Smart Grids and Electric Vehicles Developing e-mobility at small scale. Giuseppe PACE Ghent University Netlipse Meeting Bruxelles, May 12 th, 2014

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1 Smart Grids and Electric Vehicles Developing e-mobility at small scale Giuseppe PACE Ghent University Netlipse Meeting Bruxelles, May 1 th, 1

2 Summary Introduction Towards a post-car system : a vision Increasing efficiency and reducing congestion: the EV sharing E-Mobility NSR project User cases and tests Some public policy considerations Seite 1

3 1. Introduction Transport sustainability is based on global challenges (e.g. curbing the negative impacts of transport GHG emissions) To limit some modes of transport in favour of others as well as the use of conventionally fuelled vehicles, and to make the overall system efficient Targets negotiated among governments, and public and private stakeholders, often at international level. Infrastructure planning and modelling is based on these perspectives No consumer insight, no lifestyles analysis, no real and continuous data

4 .Towards a post-car system : a vision Lowering the use of fossil fuels in urban mobility without reducing city accessibility and attractiveness, increasing renewable energy usage and make it smart Renewing our culture and consciousness in order to overcome the current car system, apparently stable and unchanging Important technical, economic, policy and social changes e.g. Shift from economies of ownership to economies of access, that is, paying for access to travel/mobility services rather than the outright ownership of vehicles Coevolution of interrelated elements, changes in both demand and supply sides, stakeholders involvement, long-term processes A single policy cannot bring alone to the change

5 3. Increasing efficiency and reducing congestion: the EV sharing De-privatising vehicles, reducing residential parking problems, and associated congestion and local air pollution Car sharing Reducing conventionally fuelled vehicles Electric Vehicles Mostly available in large and medium size cities, rarely in small towns and peripheral areas For customers: success is car availability, competitive pricing, parking facilities, and the possibility to use it door-to-door (close-to-the-house) For car-sharing companies: success is high number of subscribers and rate of daily usage per vehicle, and these conditions can be achieved only in central areas of large cities (close-to-the-market). IS THAT THE SOLUTION?

6 3. Increasing efficiency and reducing congestion: the EV sharing In terms of efficiency, balance between daily availability and usage, price rates, numbers of cars and subscribers. Car sharing dominating model: how to maximise the potential users basin for the service and locates vehicles where the potential car demand would be the highest (stations, commercial areas, public buildings, etc...). Does not cover peripheral communities, as well as commuters, and specific users group needs (tourists, students, business), which have two choices: public transportation (buses or trains, when available, or taxi) or private car. When communities are too dispersed, public transportation operational costs are too high and leave them un(der)-serviced with resulting problems of accessibility and social inclusion (e.g. peripheral urban areas, social housing).

7 3. Increasing efficiency and reducing congestion: the EV sharing For the EV sharing, the traditional car-sharing approach has difficulties to prove its efficiency. The need for battery charging infrastructure highly increases infrastructure costs and reduces parking availability. In absence of dedicated maintenance and proper charging, EV is still not easily implemented. A new way of thinking is needed to support EV sharing solutions: to satisfy the household need of mobility (close-to-the-house) to offer an economic, efficient, aesthetic, emotional, innovative, and sustainable zero-tailpipe-emission (if fully electric) passenger transport door-to-door.

8 . e-mobility NSR project In Europe and the North Sea Region a need for strategies and action plans to develop e-mobility. Actually incentives developed throughout Europe to seize the potential of e- mobility, especially in terms of local and regional traffic. Activities are not synchronized or aligned with one another, and realization is confined to only few places. Opportunities for further development and growth of this future key mobility sector unexploited. E-Mobility NSR aims at creating favorable conditions to promote the common development of e-mobility in the North Sea Region. Transnational support structures in the shape of a network and virtual routes are envisaged as part of the project, striving towards improving accessibility and the wider use of e-mobility in the NSR countries. The project is being undertaken in the framework of the Interreg IVB North Sea Region Programme and runs from October 11 to September 1

9 . e-mobility NSR project Specific project objectives are: To provide state of the art information which may help policy development in e-mobility in the NSR; To provide insight on gaps and needs in respect of infrastructure, logistics, and preliminary standards for multi charging techniques; To develop a NSR smart grid concept with charging points, hence increasing accessibility in the region; To provide a long-term basis upon which regional and local governments as well as other relevant stakeholders in the NSR may engage on e- mobility, among others by creating physical or virtual e-mobility information centres in each participating region or city. To integrate the urban freight logistics dimension into the e-mobility network, promoting better accessibility and cleaner cities by stimulating the use of electric vehicles as a more efficient solution

10 . e-mobility NSR project Main Partners: 1. Hamburg University of Applied Sciences (DE). FDT Association of Danish Transport and Logistics Centres (DK) 3. Lindholmen Science Park (SE). Delft University of Technology (NL) 5. Høje-Taastrup Municipality (DK) 6. Northumbria University (UK) 7. Province of North Holland (NL) 8. Zero Emission Resource Organisation - ZERO (NO) 9. Cities Institute, London Metropolitan University (UK) 1. WFB Wirtschaftsförderung Bremen GmbH (DE) 11. Flanders Region represented by Universiteit Gent (BE)

11 . e-mobility NSR project New Infrastructure for e-mobility UGENT coordinates the WP5 Smart grid solutions, with the aim to develop models of smart grid integrating all connected actors, producers and consumers needs, for distributing energy in efficient, sustainable, reliable and safe mode. Shifting from industry orientation (and lobbies) to market (customer behaviour) Tests about EVs performance (EVs storage capacities, their charging needs and their energy consumption) and uses behaviours and acceptance Three typologies of field tests: Service EVs (public and private) Private EVs (cohousing car-sharing) Public Transport (e-buses)

12 5. User cases and tests Field tests have to: represent cost and time effective alternatives to the main urban traffic producers to guarantee them a door-to-door mobility to increase their accessibility to urban centres, and to decrease direct and indirect costs for the community The alternative is represented by car sharing, which: reduces parking needs and urban traffic Provides a solution for de-privatizing cars Instead of developing an EV sharing system, the test is about a small car sharing in a type of collaborative housing where residents actively participate in the life of their own neighbourhood: THE COHOUSING

13 5. User cases and tests Test population Four co-housing communities in Flanders: two located near a city (Brussels for La Placette, and Gent for Vinderhoute), and two located in Ghent city centre (Papegaaistraat, Sint-Pietersaalststraat,). The communities sizes range from up to 3 people The first two cohousing received two EVs each, and a charging box The second received a bonus to share EVs from Cambio Number of inhabitants Participants in the survey Gender Male Female Age Marital status Single Married Co-habiting N.of children 1 3 or more La Placette Papegaaistraat Sint- Pietersaalstst raat Vinderhoute Total Table 1: Composition of the sample population per co-housing community

14 5. User cases and tests The different location of the cohousing, and more the different familiar composition and ages, separate clearly the suburban from the urban communities. The firsts at the research of a green and less dense housing for growing their family The seconds, without children, at the research of different social life Highest school diploma Secondary school or lower High school University Professional status Student Inactive Part-time job Full-time job Blank La Placette Papegaa istraat Sint- Pietersaal ststraat 3 Vinderhoute Total Table : Education level and professional situation of the sample population

15 5. User cases and tests A initial questionnaire was filled online by all test participants. Main questions 1. Motivations to participate in the project: To work To a shop To bring or get other persons For recreation daily several times a week weekly monthly belief in electric cars as the vehicles of the future. Contribution to the development of electric cars 3. Contribution to a better environment. never 8 Table 3: Frequency of trips for different purposes To work To a shop To bring or get other persons For recreation Car % 59 % 6 % 51 % Private car 9 % 9 % 51 % 38 % Company car 13 % 1 % 9 % 13 % Shared car 1 % 8 % 1 % 1 % Bicycle % % 13 % 31 % Train 13 % % 3 % % Tram or bus 8 % 6 % 3 % 5 % On foot 8 % 1 % 1 % 1 % Other % 1 % % 1 % Table : Most used transport mode for different purposes

16 5. User cases and tests When asked about the aspects determining their choice of a car, the participants tend towards: environmental impact (emissions, safety), and practical value of the car (reliability, price and fuel consumption). For expectations about the performances of the electric car, compared to a classic car, participants tend towards the electric car Most of the participants in the project expect a limited use of the shared car: out of the 78 respondents expect to use the car once a week, out of 78 expect to use it times a week When do you plan to use the car? How do you plan to use the car? Total On week days, during the daytime 5 On week days, during the evening 3 On weekend days, during the daytime 39 On weekend days, during the evening 3 Table 5: Expected use of the shared vehicle: when do you plan to use the shared vehicle? Total As an addition to my current car (as a second car). 3 I currently don't own a car. 17 To replace my current car. 13 (blank) 5 Grand Total 78 Table 6: Expected use of the shared vehicle: how do you plan to use the shared vehicle?

17 5. User cases and tests Trip distance analysis Official statistics for Flanders: average trip distance is 8,795 km. For Ghent urban area trip distance average is 11,96 km (Reports OVG Flanders, 13). For the test, average trip is 7 km, with a shortest trip less than 1 km long and a longest 17 km long. of all trips are less than 11 km long, and of them are longer than 37 km. Half of all trips made are in between of 11 and 37 km. of all trips are shorter than km and just % of trips are longer than 7 km No of obs % 1% 9% 3% 1% % 1% % 1% 1% % % % % Kilometers Figure 1 Distribution of trip distances

18 5. User cases and tests Charging behaviour analysis Charging behaviour is analysed based on two observed values: battery State of Charge (SoC) the time of the day when vehicle is plugged in for recharging (and unplugged). Figure shows distribution of battery SoC value at the start of recharging event for Cambio service users Figure 3 shows the same distribution for cohousing community where vehicles were provided for research purposes. No of obs No of obs % % 1% 3% % 3% % 7% 6% 6% 9% % 11% 13% 18% SoC Figure Distribution of battery SoC at the start of recharging event for cohousing at Papegaaistraat and Sint-Pietersaalststraat 3% % % 3% 3% 3% 7% 7% % 3% 7% 7% 7% 13%13% 1% 1% SoC Figure 3 Distribution of battery SoC at the start of recharging event for Wezenbeek-Oppem cohousing

19 5. User cases and tests Charging behaviour analysis Figure and Figure 5 give an overview of the SoC value at the end of recharging process. For Cambio users batteries are charged to its maximum capacity and users unplug it in 89% of cases when it is full. Users prefer to share EV with highest SoC, and leave others to recharge. It can only happen if there is a sufficient number of EVs available. In Wezenbeek-Oppem cohousing community the distribution of SoC values was different because the reduced availability of the EVs. Only 3% of cases battery s SoC was recharged to its highest value No of obs No of obs % % % 1% % % % 1% % % % 1% 1% % Figure Distribution of battery SoC at the endof recharging event for cohousing at Papegaaistraat and Sint-Pietersaalststraat Figure 5 Distribution of battery SoC at the end of recharging event for Wezenbeek-Oppem cohousing 89% % SoC % % % % % % % % 6% 6% 17% 6% SoC

20 5. User cases and tests Charging behaviour analysis Differences in the time of the day when users start (Figure 6) and stop (Figure 7) recharging process suggest that different SoC distributions can not only be explained by the availability of shared EVs, but with the previous analysed differences in cohousing s population characteristics. No of obs Cambio 1% 1% 1% 9% 9% 9% 8% 8% 7% 7% % 1% 1% 1% %% % StartHour No of obs Wezenbeek-Oppem 13% 11% 1% 1% 8% 8% 7% 7%7% 3% % StartHour That element provide a first interesting insight for a consumer behavior modelling The data collection will bring to a consumer segmentation, and then to the definition of different users profiles No of obs Figure 6 Time of day when recharging is started (left Cambio users, right Wezenbeek-Oppem cohousing) 3% % %% % 3%3% Cambio 6%6% 6% 8% 11% 9% 8% 9% 11% %3% No of obs Wezenbeek-Oppem % 3% 8% 13% 1% 7%7% 11% % 7% 3% % StopHour StopHour Figure 7 Time of day when recharging is stopped (left Cambio users, right Wezenbeek-Oppem cohousing)

21 Thank you Seite