

The following table [Tab. 15] presents the most demanding route for line 865 (1b & 2b), namely, the route between Huddinge Sjukhus and Söderbymalmsskolan. The table shows how much time and distance that will be spent on ERS respectively on the conventional road (R).

Table 15. Bus Line 865 - Most Demanding Route

Road V ERS V ERS V

km 6.0 4.2 4.0 15.7 2.2

Time 15 min 8 min 12 min 20 min 5 min

5.5 Costs This subsection presents investment costs for both electric and non-electric buses, maintenance costs and also battery costs.

5.5.1 Bus and Maintenance Costs A standard bus (12 meters) costs about 2,1-3 MSEK while an articulated bus (18 meters) costs about 2,9-4 MSEK (a double articulated bus costs 4,7-8,5 MSEK) (WSP, 2011; Bösch et al., 2013). Regarding electric buses, a 12-m electric bus would cost about 6,3 MSEK (Potkany et al., 2018; Sustainable Bus, 2020). The cost of an 18-m electric bus is 7,8 MSEK according to Törnqvist (2019).

The maintenance cost varies between electric bus and diesel. The maintenance cost of an electric bus is about 40 000 SEK per year while the maintenance cost of a diesel bus is about 120 000 SEK per year. The cost difference depends on what components of a diesel bus compared to the electric bus. A diesel bus needs components such as an internal combustion

engine, fuel tank, and gearbox while an electric bus does not any needs of these components. Therefore, the maintenance cost of an electric bus is cheaper. (Misanovic et al., 2018). The maintenance cost, for diesel buses, is assumed to apply to buses with other fuels, e.g. natural gas, as well.

5.5.2 Battery Costs The cost for batteries are expected to decrease during the following 10 years. The last 10 years, the price has dropped dramatically and this trend is expected to continue. Table 16 provides data from the recent years and Table 17 shows a forecast of the future price. (Bateman et al., 2018).

Table 16. Historical Data of the Price for Lithium Batteries (Bateman et al., 2018) Year 2010 2015 2018

SEK/kWh 9 840 3 444 2 334

Table 17. Forecasts of the Future Price for Lithium Batteries (Bateman et al., 2018) Forecast 2020 2025 2030

SEK/kWh 1 968 1 181 738

A similar study was conducted by Goldie-Scot (2019) where the expected price of an average battery pack is estimated to be around 930 SEK/kWh by 2024 and 615 SEK/kWh by 2030, see the pricing development in Figure 11.

Figure 11. The Pricing Development (Goldie-Scot, 2019)

The blue rhombuses represents observed prices for the period 2010-2018, while the black triangles represents a forecast of battery price for the period 2019-2030 [Fig. 11].

5.6 General Traffic on Road 259 There are many types of vehicles travelling on road 259 daily. According to the Swedish Transport Administration, 17 027 vehicles use the road every day, including 2 750 trucks, during 2017. This data is based on two traffic-flow-measurement-points along the road and thereafter divided by two in order to receive an average value. Historical data, concerning the increase of vehicles in Sweden, was gathered from Swedish Transport Agency (Fordonsstatistik, 2020). The data is presented in Table 18.

Table 18. The Number of Vehicles in Sweden (Transportstyrelsen - Fordonsstatistik, 2020) Year 2016 2017 2018 2019 2020

Vehicles 4 773 850 4 871 446 4 933 686 4 963 689 4 956 319

The data of electric vehicles in Sweden (Elbilsstatistik, 2020) is presented in Table 19, including the increase per year as well as the ratio between electric vehicles and vehicles.

Table 19. Number of Electric Vehicles in Sweden (Elbilsstatistik, 2020) Year 2016 2017 2018 2019 2020

Electric 15 751 27 914 45 395 68 804 102 209 Vehicles

Increasing - 77,22% 62,62% 51,57% 48,55%

Ratio 0,33% 0,57% 0,92% 1,39% 2,06%

Södertörn Crosslink is expected to be finished by 2030. The data provided in Tables 18 and 19 will be used to make forecasts for the period 2021-2030. The result will be compared to other forecasts already made. According to 2030-Sekretariatet (2020), the number of electric vehicles will be around 1 700 000 by 2030. However, Andersson & Kulin (2019), estimates the total number of electric vehicles to be 2 500 000 by 2030. Viklund (2020) provides a forecast assuming 950 000 to 1 500 000 electric vehicles in Sweden by 2030.

5.7 Chapter Summary The data gathered from empirics will be used in different calculations in order to obtain findings. The key takeaways from this chapter are presented below.

- Energy consumption per km will be used to make comparisons between the renewable fuels (in which SL is currently using) and electricity, in order to calculate the potential energy saving a transition to an electrified bus traffic could imply - Data concerning routes and distances on road 259 (buses) will be used to determine the battery capacity requirement for each bus line and for calculations of profitability on Södertörn Crosslink - The costs for buses and battery will be used for calculations of lifetime costs - Data on electric vehicles and trucks in Sweden will be used for calculations of profitability (payback periods) on Södertörn Crosslink

6. Results This chapter includes two parts: calculations and findings. The first part of this chapter shows which equations have been used in this master thesis. The second part presents findings by using the equations.

6.1 Calculations This subsection is the first part of the result chapter and presents equations used to determining; electric road operator costs, including ERS costs, charges, incomes, forecasts, and payback periods. Thereafter, calculations of battery requirement are presented. This subsection is concluded by showing the equations used to determine bus and component transitioning costs for bus companies.

6.1.1 Electric Road Operator Costs This subsection presents calculations used for determining the costs associated with the electric road operator. The forecasts are included in order to calculate total incomes and payback periods. Note that equations (7-11) only applies to scenario 2, where all traffic on Södertörn Crosslink would be electrified.

6.1.1.1 ERS Costs The following equation (1) describes the cost of implementing ERS infrastructure where

cERS is the cost per km (MSEK/km) and dERS is distance (km) on Södertörn Crosslink.

Again, this applies to the electric road operator. The cERS can vary depending on surrounding conditions when implementing the infrastructure. However, the average cost per km is assumed to be constant for each of the ERS solutions, see chapter 2.1.4. The cost of implementing ERS, C , is calculated according to the following equation (1): ERS

CERS = cERS × dERS (1)

The cost of roadside components such as, grid connections, power inverters, cooling units, transformers and communication systems is all represented in the variable C , where roadside c is the cost per km (MSEK/km). The cost for roadside components is assumed to be roadside constant for all ERS solutions and can be found under chapter 2.1.4. The roadside component costs are calculated according to the following equation (2):

Croadside = croadside × dERS (2)

The total investment cost IERS is calculated, based on the two previous equations (1) and (2), according to the equation (3):

IERS = CERS + Croadside (3)

6.1.1.2 Charges, Incomes and Forecasts The idea of this subsection is to find out the economical perspective for an electric road operator by looking at charges and incomes. There are two different charges regarding the use of electric roads: electricity charge and user fee. The electricity charge includes the use of both electrical power and the grid. (Hasselgren et al., 2018). The electricity cost per km

celectricity is approximated to be 0,7-1,6 SEK per km including tax. (Jonsson, 2019). The total electricity cost, Chargeelectricity , goes to the grid owner and to the energy provider:

Chargeelectricity = celectricity × dERS (4)

The user fee, cuse fee , is the cost per km of using the electric road and, dERS, total , is the total annual driven distance. The user fee only applies while driving on electric roads, not conventional roads. According to Jonsson (2019) the user fee varies between studies but is assumed to be around 1 SEK per km or more. The user fee, Chargeuse fee , is calculated according to the following equation (5):

Chargeuser fee = cuser fee × dERS, total (5)

The following equation presents the net income for an electric road operator. The annual maintenance cost is assumed to be 1,5 % of the total infrastructure investment cost, CERS , and is paid once a year (Jonsson, 2019). By using equation (6) the net income can be calculated according to the following equation:

IncomeERO = Chargeuser fee − 0, 015CERS (6)

The following equation (7) describes the annual increase of vehicles in Sweden. The input data is presented in subsection 5.5. n2016 represents the number of vehicles in Sweden during

2016 and n2020 represents the number of vehicles in Sweden during 2020. The ratio between the number of vehicles in 2020 and 2016 is raised by 1 divided by the number of years between in order to get the average annual increase, i :

n 1 i = ( 2020 ) ( 2020−2016 ) (7) n2016

In order to make a forecast for the number of vehicles in Sweden between 2020-2030, the average annual increase, i , is multiplied with vyear−1 . The variable vyear represents the number of vehicles in any year while vyear−1 is the number of vehicles the year before. The forecast is calculated by using the following equation (8):

vyear = i × vyear−1 (8)

The increase of traffic on road 259 has been assumed to have the same percentage growth as for the rest of the country. Therefore, equation (8) has also been applied to road 259, see subsection 6.5. However, note that equations (7) and (8) do not apply to the number of electric vehicles since the increase of electric vehicles in each year is faster. Thus, another equation (9) is needed in order to calculate the annual increase for electric vehicles, ielectric . This is calculated according to the equation (9):

i = eyear (9) electric eyear−1

The variable eyear represents the number of electric vehicles in any year and variable eyear−1 represents the number of electric vehicles the year before. The increase for electric vehicles is assumed to have an annual decrease of 3 percent between the years 2020-2030. This assumption is based on historical data, see subsection 5.5. The increase between 2018 and 2019 was 51,5 percent and the increase between 2019 and 2020 was 48,5 percent. Consequently, the percent increase was decreased by 3 percent in that year with regard to the S-curve. The forecast of electric vehicles for the period 2021-2030 is calculated according to equation (10):

e = e × (i − 0, 03) (10) year year−1 electric,year−1

The variable, e2030 , is the number of electric vehicles in Sweden 2030 based on equation

(10). v2030 is the number of vehicles in Sweden 2030 based on equation (8). The ratio between the number of electric vehicles and the number of vehicles in Sweden in 2030 is assumed to be applicable to road 259. Thus, the electric vehicles and trucks on road 259 in

2030, e259,2030 , can be calculated according to the equation (11):

e = v × e2030 (11) 259,2030 259,2030 v2030

The variable v259,2030 represents the number of vehicles on road 259 and is calculated according to the equation (8).

6.1.1.3 Payback Period and Net Present Value When the costs and incomes are given, the profitability can be calculated. There are two different ways to calculate the profitability: payback period and net present value. The aforementioned, the payback period, is a simple investment-calculation, where one calculates how long time it will take in order to get back ones investment (Engwall et al., 2014). The

payback period is calculated according to equation (Engwall et al., 2014; Infanullah, 2019) (12):

Initial Investment P ayback P eriod = Net Cash F low per P eriod (12)

Equation (12) only applies to even cash inflows, in other words, the amount of cash inflow has to be the same in each year in order to calculate the payback period (Irfanullah, 2019). This will be used in order to see payback periods without including the discount factor.

The net present value (NPV) is the difference between positive cash flows (profits) and negative cash flows (costs) during a period. (Berk & DeMarzo, 2014; Kenton, 2019). The net present value is achieved by calculating the difference between the present value for all future incomes and expenditures. If the net present value is positive, it means profitability. A higher NPV provides a higher profitability. (Engwall et al., 2014). However, if the net present value is negative, the investment or the project is not considered as profitable (Gallo, 2014). Gallo (2014) also mentions that the net present value can be a way to calculate the return on the investment. The present value (PV) of cash flow (13) is calculated according to Berk and DeMarzo (2014):

P V = C (13) (1+r)t

The variable C is cash flow, i.e. income, and the variable r is the interest rate or discount factor that is required when calculating cash flows within a determined time period. The third variable t is the number of years within a determined time period. (Berk & DeMarzo, 2014). To calculate the sum of all present values on a timeline (14), it is calculated according to Berk and DeMarzo (2014):

N C NP V (C ) = P V (C ) = ∑ t (14) t t (1+r)t t=0

Equation (14) has the same function as equation (13), the only difference is the summation N sign ∑ , which means that all present values are added together within a determined time t=0 period. (Berk & DeMarzo, 2014). Since the current value of money will decrease due to inflation, a discount factor is, therefore, taken into consideration in equations (13) and (14). For instance, today’s $1 will be lower than the future’s $1. The discount factor varies depending on how the company generates its funds. (Berk & DeMarzo, 2014; Gallo, 2014). The Swedish Transport Administration has a discount factor of 3,5 percent (Trafikverket, 2018; Trafikverket, 2020d). However, the investment of ERS implementation will be handled by private actors (Hasselgren et al., 2018). Nashed (2018) assumed, therefore, that the discount factor should be higher for private actors and the discount factor is set to 6-12

percent. Due to the large margin, the discount factor for private actors for Södertörn Crosslink is assumed to be 9,0 percent.

In order to calculate the payback period, Excel-program was used in order to determine the intersection point in which all future expenditures and all future incomes exceed the initial investment cost.

6.1.2 Battery Capacity Requirement In order to be able to assume that the bus traffic using Södertörn Crosslink will generate incomes, the technology has to be tested in order to evaluate if the ERS installed on Södertörn Crosslink will be sufficient in order to support the 4 bus lines, i.e. 172, 709, 740 and 865. In this calculation model, the specific energy consumption (kWh/km) is assumed to be constant and only dependent on the driven distance. Therefore, an average value for the energy consumption is assumed based on information from earlier studies. Further, heating is assumed to be powered by an additional diesel (HVO) heater. Therefore, electricity from the battery is assumed to only be used for running the bus. Further, in order to maximize the life expectancy of the battery, the SOC span is set to 20-80 %. Consequently, the bus will only have access to 60 % of the total battery capacity. The battery capacity for line; 172, 709, 740 and 865, is chosen with respect to the most demanding route. Additionally, the bus should be able to travel back and forth on the route solely relying on energy received from ERS.

The following equation (15), is a linear equation that describes the energy received and consumed while driving on ERS and on the conventional road. Ediff is the amount of energy received and consumed while driving the route, t is the time in minutes spent on ERS, W is the total energy efficiency, in kW, from the receivers placed under the vehicle chassi, Euse is the energy use per km (kWh/km) and finally, dbus line is the driven distance. The data gathered from the Administrative Authority in Stockholm, see appendix, providing distances, bus types, is used as input data into the following equation (15):

E = t × W − E × d (15) diff 60 use bus line

The number of receivers required has been determined with the aim of reducing the difference between the highest value of energy received ( ymax ) and the lowest value of energy consumed ( ymin ) in order to maximally reduce the size of the battery ( EB, cap ). The battery capacity requirement (16) for each bus line is calculated by taking the difference between the highest value of energy received and the lowest value of energy consumed and dividing this value with 60 to get kWh/ % in the SOC 20-80%. Finally, this value is multiplied by 100 to get the full battery capacity requirement. The obtained value is the minimum battery capacity required in order to travel back and forth on the route solely relying on energy received from ERS.

(ymax−ymin) EB, cap = 60 × 100 (16)

6.1.3 Bus and Component Transitioning Costs This subsection presents calculations used for determining the transitioning costs associated with the bus entrepreneur.

6.1.3.1 Fuel Costs The following equation describes the total annual energy consumption cost for all buses operating on road 259, where the data gathered from empirics, see appendix, is used as input data. In the following equation (17), dbus line represents the daily driven distance (km),

efuel type represents the energy consumption per km (kWh/km), cfuel type represents the cost for the specific fuel type, and finally, Efuel, cost is the total annual energy consumption (kWh).

For example, Bus ID 107071 drives a distance of 483 km per day, dBus Line , using natural gas as fuel with an average energy consumption of 6,4 kWh/km [Tab. 9], efuel type , with a fuel cost of 1,27 SEK/kWh [Tab. 9], cfuel type , 365 times a year. Further, the total annual energy consumption cost, E , is calculated by adding together all the partial sums, in other fuel, cost words, the total annual energy consumption cost for each bus. Equation (17) can also calculate the annual energy consumption, Efuel , by deleting the fuel cost cfuel type .

Efuel, cost = ∑ (dBus Line × efuel type × cfuel type × 365) (17)

The energy consumption (kWh/km), cfuel type , for electric buses can be seen in subsection 6.3. By using equation (17), the annual energy electricity consumption cost can be calculated for electric buses as well. The energy consumption of both fuel and electricity can be compared by looking at the energy saving potential (SLL - Strategisk Utveckling, 2019b) and this is calculated according to equation (18):

E −E E(%) = fuel electric (18) Efuel

6.1.3.2 Battery, Receiver & Buses Costs As mentioned in the subsection 6.4.3, the current battery cost for a lithium battery is around 1 968 SEK per kWh. However, the battery price is expected to decrease and by 2030 to be below 738 SEK per kWh. (Bateman et al., 2018). The battery cost Cbattery is calculated according to equation (19):

Cbattery = EB,cap × cenergy (19)

where the variable EB,cap is the size of the battery capacity, see subsection 7.1.2 and equation

(16), and cenergy is the cost per kWh (SEK/kWh).

The following equation (20) describes the total cost all receivers, Creceiver . The price for one receiver, creceiver , is approximately 15 000 SEK (interviewee 1, 2020). The number of receivers required, nreceiver , for each bus line is dependent on different factors, see subsection

7.2. The cost Creceiver is calculated according to equation (20):

Creceiver = creceiver × nreceiver (20)

The total costs, C total , is calculated by summing the battery costs and the receiver costs times the amount of buses, n vehicle , and finally by adding to total costs for all new buses,

C buses . The total cost, Ctotal, inductive , is calculated, together with equations (19) & (20):

C total, inductive = ∑ C battery + C receiver + C buses (21)

The variable Cbuses is the total cost for all buses and is calculated according to equation (22) where, n12m , is the number of 12 meter long electric buses and n18m is the number of 18 meter long buses required :

Cbuses = c12m × n12m + c18m × n18m (22)

To exchange the current bus fleet, 11 normal buses, n12m , and 35 articulated buses, n18m , will be required. Additional input data to equation (22) can be found in subsection 6.4.1. The total cost of buses also applies to subsections 7.1.3.3, 7.1.3.4 and 7.1.3.5. This equation (22) also applies to non-electric buses, where costs are 2,1-3 MSEK and 2,9-4 MSEK for standard buses (12 meters) and articulated buses (18 meters) respectively (WSP, 2011; Bösch et al., 2013).

6.1.3.3 Mechanical Arm Costs The mechanical arm costs around 10 000-15 000 SEK for private cars and 20 000 - 30 000

SEK for buses and trucks (interviewee 2, 2020). The total cost, Ctotal, rail , including the cost of mechanical arm and the number of buses and the total cost of all buses Cbuses , is calculated according to equation (23):

Ctotal, rail = Cmechanical arm × nvehicle + Cbuses (23)

6.1.3.4 Pantograph Costs According to Singh (2016), a pantograph costs 30 000-80 000 SEK. The total cost, including the number of buses and the total cost of all buses Cbuses , is calculated according to the equation (24):

Ctotal = Cpantograph × nvehicle + Cbuses (24)

6.1.3.5 Lifetime Cost The lifetime cost will be compared between electric buses and non-electric buses in order to find out the cost difference in the long term. The lifetime cost Clifetime , with regard to the number of years, is calculated according to (25):

Clifetime = Cbuses + years × (cmaintenance × nbuses + Efuel,cost) (25)

The variable cmaintenance represents the maintenance cost. The maintenance cost of an electric bus is about 40 000 SEK per year while the maintenance cost of non-electric bus is 120 000

SEK per year (Misanovic et al., 2018). nbuses , represents the number of buses. This equation applies to both electric and non-electric buses.

6.2 Findings This subsection presents the findings regarding electric road operator, battery capacity requirement and transitioning costs for bus companies. The equations presented in the previous subsection, 6.1, were used.

6.2.1 Electric Road Operator This subsection presents what costs, charges, incomes, and forecasts are associated with the Electric Road Operator, considering the two scenarios. The idea is to find out the payback period for each ERS technology in order to see the profitability of the investment.

6.2.1.1 ERS Costs This subsection presents the costs of implementing ERS on Södertörn Crosslink where a cost comparison between the three ERS technologies: inductive, conductive overhead and conductive rail is provided. Södertörn Crosslink is 20 km long where the grid infrastructure investment is about 8 MSEK per km (Jonsson, 2019). Thus, the total cost of the electricity grid will be 160 MSEK.

The cost of implementing ERS (see Table 3 in subsection 2.1.4) varies between the different ERS technologies. The total implementation costs for each technical solution (the entire route, i.e. 20 km back and forth) are shown in Table 20. Table 20 also presents the total

investment cost if including the cost of the electricity grid. These costs apply to both scenario 1 and scenario 2.

Table 20. Implementing Costs Technology Cost (SEK) Total Cost (SEK)

Inductive 200 000 000 360 000 000

Conductive Overhead 280 000 000 440 000 000

Conductive Rail 240 000 000 400 000 000

6.2.1.2 Charges, Incomes and Forecasts Regarding scenario 1, the electric road operators can earn 1 080 270 SEK annually by using an user fee of 1,00 SEK per km. It means that the public transport needs to pay around 2 808 702 SEK per year, if including an electricity charge of 1,60 SEK/km (Jonsson, 2019), when using electric roads on Södertörn Crosslink for the four bus lines.

As said, electric road operators can earn 1 080 270 SEK annually if only using electric buses on Södertörn Crosslink. The annual maintenance cost will be around 3 000 000 SEK - 4 200 000 SEK for the entire ERS-route, see subsection 2.1.4, depending on which ERS technology that will be chosen. Consequently, it will not be profitable only using electric buses as this will result in annual losses, regardless of chosen ERS technology.

Regarding scenario 2, in order to calculate incomes based on general traffic, the number of electric vehicles firstly has to be calculated. Table 21 presents a forecast of the number of vehicles, including electric vehicles (and increase in each year) as well as the ratio between them, in Sweden 2021-2030. The estimated increase per year for the number of vehicles is about 0,96%. The forecast of electric vehicles in Sweden is based on the equation (10), see subsection 6.1.1.2.

Table 21. Forecast in Sweden 2021-2030

Year 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030

Vehicles 5 006 801 5 054 738 5 103 134 5 151 994 5 201 321 5 251 120 5 301 396 5 352 154 5 403 397 5 455 132

Electric 148 766 212 068 295 942 404 112 539 696 704 578 898 696 1 119 334 1 360 561 1 612 958 Vehicles

Increase 45,55% 42,55% 39,55% 36,55% 33,55% 30,55% 27,55% 24,55% 21,55% 18,55%

Ratio 2,97% 4,20% 5,80% 7,84% 10,38% 13,42% 16,95% 20,91% 25,18% 29,58%

The following table [Tab. 22] presents a forecast of the number of vehicles and trucks, travelling on road 259, in the period 2018-2030. The estimated annual increase of vehicles in

Sweden, 0,96 %, is assumed to apply to road 259 as well, see equation (9) in subsection 6.1.1.2.

Table 22. Forecast on Road 259 2018-2030

Year 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030

Vehicles 17 190 17 355 17 521 17 689 17 858 18 029 18 201 18 378 18 552 18 729 18 909 19 090 19 272

Trucks 2 776 2 803 2830 2 857 2 884 2 912 2 940 2 968 2 996 3 025 3 054 3 083 3 113

The number of electric vehicles on road 259, including electric trucks, can be calculated based on the given ratio presented in Table 21 and findings in Table 22. For example, Table 31 shows the ratio is 29,58% by 2030 and Table 22 shows it will be 19 272 vehicles on road 259 by 2030, which means that it can exist 5 968 electric vehicles on road 259 by 2030. The findings of both electric vehicles and electric trucks are presented in table 23.

Table 23. Electric Vehicles and Trucks on road 259

Year 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030

Electric 158 241 361 526 749 1 046 1 428 1 907 2 489 3 175 3 954 4 807 5 968 Vehicles

Electric 26 39 58 85 121 169 231 308 402 513 639 776 920 Trucks

In order to calculate annual income, the numbers for year 2030 will be used since Södertörn Crosslink will be finished first in 2030. The annual income includes revenues from both electric buses and electric vehicles through a user fee (1 SEK/km) less the maintenance cost (17), which is 1,5% of the ERS investment (Jonsson, 2019; Hasselgren et al., 2018). The maintenance cost for each ERS technology is shown in Table 24. Note that the conductive overhead technology only applies to trucks (and other heavy vehicles, e.g. buses) since private cars are not suitable for this technical solution (Nashed, 2018; Hasselgren et al., 2018). Table 24 shows a comparison of annual income for each ERS technology.

Table 24. Annual Income ERS Technology Revenues (SEK) Maintenance (SEK) Income (SEK)

Inductive 42 678 715 (3 000 000) 39 678 715

Conductive Rail 42 678 715 (3 600 000) 39 078 715

Conductive Overhead 7 798 759 (4 200 000) 3 598 760

The results in Table 24 are based on the number of electric vehicles from year 2030, that are shown in Table 23, and the current bus fleet. The other forecasts of electric vehicles in 2030

are shown in Table 25. The percentage-row is the ratio between the forecasted number of electric vehicles [Tab. 25] and the number of vehicles in 2030 that were taken from Table 21.

Table 25. Other Forecasts

Source 2030-sekretariatet Andersson & Kulin Viklund Viklund (2020) (2019) (2020) (2020)

Electric Vehicles 1 700 000 2 500 000 950 000 1 500 000

Percentage 31,16% 45,83% 17,41% 27,50%

Electric vehicles 6 006 8 832 3 356 5 299 on road 259

Electric trucks 970 1 426 542 856 on road 259

Based on the data [Tab. 25], revenues, maintenance costs and incomes are shown in Table 26. Table 26 only applies to inductive technology. The findings of both conductive rail and conductive overhead technology are shown in Table 27 and 28 respectively.

Table 26. Income of Using Inductive

Source Revenue (SEK) Maintenance (SEK) Income (SEK)

2030-sekretariatet (2020) 44 923 529 (3 000 000) 41 923 529

Andersson & Kulin (2019) 65 555 651 (3 000 000) 62 555 651

Viklund (2020) 25 580 915 (3 000 000) 22 580 915

Viklund (2020) 39 765 499 (3 000 000) 36 765 499

The next table [Tab. 27] presents revenues, maintenance costs and incomes when using the ERS technology conductive rail.

Table 27. Income of Using Conductive Rail

Source Revenue (SEK) Maintenance (SEK) Income (SEK)

2030-sekretariatet (2020) 44 923 529 (3 600 000) 41 323 529

Andersson & Kulin (2019) 65 555 651 (3 600 000) 61 955 651

Viklund (2020) 25 580 915 (3 600 000) 21 980 915

Viklund (2020) 39 765 499 (3 600 000) 36 165 499

The next table [Tab. 28] presents revenues, maintenance costs and incomes when using the ERS technology conductive overhead.

Table 28. Income of Using Conductive Overhead

Source Revenue (SEK) Maintenance (SEK) Income (SEK)

2030-sekretariatet (2020) 8 161 316 (4 200 000) 3 961 316

Andersson & Kulin (2019) 11 483 572 (4 200 000) 7 293 572

Viklund (2020) 5 037 325 (4 200 000) 837 325

Viklund (2020) 7 328 251 (4 200 000) 3 128 251

6.2.1.3 Payback Period As previous findings indicate that there will not be any payback period for scenario 1 due to annual losses, this subsection only applies to scenario 2. The payback period varies between ERS technologies and the payback period for the inductive technology is 5 years or 7 years with regard to a discount factor of 9,0 percent [Fig. 12]. The payback period for conductive rail technology is 6,1 years or 9,3 years with regard to discount factor [Fig. 13] while the payback period for conductive overhead technology is 77,8 years. There is no payback period for conductive overhead technology if taking the discount factor into consideration [Fig. 14]. These payback periods, and following graphs, are based on the forecasts made in this study.

Figure 12. Payback Period for Inductive

Figure 13. Payback Period for Conductive Rail

Figure 14. Payback Period for Conductive Overhead

The blue line, in figures 12-14, represents the total net present value for each year. The dashed line shows the initial investment cost for ERS, i.e. in-road and roadside components. The point in which the two lines intersect shows the payback period for the investment. In other words, the net present value is positive when the blue line exceeds the dashed line.

6.2.1.3.1 Comparisons This subsection presents comparisons of payback periods between this study’s forecast and other forecasts. The following table [Tab. 29] presents different predictions concerning the payback period for inductive technology. The predictions are based on forecasts regarding the deployment of electric vehicles on road 259, see Table 23. Additionally, the prediction made in this master thesis is also presented below [Tab. 29]. The other payback period-figures [Fig. 22-25] are shown in the appendix.

Table 29. Comparisons with Forecasts (Inductive)

Source Payback Period (years) Payback Period including discount factor (years)

Study’s forecast 5 7

2030-sekretariatet (2020) 4,8 6,5

Andersson & Kulin (2019) 3,2 4

Viklund (2020) 8,9 18,5

Viklund (2020) 5,4 7,2

The following table [Tab. 30] presents payback periods for conductive rail technology, based on forecasts, including comparison with this study’s forecasts. The payback period-figures [Fig. 26-29] for conductive rail are shown in the appendix.

Table 30. Comparisons with Forecasts (Conductive Rail)

Source Payback Period (years) Payback Period including discount factor (years)

Study’s forecast 6,1 9,3

2030-sekretariatet (2020) 5,8 8,7

Andersson & Kulin (2019) 3,8 5

Viklund (2020) 10,9 47

Viklund (2020) 6,6 10,5

The next table [Tab. 31] presents payback period for the ERS conductive overhead technology. The other payback period-figures [Fig. 30-33] are shown in the appendix.

Table 31. Comparisons with Forecasts (Conductive Overhead)

Source Payback Period (years) Payback Period including discount factor (years)

Study’s forecast 77,8 -

2030-sekretariatet (2020) 70,7 -

Andersson & Kulin (2019) 38,4 -

Viklund (2020) 334,4 -

Viklund (2020) 89,5 -

Table 31 shows that conductive overhead solution will not be profitable when taking the discount factor into consideration. According to Hasselgren et al. (2018) and Nashed (2018), private cars cannot use the ERS technology conductive overhead due to high height between the ground and the overhead wires. This made that the conductive overhead technology can only be used by buses and trucks, which provided lower incomes.

6.2.2 Battery Capacity Requirement The energy consumption for a 12 meter (normal bus) electric bus is set to 1,4 kWh/km (Vattenfall, 2015) and 2,3 kWh/km for an 18 meter (articulated bus) electric bus (Andersson, 2017). The following figures 15-18, in this subsection, show how much each bus line receives (positive slopes) and losses energy (negative slopes) at a trip back and forth. The black dashed line represents SOC-limits. Based on the figure and the equations (15) and (16), the battery capacity can be presented. Figure 15 presents the energy variations of bus line 172.

Figure 15. The Energy Consumption of Bus Line 172

Bus line 172 [Fig. 15], using a 12-m electric bus (blue line), will need three receivers and a battery capacity of 66 kWh in order to manage to go back and forth on a 50,2 km route. The 18-m electric bus (red line) will need six receivers and a battery capacity of 106 kWh. The next figure [Fig. 16] presents the energy variations for bus line 709.

Figure 16. The Energy Consumption of the Bus Line 709

Bus line 709 [Fig. 16], using a 12-m electric bus (blue line), will need three receivers and a battery capacity of 58 kWh. The 18-m electric bus (red line) will need six receivers and a battery capacity of 80 kWh. The next figure [Fig. 17] presents the energy variations for bus line 740.

Figure 17. The Energy Consumption of the Bus Line 740

Bus line 740 [Fig. 17], using a 12-m electric bus (blue line), will need two receivers and a battery capacity of 30 kWh, while the 18-m electric bus (red line), needs four receivers and a

battery capacity of 30 kWh. The next and last figure [Fig. 18] in this subsection presents the energy variations for bus line 865.

Figure 18. The Energy Consumption of the Bus Line 865

Bus line 865 [Fig. 18], using a 12-m electric bus (blue line), will need three receivers and a battery capacity of 18 kWh. The 18-m electric bus (red line) will need five receivers and a battery capacity of 33 kWh.

The following table [Tab. 32], is a summation of the data presented in this chapter. The blue texts represent 12-m electric buses and the red text represents 18-m electric buses.

Table 32. Battery Capacities and Number of Receivers Bus Line Required Receivers Required Receivers battery capacity (30kW) battery capacity (30kW) (kWh) (kWh)

172 66 3 106 6

709 58 3 80 6

740 30 2 30 4

865 18 3 33 5

6.2.3 Bus and Component Transitioning Cost This subsection presents what transitioning costs exist for a bus company, including fuel costs, battery costs, bus costs, ERS component costs, and lifetime costs.

6.2.3.1 Fuel Costs The following table [Tab. 33] shows the annual energy consumption and costs for each bus line.

Table 33. Energy Consumptions and Costs Bus line Energy Consumption (kWh) Cost (SEK)

172 11 428 698 16 885 815

709 1 405 673 1 785 205

740 5 000 208 6 936 228

865 3 585 882 4 303 058

The four bus lines consume a total of 21 420 460 kWh annually, with a total cost of 29 910 305 SEK.

The following table [Tab. 34] shows the energy consumption of using electricity as a propellant.

Table 34. Energy Consumption of Using Electric Bus line Energy Consumption (kWh) Cost (SEK)

172 3 029 865 1 817 919

709 334 864 200 810

740 1 343 018 805 812

865 1 121 854 673 112

Total 5 829 420 3 497 653

The total annual energy consumption, using electricity as a propellant, would be 5 829 420 kWh. This value is based on the average energy consumption in Huddinge-, Söderort- and Botkyrka county, i.e. 1,5 kWh/km, see subsection 5.3. The total cost of using electricity as a propellant is about 3 500 000 SEK per year, using a tax-exempt electricity price of 0,60 SEK

per kWh (SLL - Strategisk Utveckling, 2018). Consequently, about 26,4 MSEK can be saved annually by using electricity compared to fuels.

Further, the energy saving potential is 72,88% [Fig. 19]. If instead using the average energy consumption of 5,25 kWh/km (fuel), see subsection 5.4.1, the energy saving potential will be 71,43%. The figure 19 shows the annual energy consumption difference between using propellant fuel and electricity.

Figure 19. The Comparison between Fuel and Electric

6.2.3.2 Battery, Receiver & Bus Costs This following subsection presents the total cost of both batteries and receivers based on findings received in subsection 6.2.2. The total battery cost of each bus line is presented in Table 37. Note that some bus lines do not have any 12 m buses or 18 m buses. If so, this is marked with a “-” in the Tables 35-37.

Table 35. The Battery Costs Bus line 12 m bus (SEK) 18 m bus (SEK)

172 - 208 608

709 114 144 -

740 59 040 59 040

865 - 64 994

Table 36 presents the receiver costs and also the number of receivers required for each bus.

Table 36. The Receiver Costs Bus line Receivers 12 m bus (SEK) Receivers 18 m bus (SEK) (12 m bus) (18 m bus)

172 - - 6 90 000

709 3 45 000 - -

740 2 30 000 4 60 000

865 - - 5 75 000

Finally, the total cost, for both batteries and receivers for each bus, is presented in table 37.

Table 37. The Total Cost Bus line 12 m bus (SEK) 18 m bus (SEK)

172 - 298 608

709 159 144 -

740 89 040 119 040

865 - 139 944

The transition to an electrified bus fleet, operating on Södertörn Crosslink, will require a total amount of 46 new buses, 11 new 12-m buses and 35 new 18-m buses. A 12-m electric bus cost about 6 300 000 SEK (Potkany et al., 2018; Sustainable Bus, 2020) while an 18m electric bus cost about 7 800 000 SEK (Törnqvist, 2019). A total of 217 receivers will be required, with a total cost of 2 985 000 SEK. The total battery cost will be 4 095 408 SEK, where the battery cost per kWh is 1968 SEK per kWh. Note that some 18m buses are assumed to replace the current bogie buses that have a length of 14,5 m. The total cost, including batteries, receivers and electric buses, will be 349 380 408 SEK.

6.2.3.3 Mechanical Arm Costs The total cost for 46 electric buses, including mechanical arms with a cost of 1 380 000, will be 343 680 000 SEK using conductive rail.

6.2.3.4 Pantograph Costs Using conductive overhead technology costs 3 680 000 SEK for 46 pantographs, where the total cost, including electric buses, will be 345 980 000 SEK.

6.2.3.5 Lifetime Cost The lifetime cost of both electric buses and non-electric buses is compared in Figure 20. The blue line represents electric buses and the red line represents non-electric buses.

Figure 20. Lifetime Cost

Figure 20 shows that the lifetime cost of electric buses will be cheaper than non-electric buses after six years (see the intersection point in Figure 20). For instance, if comparing the lifetime costs after a 10-year period, the electric buses will be about 120 MSEK cheaper. Figure 21 shows cost differences between non-electric buses and electric buses for ten years. The yellow block represents the cost of energy consumption, the red block represents maintenance cost and the blue block represents the initial vehicle cost.

Figure 21. Cost Comparison between Fuel and Electric

6.2.4 Subsection Summary This subsection summarizes the most important findings, subsections 6.2.1-6.2.3, in a bulleted list. These important findings will be discussed in the following chapter.

- Charges and Incomes The charge of using an electric road is an user fee, where the fee is 1 SEK per km. The electric road operator can earn about 1 MSEK annually if only using the bus traffic. This does not provide any profitability due to the high maintenance costs of ERS technology, regardless of which ERS technology is chosen. To generate profitability, several electric vehicles are also needed. The forecast of the number of electric vehicles for 2030 was made since the Crosslink Södertörn will assumably be finished in this year. Thus, the annual income for inductive technology will be 40 MSEK [Tab. 24] while the annual income for conductive rail will be 39 MSEK [Tab. 24]. The conductive overhead technology will earn 3,6 MSEK [Tab. 24] in each year. These annual incomes are based on this study’s forecast. Other forecasts show that the annual income for inductive technology will be around 23 - 63 MSEK [Tab. 26] while the annual income for conductive rail will be around 22 - 62 MSEK [Tab. 27]. The annual income for conductive overhead technology will be around 0,8 - 4 MSEK [Tab. 28].

- Payback period Based on information about annual incomes, the payback period can be calculated. The payback period with the discount factor and the payback period without the discount factor are calculated in order to see the difference. There is no payback period for scenario 1 due to low traffic volume regardless of including discount factor or not. Regarding scenario 2, the payback period, concerning a discount factor of 9,0 percent for inductive technology, based on this study’s forecast, is 7 years [Tab. 29]. If not including the discount factor, the payback period will be shorter, i.e. 5 years [Tab. 29]. For the conductive rail technology, the payback period with the discount factor, based on this study’s forecast, is 9,3 years while the payback period without the discount factor is 6,1 years [Tab. 30]. There is no payback period for conductive overhead technology if including the discount factor since this technology is limited to heavy trucks, which results in low incomes. However, if not including the discount factor, the payback period for conductive overhead technology, based on this study’s forecast, can be 77,8 years [Tab. 31]. Other forecasts are shown in tables 29-31 and the idea of other forecasts is to compare to this study’s forecast. Most of the other forecasts are close to the study’s forecast.

- Battery Capacity Requirement The bus lines 172 and 709 require higher battery capacity compared to the two other bus lines 740 and 865. The battery capacity of both bus lines 172 and 709 is 66-106

kWh and 58-80 kWh respectively. The battery capacity of both bus lines 740 and 865 is 30 kWh and 18-33 kWh respectively. The battery capacities were based on bus travel back and forth.

- Transitioning Costs The propellant cost will be about 26 MSEK cheaper each year if beginning the electric buses instead of non-electric buses.The total cost of electric buses, including receivers, a mechanical arm, or a pantograph, will be around 343 - 350 MSEK. The lifetime cost of electric buses will be cheaper after six years. The implementation of ERS for Södetörn Crosslink will cost around 200 - 280 MSEK. The cost margins depend on which ERS technology will be chosen.

7. Analysis & Discussion The findings, that were presented in the previous chapter, are analyzed and discussed in order to make actions or obtain alternative solutions. This subsection is introduced by a sensitivity analysis.

7.1 Sensitivity Analysis This subsection discusses uncertainties in the input data used in mathematical models as well as assumptions made throughout the report. Each point of sensitivity analysis is briefly described below.

- The most demanding route is chosen for each bus line, see subsection 5.4. However, bus line 172 and 709 have some shorter routes that barely (or not at all) utilize the electric road system. However, these routes have about 1-2 departures per week, consequently, this data can be neglected as it will not noticeably affect the result concerning the income for the electric road operator.

- The cost for electricity, received from ERS, is assumed to be free from taxes and around 0,6 SEK/kWh. (SLL - Strategisk Utveckling, 2018). However, the price for electricity is not yet decided, consequently the price could change before 2030. Further, the energy consumption for electric buses is set to 1,4 kWh/km for 12-m electric buses and 2,3 kWh/km for 18-m electric buses. Electricity will most likely only be used for driving and air conditioning. However, considering Swedish winter temperatures, an additional diesel-powered auxiliary heater will probably be required in each bus. Consequently, this would increase the overall energy usage. Making changes to the electricity price or to the energy consumption requirement, could affect the obtained results regarding energy saving potential and lifetime costs for electric buses.

- The equations used for determining the battery capacity requirement are based on two assumptions. Firstly, the energy consumption is assumed to be constant, i.e. the energy consumption is assumed to only be dependent on the driven distance. Previous studies have made a similar assumption, see subsection 5.3. However, in real life, the energy consumption varies. Therefore, the graphs presented in 6.2.2, would more accurately not have a linear appearance due to variations in energy consumption. The estimated average energy consumption per km varies between earlier studies, Vattenfall (2015) assumes a 12-m electric bus to have an average energy consumption of 1,4 kWh per km while Beekman and van den Hoed (2016) assumes an average energy consumption of 2,0 kWh per km. Different assumptions regarding energy consumption per km can affect the outcome of the results. Secondly, the buses are

assumed to continue their current operations even after Södertörn Crosslink is built. In other words, bus lines 172, 709, 740, and 865, are expected to drive the same route as they drive today. This assumption was made in order to determine how far each bus line potentially will travel on ERS in order to determine the battery capacity requirement and the income for the electric road operator. However, changes to the direction of the routes might occur. Consequently, the obtained results might be less accurate by the time Södertörn Crosslink is finished.

- The battery cost is calculated according to the current price of 1 968 SEK per kWh (Bateman et al., 2018). However, the battery price is expected to decrease until 2030. Therefore, the results regarding lifetime costs for electric buses will likely change.

- The distance and time spent on ERS, for each bus line, are determined by using primary sources obtained through mail contact with the Administrative Authority in Stockholm and by using Google Maps. Deviations in time as well as distance spent on ERS can occur due to human errors. Therefore, if the experiment was about to be carried out again, the results could differ from the ones provided in this report.

- The forecast made in this report, regarding the increase of electric vehicles in Sweden, is based on historical data. The result obtained in this study shows that there will be approximately 1,6 millions electric vehicles in Sweden by 2030. This result is close to previous forecasts provided by Viklund (2020) (1,5 millions electric vehicles) and 2030-Sekretariatet (2020) (1,7 million electric vehicles). However, compared to the forecast made in this study, forecasts obtained from other studies are based on several parameters. Therefore, the obtained result might be considered as less accurate.

- The number of electric vehicles, on Södertörn Crosslink in 2030, adopted to ERS technology might not be equivalent to the number of electric vehicles. This, due to the fact that a full scale implementation of ERS deployment probably has not yet occured. Therefore, it is unlikely to assume that all electric vehicles owners have made investments in supporting technologies, such as receivers or mechanical arms. Consequently, the payback period for the electric road operator will probably be longer compared to the result obtained in this study.

- Some of the data gathered from earlier studies provides a range of different numbers, for instance, the cost of ERS technologies. At many occasions the most expensive alternative has been used in order to obtain findings from a worst case scenario perspective. Hence, using other numbers would provide different results.

7.2 ERS Technology, Charges, Incomes and Payback Period Two different scenarios were formulated in the introduction concerning the economic perspective of ERS profitability:

- Scenario 1: All bus traffic currently operating on road 259 is electrified.

- Scenario 2: All traffic (private cars, commercial trucks, and buses) currently operating on road 259 is electrified.

Regarding scenario 1, the electric road operator can earn 1 080 270 SEK per year by receiving payments from the four bus lines presumed to operate on Södertörn Crosslink using ERS. However, this alternative alone will result in heavy losses due to high annual maintenance costs.

Considering scenario 2, based on provided scenarios in subsection 6.2.1.2, Table 24, the electric road operator can generate an annual income of 39 678 715 SEK, using the inductive technology, 39 078 715 SEK per year using the conductive rail technology, and 3 598 760 SEK per year using the conductive overhead technology. If using the results from other forecasts regarding electric vehicles in Sweden, see Table 26, the annual income for inductive technology will be 22 580 915 - 62 555 651 SEK per year, 21 980 915 - 61 955 651 SEK per year for conductive rail technology [Tab. 27], and 837 325 - 7 293 572 SEK per year for the conductive overhead technology [Tab. 28].

The implementation cost of ERS varies between the three technologies. The most expensive ERS technology is the conductive overhead solution (Jonsson, 2019). Conductive rail and inductive wireless solutions provide similar results regarding costs. However, the inductive solution seems to be slightly cheaper. Further, it is clear that the costs associated with on- vehicle-components, such as receivers and pantographs do not differ much between the technologies. The total cost for the most expensive alternative only differs 5,7 MSEK from the least expensive. Thus, the major costs are due to ERS infrastructure implementation and not due to on-vehicle-components. (Interviewee 2, 2020).

In subsection 6.2.1.3, the payback period for each ERS technology is presented. The findings show that the payback period for inductive and conductive rail technologies is about 5 years and 6,1 years respectively. If considering a discount of 9,0 percent, the payback period will be 7 years for inductive technology and 9,3 years for conductive rail technology. Regarding the conductive overhead technology, the payback period will be 77,8 years and if including the discount factor, it does not provide any payback period due to low incomes each year.

Figures 30-33, see appendix, shows that an investment in conducive overhead technology will never generate profits due to negative net present value. If looking at other forecasts, the payback period (including the discount factor) can be shorter or longer. The best and worst case for inductive technology is 4 [Fig. 23] respectively 18,5 years [Fig. 24]. However, Table 29 also shows that most payback periods are close to the best case. For example, one of the forecasts shows that the payback period is 6,5 years [Fig 22; Tab. 29], which only differs by 2,5 years from the best case. Regarding the conductive rail technology, the best case is 5 years [Fig. 27] while the worst case is 47 years [Fig. 28]. In the worst case for conductive rail technology, it is on the verge of profitability [Fig. 28]. Consequently, there might be a risk of reaching profits if it was fewer road users, which provide negative net present value. However, other cases [Fig. 26; Fig. 29] will be profitable by a good margin. Their payback periods are about 8,7-10,5 years [Tab. 30], which are close to the result of the best case compared to the worst case.

In summary, compared to the first scenario, the second scenario generates profits. A high number of electric road users is an important and crucial factor for profitability. The scenarios provided assumes that all electric vehicles will be adopted to ERS technology in 2030. However, this might not be the case since a full scale deployment might not have occurred yet. Consequently, the number of vehicles able to use and pay for the use of ERS on Södertörn Crosslink will be less then the provided results implies. Additionally, one might not assume that all vehicles using the road are in need of recharging their vehicles. Vehicles using larger batteries consequently having higher battery capacities, can drive long distances without using ERS systems. Therefore, considering these two aspects, the income for the electric road operator might be less than what the result above implies.

7.3 Battery Capacity Requirement Bus line 172, 18-meter electric bus, cannot complete the required route without crossing the 20 % SOC limit line. Frequencies between departures is noticeably high for line 172 where each bus, on average, has 34 departures per day, see appendix. Consequently, implementing ERS infrastructure on Södertörn Crosslink is not sufficient for this particular route, hence, additional charging technology is necessary. Due to high frequencies between departures and the battery type used for ERS, “additional charging technology” (Törnqvist, 2019) would be the best option as this enables quick recharging at bus stops and end stations.

Bus line 709 can barely complete the required route without crossing the 20 % SOC limit. Therefore, additional charging infrastructure (Törnqvist, 2019) would be required for this route. However, there are only a few departures every day, see appendix, and the frequency between departures is low. Hence, additional charging infrastructure deployment at end stations could be a sufficient solution.

Bus line 740 and 865 seems to manage their routes without any risk of crossing the 20 % SOC limit. A trip back and forth on the route seems to be no problem for both of the lines. However, additional charging infrastructure at end stations could be necessary as the energy in the battery at some point might fall below the SOC limit, at least for the buses with most departures during the day, see appendix. In summation, bus lines 740 and 865 seem to have the most ideal routes as they, to a great extent, can rely on the ERS infrastructure on Södertörn Crosslink.

An energy measuring system will be required in order for the vehicle battery to not fall below or exceed the SOC span limits of 20-80 %, consequently experiencing battery wear. A new actor, responsible for measuring customer energy consumption, might be necessary, depending on the choice of ERS technology. The inductive solution, provided by Electreon, has already incorporated an energy measuring device within the technology in which they provide (Interviewee 1, 2020). Hence, by using the wireless inductive solution, the need for an additional actor becomes unnecessary.

To summarize, the choice of average energy consumption for the bus will impact the final results, i.e, the requirement of battery energy capacity and power transmission. Further, it is important to note that minimizing the battery capacity required, could create a very sensitive system as there is no room for route flexibility (Lantz & Aldenius, 2020). Therefore, the obtained results in 6.2.3 should be taken with precautions, and be seen as the minimum battery capacity required.

7.4 Energy Saving Potential and Vehicle Lifetime Costs Subsection 6.2.3.1 shows comparisons between the use of fuel and electricity. The consumption of electricity will be about 5 800 000 kWh per year, which is 15 600 000 kWh lower compared to the use of fuels, consuming 21 400 000 kWh per year. The cost will be reduced by approximately 26,4 MSEK per year and the energy saving potential will be around 72,88% [Fig. 21] (or 71,43% if using the average of energy consumption, 5,25 kWh/km), which is close to the forecast, created by SLL - Strategisk Utveckling (2019b), that showed an energy saving potential of 67% in the same area (Huddinge/Botkyrka/Söderort).

The lifetime cost, including investments in new vehicles, maintenance and change of battery, shows that electric buses will be cheaper in the long-term. Due to a higher initial investment costs, it takes at least 6 years before an investment in electric buses is considered to be profitable. The energy consumption cost as well as the maintenance cost is lower for electric vehicles. The time in which the investment becomes profitable is directly dependent on the driven distance. Therefore, the energy consumption price has considerable influence on the payback peroid for electric vehicles. The cost of energy consumption, used in calculations, was 0,60 SEK/kWh without including tax (SLL - Strategisk Utredning, 2018). According to SLL - Strategisk Utveckling (2018), the cost of energy consumption, including taxes, is

about 0,90 SEK/kWh. Consequently, decisions regarding the future electricity price will affect the payback period for electric buses.

8. Conclusion This final chapter initially presents the answer to the two research questions. This chapter also includes discussions about research contributions, limitations and a few recommendations to future work.

8.1 Answer to the Research Questions Firstly, the two research questions of the master thesis and two scenarios (RQ1) are repeated in this subsection and, thereafter, answered and analysed. Note that the answer to the second research question is presented after Table 38.

- Scenario 1: All bus traffic currently operating on road 259 is electrified.

- Scenario 2: All traffic (private cars, commercial trucks, and buses) currently operating on road 259 is electrified.

There is no payback period for scenario 1 due to high maintenance costs. This means that Södertörn Crosslink will not be profitable. Regarding scenario 2, the payback period varies depending on chosen ERS technology, the number of electric vehicles on Crosslink Södertörn, and the impact of the discount factor. If including the discount factor, the payback period for the inductive solution is 7 years, and 9,3 years for the conductive rail, based on this study’s forecast on the increase of electric vehicles during the period 2021-2030. However, there is no payback period for conductive overhead technology due to low annual incomes. Thus, a large traffic volume is required in order to increase the profitability of the investment.

The implementation cost on Crosslink Södertörn will be around 200 MSEK for the inductive technology, and around 240 MSEK for the conductive rail solution. The implementation cost for conductive overhead technology will be around 280 MSEK.

The comparison made in subsection 2.1.3, regarding advantages and disadvantages between ERS technologies, shows that conductive rail or inductive wireless solution are applicable to both heavy trucks, buses and private vehicles, and therefore, viewed from an economic perspective, the only suitable solutions for Södertörn Crosslink. Both the inductive and conductive rail technology generates high incomes and can provide long-term profitability. The conductive overhead technology has, compared to the other solutions, a high technology readiness and is considered to be ahead of the technical development. Additionally, this

technology provides high energy efficiencies and power transmissions. However, since the overhead solution only applies to heavy vehicles, i.e. buses and trucks, it is not suitable to the studied case. Further, considering aesthetics, the inductive solution has no visual impact on the surrounding environment compared to the conductive rail solution which has some minor impacts. The conductive rail solution has a higher rate of energy transfer compared to the inductive technology. However, the energy transfer rate, for the inductive technology, is expected to improve within this upcoming year, consequently reaching the same magnitude as the conductive rail solution. Finally, the conductive rail solution has a higher need for maintenance since there is mechanical wear between the vehicle (with mechanical arm) and the conductive rail. Considering aspects connected to economics, technology and aesthetics, the inductive solution provides best results and therefore considered to be the best solution for implementation on Södertörn Crosslink. The following table [Tab. 38] provides a scale between green and red where green represents “no challenge” and red “major challenge”.

Table 38. Comparison between ERS technologies (Ezer & Tongur, 2020) Inductive Conductive Rail Conductive Overhead

Implementation Cost

Maintenance Costs

Visual Impact

Mechanical Wear

Energy Metering System

Maturity Level

Support Heavy Vehicles

Support Light Vehicles

Power

Energy Efficiency

RQ2: Is it profitable in the long term for a bus operator to transition to an electrified bus fleet, assuming the use of ERS technology?

A transition to an electrified bus fleet will require additional costs. Replacing the current bus fleet with electric buses will cost around 343-350 MSEK. The cost margin depends on which ERS technology is used. Initially, the costs of electric buses are higher compared to conventional buses as a consequence of a higher purchase price. However, the fuel costs of non-electric buses are about 26 MSEK per year more expensive compared to electric buses. Consequently, the lifetime cost of electric buses is cheaper in the long term. After 6 years of

use, the electric alternative is estimated to reach profits. Thus, it is profitable in the long term for a bus operator to transition to an electrified bus fleet, assuming the use of ERS technology.

8.2 Research Contribution The aim of this master thesis was to investigate and obtain findings regarding costs and payback period for the implementation of ERS technology on the future road, Södertörn Crosslink. Theoretically, this paper provides an increased understanding of ERS both from an economic and technological perspective. Based on findings obtained, the traffic volume has a major impact on potential revenues for the electric road operator. However, a full scale implementation of ERS technology has to be implemented as pilot project deployments will not be sufficient in order for electric road users to invest in vehicles applicable to the electric road infrastructure. Consequently, the electric road operator will, in most cases, not earn revenues before a full scale deployment of ERS. However, considering a full scale deployment scenario, where the number of electric vehicles adopted to ERS technology follows the forecast provided in this study, investments in ERS infrastructure will be beneficial from an economic perspective.

This study has also investigated the possibility of using ERS to support the bus lines currently operating on road 259. The equations used for determining the battery capacity requirement, number of receivers, and energy saving potential can be used for other projects. However, input data, specific to the investigated road, has to be gathered. The equations used for determining the payback period can also be used in other projects, however, additional data regarding traffic volume and distance on ERS has to be determined with consideration to the specific road.

This thesis has also provided information regarding costs for conventional and electric buses as well as made relevant comparisons. The purchase price of electric buses are significantly more expensive compared to conventional buses. However, since the price for electricity is lower than the price for renewable fuels, the investment in electric buses on Södertörn Crosslink becomes profitable after 6 years. Consequently, this thesis has contributed with information regarding investment opportunities that lies within transitioning to an electrified bus fleet.

Even though the conductive overhead solution is considered to be more mature, have higher power transmission capabilities and efficiencies, this technology does not generate profits since it is only suitable to certain vehicles. The conductive rail and inductive wireless solutions, viewed from an technological perspective, provide similar benefits. From findings, the inductive technology seems to be slightly cheaper and require less maintenance costs compared to the conductive solution. However, considering power and energy efficiency, the conductive technology is superior. Although, if the inductive solution reaches the same

capabilities as the conductive technology, concerning power and energy efficiency, this solution will be most suitable for Södertörn Crosslink, and possible on other roads/highways. Further investigations regarding technology and financing are required before implementing ERS on a larger scale.

8.3 Limitations This master thesis has encountered several limitations. Due to an unforeseen global virus pandemic, the research process became more complicated as this limited the possibilities for in personal meetings as well as opportunities for gathering materials through interviews. Additionally, the researchers of this paper experienced it to be difficult to come in contact with certain persons as a consequence of people working from home. This study was carried out as a case study on Södertörn Crosslink. Since all gathered data regarding payback period, traffic volumes and bus lines only is applicable to the studied road, the findings of the study are not considered to be generalizable. Therefore, similar studies will be required for other roads.

8.4 Recommendations for Future Work This master thesis is concluded by providing a few recommendations on future work and key takeaways based on findings of this study and own reflections. Some of the recommendations are supported by earlier studies.

- The traffic volume is the most important factor in determining if an implementation of ERS has the potential to become profitable. This statement is supported by Andersson et al (2019), arguing that the traffic volume has a major impact on potential revenues for the electric road operator. This, since the income is dependent on the user fee in which is based on the driven distance on ERS (SEK/km). It is plausible to assume that traffic volumes, sufficiently high enough to create revenues, will first occur at a full-scale deployment of ERS. Minor pilot projects deployments will not be sufficient in order for electric road users to invest in vehicles applicable to the electric road infrastructure. Therefore, in order for the implementation of ERS deployment to accelerate, risks have to be reduced in order to increase private actor participation. According to Hasselgren et al., (2018) the government could reduce risks by guaranteeing a certain traffic volume. This by covering the “loss of profits” if the volume is not reached. Further, forecasts, like the ones provided in this study, will be required in order to make reasonable assumptions regarding traffic volumes. Providing a foundation of information in which established actors can base their decisions upon is important to reduce risks and increase private actor participation. Further, decisions and additional information regarding technology standards, business models, investment responsibilities, costs and return on investments will be

required in order to minimize market uncertainty and accelerate ERS deployment.

- BRT implementation could accelerate the diffusion of electric vehicles as well as the deployment of ERS technology. If certain lanes are dedicated to electric vehicles, this would enable faster transportation, reduced traffic jams and less accidents. Safer transportation and increased accessibility could work as an incentive, consequently, encouraging private and public actors to the transition to electric vehicles.

- Standardization of certain components connected to ERS technology along with providing carefully developed “full-scale deployment plans” could reduce market risks and increase private actor participation. This statement is supported by Andersson et al. (2019) mentioning that, if not choosing a standard, other technologies might advance and provide superior solutions and make the chosen technology obsolete.

- Additional pilot projects are necessary before implementing ERS at a larger scale. This in order to further investigate technology and financing options as well as potential business - and payment models. Since the electric road operator likely will be responsible for high-risk investments (installation and maintenance of ERS technology), this role especially requires further attention. This statement is supported by Morales (2019) and Nashed (2018) mentioning the importance of an increased knowledge base regarding ERS. Further, earlier and ongoing pilot projects, for instance E16 in Sandviken and SmartGotland on Gotland, should be studied and compared to increase the understanding of ERS.

- Owners of private electric vehicles may have to pay for the cost of ERS components, e.g. receivers (inductive), mechanical arm (conductive rail), or pantograph (conductive overhead). Currently, electric vehicles are more expensive than conventional vehicles. A quantitative study, e.g. using surveys, of private vehicle-owners should be performed and analyzed in order to find out their thoughts regarding ERS components and their costs. Are electric vehicle-owners ready to pay the cost of ERS components?

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Appendix This Appendix presents currencies, other payback periods, and detailed information on bus lines.

Currencies There was information on costs in other currencies. Therefore, a currency converter has been used here and at the calculation in order to get results in Swedish currency. See the currency converter below.

(€1 = 10,83 SEK, last checked: 2020-05-04) ($1 = 9,84 SEK, last checked: 2020-05-04)

Payback Periods This appendix also shows figures of payback periods based on other forecasts for the number of electric vehicles in Sweden by 2030 and own calculations for the number of electric vehicles (including electric trucks) on Södertörn Crosslink daily. The figures 22-25 represent payback periods for inductive technology, figures 26-29 represent conductive rail and figures 30-33 represent conductive overhead. Each figure in the appendix is briefly described.

Figure 22. Payback Period for Inductive 1

2030-Sekretariatet (2020) assumes there are 1 700 000 electric vehicles by 2030, which 6 006 electric vehicles drive on Södertörn Crosslink daily. The payback period is about 6,5 years [Fig. 22].

Figure 23. Payback Period for Inductive 2

It will be a total of 2 500 000 electric vehicles in Sweden by 2030 according to Andersson and Kulin (2019). Thus, there can be 8 832 electric vehicles on Södertörn Crosslink daily, in which the payback period can be 4 years [Fig. 23].

Figure 24. Payback Period for Inductive 3

Figure 25. Payback Period for Inductive 4

Viklund (2020) assumes 950 000 - 1 500 000 electric vehicles in Sweden by 2030, which means 3 359 - 5 299 electric vehicles on Södertörn Crosslink daily. Thus, the payback period will be 18,5 years (3 359 electric vehicles) [Fig. 24] or 8 years (5 299 electric vehicles) [Fig. 24].

Figures 26-29 represent payback periods for conductive rail technology. Each figure is based on the same forecasts and own calculations for the number of electric vehicles on Crosslink Södertörn [Fig. 22-25].

Figure 26. Payback Period for Conductive Rail 1

1 700 000 electric vehicles in Sweden by 2030 (2030-Sekretariatet, 2020) and 6 006 electric vehicles on Södertörn Crosslink daily. Thus, the payback period is 8,7 years [Fig. 26].

Figure 27. Payback Period for Conductive Rail 2

2 500 000 electric vehicles in Sweden by 2030 according to Andersson and Kulin (2019), which means 8 832 electric vehicles on Södertörn Crosslink daily. Thus, the payback period is 5 years [Fig. 27].

Figure 28. Payback Period for Conductive Rail 3

Viklund (2020) assumes 950 000 electric vehicles in Sweden by 2030, which means 3 356 electric vehicles on Södertörn Crosslink daily. Thus, the payback period is 47 years [Fig. 28].

Figure 29. Payback Period for Conductive Rail 4

Viklund (2020) also assumes 1 500 000 electric vehicles in Sweden by 2030, which means 5 299 electric vehicles on Södertörn Crosslink daily. Thus, the payback period is 10,5 years [Fig. 29].

Figures 30-33 represent the payback period for conductive overhead technology. The forecasts and own calculations are the same, like inductive and conductive rail technologies. However, figures 30-33 are only based on electric trucks (and other heavy electric vehicles). There are no payback periods for conductive overhead technology.

Figure 30. Payback Period for Conductive Overhead 1

2030-Sekretariatet (2020) assumes 1 700 000 electric vehicles in Sweden by 2030, which means 970 electric trucks on Södertörn Crosslink daily. The payback period is illustrated in Figure 30.

Figure 31. Payback Period for Conductive Overhead 2

Andersson & Kulin (2019) assumes a total of 2 500 000 electric vehicles in Sweden by 2030, which means 1 426 electric trucks on Södertörn Crosslink daily. The payback period is illustrated in Figure 31.

Figure 32. Payback Period for Conductive Overhead 3

Viklund (2020) approximates a total of 950 000 electric vehicles in Sweden by 2030, which means 542 electric trucks on Södertörn Crosslink daily. The payback period is illustrated in Figure 32.

Figure 33. Payback Period for Conductive Overhead 4

Viklund (2020) also assumes a total of 1 500 000 electric vehicles in Sweden by 2030, which means 856 electric trucks on Södertörn Crosslink daily. The payback period is illustrated in Figure 33.

Bus Lines The bus line consists of 7 different routes, three routes in the direction of Skarpnäck-Norsborg, and 4 routes in the opposite direction [Tab. 39]. Four of these routes go on road 259. The total route distance between Norsborg and Skarpnäck is approximately 27 km.

Table 39. Bus Line 172 - Details

172 Starting End Number of Number of Total Total Distance on road Possible station Station departure departure number of distance 259 percentage on (weekday) (weekend) departures / ERS week

1a Skarpnäck Huddinge 1 - 5 12 278 m 0 m 0% Station

1b Skarpnäck Norsborg 89 62 569 26 718 m 6 149 m 23.0%

1c Högdalen Fittja 35 - 175 15 840 m 6 149 m 38.8%

2a Huddinge Skarpnäck 1 1 7 13 184 m 0 m 0% Sjukhus

2b Huddinge Skarpnäck 2 - 10 12 318 m 0 m 0% Station

2c Norsborg Skarpnäck 87 55 545 26 974 m 6 149 m 23.1%

2d Fittja Högdalen 30 - 150 15 362 m 6 149 m 40.0%

Table 40 consists of data representing each and every bus currently operating on bus line 172, including the direction of the route, number of departures, and total distance. Bus ID is the number on the bus and Bus index indicates what type of bus it is, including fuel usage, see bus index tables 9-11 in subsection 6.4.1. The following shortenings have been used; Norsborg (N), Skarpnäck (S), Huddinge Sjukhus (H.sjuk), Huddinge station (H.Stat), Fittja (F), Högdalen (H). The idea of this table is to calculate the energy consumption and cost per year that is presented in subsection 7.2.3.1.

Table 40. Bus Line 172

Bus ID Bus Index Route Departures per day km per day

107071 9 9 N-S 18 483 9 S-N

107069 9 6 N-S 15 361 6 S-N 1 H.Sjuk-S 1 H.Stat-S 1S-H.Stat

106439 11 31 N-S 71 1816 32 S-N 4 F-H 4 H-F

107070 9 1 H.Stat-S 39 1032 19 N-S 19 S-N

106438 11 6 F-H 42 897 6 H-F 15 N-S 15 S-N

103711 12 15 F-H 35 595 15 H-F 3 N-S 2 S-N

103710 12 5 F-H 19 350 9 H-F 3 N-S 2 S-N

Bus 709 line consists of five different routes, where two routes in the direction of Huddinge Station-Truckvägen (Länna) and three routes in the opposite direction [Tab. 41]. All of these routes go on road 259. The total route distance between Huddinge and Länna is approximately 28 km.

Table 41. Bus Line 709 - Details

709 Starting End Station Number of Number of Total Total Distance on Possible station departure departure number of Distance road 259 percentage on ERS (weekday) (weekend) departures / week

1a Huddinge Länna 10 10 70 23 456 m 6 250 m 26.6% Station Handelsplats

1b Huddinge Gladö Kvarn 2 - 10 10 451 m 4 650 m 44.5% Station

2a Länna Huddinge 10 10 70 28 000 m 6 250 m 22.3% Handelsplats Station

2b Länna Gladö Kvarn 1 - 5 19 223 1 600 m 8.3% Handelsplats

2b Gladö Kvarn Huddinge 3 - 15 9 642 m 4 650 m 48.2% Station

Table 42 consists of data representing each and every bus currently operating on bus line 709, including the direction of the route, number of departures, and total distance. Bus ID is the number on the bus and Bus index indicates what type of bus it is, including fuel usage, see bus index tables 9-11 in subsection 6.4.1. The following shortenings have been used; Huddinge station (H.Stat) and Länna (L)

Table 42. Bus Line 709

Bus ID Bus Index Route Departures per km per day day

107606 1 4 H.Stat-L 6 178,334 2 L-H.Stat

107615 1 2 H.Stat-L 8 211,563 6 L-H.Stat

107621 1 4 H.stat-L 7 161,905 3 L-H.Stat

107625 1 1 H.Stat-L 2 59,483 1 L-H.Stat

Bus line 740 has a total of 7 different routes, 3 in the direction Kungens kurva - Huddinge station, and 4 routes in the opposite direction [Tab. 43]. Four of the routes includes traveling on road 259. The total route distance between Kungens Kurva and Huddinge Station is approximately 17 km.

Table 43. Bus Line 740 - Details

740 Starting point End station Number of Number of Total Total Distance on Possible departure departure number of distance road 259 percentage (weekday) (weekend) departures / on ERS week

1a Lindvreten Huddinge 46 28 286 17 180 m 5 500 m 31,1 % station

1b Skärholmen Huddinge 3 3 18 14 613 m 5 500 m 37,6 % station

1c Lindvreten Skärholmen 1 0 5 3 043 m 0 m 0 %

2a Huddinge station Lindvreten 46 29 288 17 708 m 5 500 m 31,1 %

2b Skärholmen Lindvreten 1 0 5 3 034 m 0 m 0 %

2c Huddinge station Skärholmen 0 2 4 14 549 m 5 500 37.8%

2d Skärholmen Kungens kurva 0 16 32 1 789 m 0 m 0 %

Table 44 consists of data representing each and every bus currently operating on bus line 709, including the direction of the route, number of departures, and total distance. Bus ID is the number on the bus and Bus index indicates what type of bus it is, including fuel usage, see bus index tables 9-11 in subsection 6.4.1. The following shortenings have been used; Lindvreten (Lv), Skärholmen (Sk), Kungens Kurva (K) and Huddinge Station (H.Stat).

Table 44. Bus Line 740

Bus ID Bus Index Route Departures per km per day day

107532 5 1 Sk-H.Stat 15 257 11 Lv-H.Stat 3 H.Stat-Lv

104097 11 2 Sk-H.Stat 2 29

107621 1 1 Lv-H.Stat 7 120 6 H.Stat-Lv

107616 1 4 H.Stat-Lv 9 155 5 Lv-H.Stat

105601 7 6 Lv-H.Stat 12 206 6 H.Stat-Lv

105602 7 12 Lv-H.Stat 28 464 1 Lv-K 15 H.Stat-Lv

105600 7 1 Lv-K 19 310 9 Lv-H.Stat 9 H.Stat-Lv

107135 9 2 Lv-H.Stat 3 52 1 H.Stat-Lv

106031 11 4 Lv-H.Stat 10 172 6 H.stat-Lv

107625 1 11 Lv-H.Stat 21 361 10 H.Stat- Lv

107470 1 6 Lv-H.Stat 6 103

107611 1 4 H.Stat-Lv 4 69

107606 1 3 H.Stat-Lv 3 52

106039 11 Lv-H.Stat 1 17

107615 1 H.Stat-Lv 4 69

105711 7 Lv-H.Stat 1 17

Bus line 865 has a total of 4 different routes, 2 in the direction Handen - Skärholmen and 2 routes in the opposite direction [Tab. 45]. All of the routes include travelling on road 259. The total route distance between Handen and Skärholmen is approximately 32 km.

100

Table 45. Bus Line 865 - Details

865 Starting point End station Number of Number of Total Total Distance on Possible departure departure number of distance road 259 percentage (weekday) (weekend) departures / on ERS week

1a Söderbymalmsskolan Skärholmen 27 14 163 31 759 m 19 100 m 60,1 %

1b Söderbymalmsskolan Huddinge 3 1 17 20 380 m 15 760 m 77,3 % sjukhus

2a Skärholmen Söderbymalms 31 14 183 32 217 m 19 100 m 59,3 % skolan

2b Huddinge sjukhus Söderbymalms 9 2 49 20 426 m 15 760 m 77,2 % skolan

Table 46 consists of data representing each and every bus currently operating on bus line 865, including the direction of the route, number of departures, and total distance. Bus ID is the number on the bus and Bus index indicates what type of bus it is, including fuel usage, see bus index tables 9-11 in subsection 6.4.1. The following shortenings have been used; Handen (Ha), Skärholmen (Sk), Söderbymalmsskolan (Sö) and Huddinge Sjukhus (H.Sjuk).

101

Table 46. Bus Line 865

Vehicle ID Bus Index Route Departures per day km per day (total)

303888 6 4 Sö-Sk 6 195,351 2 Sk-Sö

303105 6 2 Sö-Sk 5 162,929 3 Sk-Sö

307267 6 1 Sö-H. Sjuk 3 61,232 2 H.Sjuk-Sö

303100 6 1 Sö-H.Sjuk 6 159,270 1 Sö-Sk 2 H.Sjuk-Sö 2 Sk-Sö

303110 6 1 Sö-Sk 4 130,381 3 Sk-Sö

303111 6 2 Sö-Sk 2 65,096

303891 6 1 Sö-H.Sjuk 4 118,087 2 Sö-Sk 1 Sk-Sö

307261 6 1 Sö-Sk 2 65,159 1 Sk-Sö

303085 6 6 Sö-Sk 9 291,389 3 Sk-Sö

303106 6 1 Sö-Sk 2 65,159 1 Sk-Sö

303151 10 1 Sö-Sk 1 32,548

303150 10 2 Sö-Sk 4 130,586 2 Sk-Sö

303145 10 2 Sö-Sk 4 130,586 2 Sk-Sö

303882 6 1 Sö-Sk 4 118,698 2 Sk-Sö 1 H.Sjuk-Sö

303873 6 1 Sö-Sk 2 65,159 1 Sk-Sö

303870 6 5 Sk-Sö 5 163,523

303141 10 1 H.Sjuk-Sö 1 20,426

303131 10 1 H.Sjuk-Sö 1 20,426

302512 10 1 H.Sjuk-Sö 2 53,037

102

1 Sk-Sö

103 TRITA TRITA-ITM-EX 2020:204