Sustainable Transportation Application for Smart Mobility

Michela Longo, Dept. of Energy

Politecnico di Milano Milano (Italy)

michela.longo@polimi.it,

Mariacristina Roscia Dept. of Enegineering University of Bergamo

Dalmine (Italy) cristina.roscia@unibg.it

Abstract— Electric mobility can be seen as the element capable of breaking the current model "non-sustainable" road transport. It is able to promote a "green revolution" for a smarter mobility and integrated with other sectors of the economy especially with the energy sector. The idea to integrate renewable energy sources, in this case photovoltaic system, with the electric mobility can bring many economic benefits to the environment, both at the urban level and not alone, so much so that it is taken up a route for the future of mobility. The aim of this work describe a possible project of green mobility for a Campus, based on power from renewable sources in order to feed a system of shared transport, in order to optimize traffic flows of vehicles. In this mode, it is possible to have a zero impact of CO2 emissions.

Index Terms-- electric vehicles, green energy, distributed energy resources, smart mobility, CO2 emission

I. INTRODUCTION A new period for electric mobility and integrated, has

already begun, and Europe is at the forefront in this crucial stage of change. The transformation affects not only the energy used by the vehicles and the presence of a new charging infrastructure, but also by the possibility of redesigning the mobility in a more sustainable urban infrastructure and integrating it with the electrical grid in a smart way and efficient [1,2].

The concept of a smart grid to transport energy at the user has emerged in recent years, creating a lot of discussion and controversy about structure, utility and flexibility technique [3]. At the same time was increased the pressure to governments. These served to increase the incentive for technological development and to try to incorporate significant levels of renewable energy sources. With their mass production and the ability to communicate with the power grid, the electric vehicles can be seen as the first "electric system" able to loading them in an intelligent way, and to test solutions and standards for future Smart Grid.

The concept of Smart Grid is qualitative because there are different types of implementation that have different levels of complexity [4]. In general, the standard implementations consist in the use of sensors and advanced communication technologies with the aim to give the end user a wide range of services currently not available [5-7].

Figure 1 shows an example of this type of network integrated with electric vehicles. It is the integration of technologies that they enable you to rethink the operation of the conventional electric network, to meet the following requirements. For example, detect problems before they impact on service; respond as quickly as possible to the input local communicate quickly, have an advanced centralized diagnostic system, provide a feedback control that brings the system quickly to a steady state after any interruption or disturbance of the network; adapt quickly to changing conditions of the system, reduce the environmental impact.

Figure 1. Example of Smart grid and Electric vehicles

The electric grid of the future will increasingly ensure standards in terms of reliability, safety, power, efficiency and reducing environmental impact. The consumer can become a producer and the network must be able not only to carry the electrical energy, but also to optimally manage the flows of energy and products required by end users.

From the above, it is evident the importance of having in the future a distribution network that allows to achieve these objectives, also in view of the spread of electric vehicles.

The intelligent charging also has the potential to double the battery life of the vehicles and coordinating the work of network management systems and the transmitted energy, with parameters defined by users/operators that can go autonomy, tariffs, particularly source energy and so on [8-13]. In this mode, electric vehicles would promote greater integration in the electricity grid, allowing bi-directional

978-1-4799-4749-2/14/$31.00 ©2014 IEEE

2014International Symposium on Power Electronics,Electrical Drives, Automation and Motion

1054

information flows between the various actors, thus allowing at large manufacturers to optimize their electricity generation, and small producers to sell locally in the network, their excess energy [14, 15]. The role of paper is to highlight the potentials that those technologies offer using in this case the integration of the photovoltaic systems and electric vehicles applied on University of Bergamo considering all Faculties (Dalmine, Bergamo and Upper Town). The work supposes possible scenarios for sustainable mobility and can take advantage of all the properties and the potentials offered by vehicles with electrical and photovoltaic technology, including energy efficiency and emissions reduction.

II. ELECTRIC ENERGY FOR INTELLIGENT MOBILITY There are many factors that electric mobility is able to take

advantage of and that would represent significant progress for a transportation management increasingly integrated with the needs of the city and more and more intelligent.

The advantages of an electric vehicle compared with a conventional thermal are varied, some of these are: • No toxic gas in atmosphere; • Global efficiency of higher energy, at least twice as many

vehicles with internal combustion engine, which partially compensates for the lack of energy stored on board;

• Pair of pull best suited for use in town for a high acceleration from standstill and low speed;

• No noise; • Maintenance almost complete. The first aspect to consider is that electric vehicles are powered by an energy carrier that can be produced from all sources of primary energy, in contrast to conventional vehicles that can make use of only one source of energy, i.e. the oil. In addition to the energy source, another new feature is the charging infrastructure that is completely different from that used for gasoline vehicles, but has the great advantage to lean to the electricity grid, which is already present almost everywhere. In this way, it is necessary to construct only the last part of the infrastructure, the charging station, so that the development of the network of charging has a relatively low cost and depends on the type of charging point that can be domestic, public, semi-public (offices, supermarkets). Among all the possible energy alternatives for road transport, electricity is the only one that proves to be prepared both from the infrastructure point of view, that from the point of view of stability of the price charging: electricity generation and distribution are in fact publicly regulated. Electric mobility can reduce and then stop the energy dependence of the transport sector in respect of the Petroleum Exporting Countries, replacing those imports with electricity generated within their own country in a relatively short time horizon.

III. DESCRIPTION OF CAMPUS The University of Bergamo is located in Lombardy, a region in Northern Italy with more than 10 million inhabitants and one of the regions with the highest GDP pro capita in Europe. The University of Bergamo has about 16,000 students (undergraduates and graduates), and more than 300 PhD students. The number of students is increasing each year, with

a 7% growth rate per year between 2001 and 2011. A staff of 656 members (331 professors & researchers, 95 assisting academic staff, 230 administrative and technical staff) provides a dynamic scientific and teaching environment open to innovations. The six Departments and the Research centers of the University of Bergamo are strictly intertwined in the town life. They are grouped in three campuses located in three different areas: Faculty of Economics and Law in the City of Bergamo, Faculty of Humanities in the Mediaeval Upper town and Faculty of Engineering in Dalmine where at 400 m there is the University Sport Centre (USC). Figure 2 shows a map of the location of the different zones.

Figure 2. Location of the different Faculty

The distances are relative from Dalmine (Faculty of Engineering) to Bergamo for the different Campus, respectively Humanities, Law, Economics. The Table I indicates the number of km necessary to arrive at another location of the Campus. In fact, the paths are relative only for the connections between the faculties. This information is necessary to provide a calculation that relates the autonomy of electric vehicles in terms of consumption and distance covered.

TABLE I. DISTANCE BETWEEN DIFFERENT FACULTIES

Distance [km] Distance

[km]

Dalmine - Sant'Agostino 12.8 Caniana – Sant'Agostino 3.4

Dalmine - Salvecchio 12.8 Caniana - Salvecchio 4.8

Dalmine - Rosate 13.1 Caniana - Rosate 4.7

Dalmine – Pignolo 11.4 Caniana – Pignolo 2.3

Dalmine Caniana 8.3 Caniana - Dalmine 8.3

1055

IV. PHOTOVOLTAIC SYSTEMS INSTALLED Since a photovoltaic system improves the environment in

which we live by helping to reduce the use of fossil fuels, and then bring down the production of CO2, the university has installed to become greener on two of its buildings two photovoltaic systems. The first is located in Dalmine on the building of the University Sports Centre (USC) and the second on the building of Bergamo, Faculty of Economics and Law.

Both PV systems are with crystalline silicon cells, tilt angle is equal to 15° and Azimuth value is 30°. The first system (USC-Dalmine) has installed a power of 100 kWp, whose data of the system are: Power of the system: 102,120 kWp; Energy Production for year: 96.095 kWh (941 kWh/kWp); CO2 abatement: about 67,3 ton/year; Year of start activity: 20/05/2011. On the building of the Faculty of Economics and Law (PV system-Bergamo) was installed a photovoltaic power systems of about 142 kWp installed on the 30th of November 2012. The data of the production of energy of these systems are shown in Figure 3. Of course, for the system of Bergamo, the prodaction of energy in the year 2012 is low due to the commissioning service at end of the year. For this study, therefore, is been considered for USC-Dalmine the average production which is equal to 96.09 MWh, whereas for PV system-Bergamo is been considered the production of 2013 which is equal to 129.1 MWh.

Figure 3. Production of Energy of the different PV systems

The idea to sustainable and intelligent mobility integrated at the University of Bergamo is not only a mechanism that connect the structures each other, but it is also the ability to offer a variety of other services. This opportunity can be created and delivered through the use of electric vehicles.

V. CASE OF STUDY: DIFFERENT SCENARIOS

The central role in sustainable mobility is offered by the use of electric vehicles. Electric vehicles have more efficiency in terms of energy with respect to almost all internal combustion engines. A gasoline engine has an efficiency of 25 - 28%, a diesel approaching to 40%, while an induction electric motor in alternating current has an efficiency of 90%, along with other facts that it does not produce exhaust fumes, or gas emissions and generate virtually zero pollution if supplied with energy from renewable sources. In this work, we have supposed to use

three types of electric vehicle, in particular cars, scooter and bicycle and they recharge with the energy product of the system installed on the building, in one case USC-Dalmine and another case with PV system-Bergamo.

The electric vehicles (Figure 4) have different characteristics that they are: • E-car: This vehicle can drive for 140-185 km; the battery

capacity can be in range of 20 kWh and tipically the traction power is 60 kW. Typical maximum speed is 150 km/h and the number of seats is between 2 and 5. Consumption is about 0.13 kWh/km with driven range is equal to 175 km..

• E-Scooter: This vehicle can drive for 40-150 km; the battery capacity can be in range of 3.75 kWh andtipically the traction power is in range of 0.5-130 kW. Typical maximum speed is 45-220 km/h and the number of seats is equal to 2. Consumption is about 0.06 kWh/km with driven range is equal to 60 km.

• E-Bicycle: This vehicle can drive for 40 km; the battery capacity can be in range of 0.36 kWh and tipically the traction power is in range of 250/350/500 W. Typical maximum speed is 150 km/h and the number of seats is between 2 and 5. Consumption is about 0.009 kWh/km.

Figure 4. Different type of electric vehicles

In order to employ these vehicles and make sure that their impact of CO2 is equivalent to zero, it is necessary to take advantage of the energy produced by photovoltaic (PV system and UCS-Dalmine-Bergamo). They have made several assumptions of energy use: • First scenario: All the energy produced (100%) by the

photovoltaic system (both UCS-Dalmine and PV system-Bergamo) must recharge in one case only electric cars,or only scooters or finally only to recharge bicycles. But this hypothesis is not real, because it is very strange that all energy producted both only used for recharge and not for another scopes.

• Second Scenario: The energy generated by the photovoltaic system (both UCS-Dalmine and PV system-Bergamo), 50% is used to recharge electric cars, the remaining 25% is used to recharge bicycles and the residual 25% is used for the scooter.

• Third Scenario: The energy generated by the photovoltaic system is divided in this mode: for UCS-Dalmine considering that this is a sports center, the 50% of the production is used to feed the structure of the building and

1056

the remaining 50% is divided in turn by 35% for recharging of electric cars, 5% for recharging the bicycle and for the remaining 15% for the scooter. While the energy generated by the PV system-Bergamo at the Faculty of Economics is for 50% is used to recharge electric cars, the remaining 25% is used to recharge bicycles and the residual 25% is used for the scooter.

• Fourth Scenario: The energy generated by the photovoltaic system is divided in this mode: for UCS-Dalmine considering that this is a sports center, the 70% of the production is used to feed the structure of the building and the remaining 30% is divided in turn by 20% for recharging of electric cars, 5% for recharging the bicycle and for the remaining 5% for the scooter. While the energy generated by the PV system-Bergamo is used to feed the structure of the building for 50%, the remaining 50% is divided in turn by 35% for recharging electric cars, charging 5% for bicycles and the remaining 15% for the scooter .

Assuming a path that connects all the main sites of the University of Bergamo, with its starting point at the UCS, the total kilometers that a generic electric vehicle should cover would be equal to 33 km. This distance is quite affordable considering the use of the vehicles listed beforehand.

VI. DISCUSSION OF RESULTS

Figure 4 shows different scenarios utilizing different percentage for the energy production of PV system installed respectively on the building in Dalmine and another building in Bergamo.

Figure 5. Different scenarios with trips for day with the use of different

electric vehicles

Those graphs allow us to point out that the production that we are considering, in the first scenario where for both the PV systems (USC-Dalmine and Bergamo) they used all energy (100%), respectivelly for 96.095 kWh (Dalmine) and 129.101,2 (Bergamo) for recharge the single vehicle. In this case, it can allow to recharge with the energy of USC: 22400 times/year a car, 48533 times/year a scooter and 323552 times/year bicycle. While with the energy of Bergamo it is possibile to recharge: 30094 times/year a car, 65203 times/year a scooter and 434684 times/year bicycle. But this scenario is not real. It is important to consider an use better of the production of the photovoltaic system. The fourth scenario, infact is more reale. In this case, it can allow to recharge with the energy of USC: 4480 times/year a car, 2427 times/year a scooter and 16178 times/year bicycle. While with the energy of Bergamo it is possibile to recharge: 10533 times/year a car, 9780 times/year a scooter and 21734 times/year bicycle. Figure 6 shows CO2 emission at day using vehicles not electrics. The values represents the emission of CO2 to one single car and one scooter.

(a)

1057

(b)

(c)

(d)

Figure 6. CO2 emissions at day (a) First Scenario, (b) Second scenario, (c) Third Scenario and (d) Fourth Scenario

The evaluation of the emissions avoided of CO2 for each mobility transport per km traveled can be observed from the figure 7. In addition to emissions avoided for the production of the same amount of energy through the photovoltaic (62.7 ton per year). The analysis of the emissions avoided by the use of electric vehicles is concentrate only for cars and scooters because the bike does not generate.

(a)

(b)

(c)

(d)

Figure 7. CO2 emissions avoided at day (a) First Scenario, (b) Second scenario, (c) Third Scenario and (d) Fourth Scenario

What is evident from Figure 7 is that there is a high level of emission reductions over the use of non-electric vehicle. Considering the latter choice, which allows the different categories of vehicles to cover a certain distance based on their efficiency in terms of CO2 emissions avoided; we can appreciate how important electric mobility can be considered at the urban level in the period of one year. For example, in the case of fourth scenario that it use the energy producted of the photovoltaic system of USC, the CO2 emission avoided at year are equal to 19663 g CO2/km for car and 10651 g CO2/km, while using the photovoltaic system of Bergamo permits to avoid the CO2 emission fo 46228 g CO2/km for year for car and 42926 g CO2/km for scooter.

VII. CONCLUSION The scope of this work is been to study different scenarios

for sustainable mobility offering a green university campus. In this case, it exploits the synergy between different technologies, both for electric vehicle and photovoltaic system. Under various hypotheses, it was decided initially to allocate all of the energy produced by the photovoltaic system installed in the University Sports Centre (U.S.C.) of Bergamo University (Italy) to each category of electric vehicle such as

1058

buses, vans, cars, scooters and e-bikes already available on the European market.

What emerges from the analysis is the reduction of CO2 emissions avoided by using electric vehicles and PV systems. In particular, for the energy production on the building University Sport Centre (USC), the system has installed a power of 100 kWp which is in the order of 62.7 tons per year. The installation has been done to ensure better energy efficiency of the entire sports center (USC-Dalmine) and Faculty of Economics and Law in the City of Bergamo (PV system-Bergamo), which has a total consumption that is around 300,000 kWh for year. In conclusion from what has come out with a view to sustainable mobility and intelligent for the University of Bergamo, it can be said that allocating a variable percentage of the energy produced by the photovoltaic systems can create and offer services through its electric vehicles and charging points, to all categories of users.

The further work for this research will be to study the different electric vehicles, in particular in addition to E-cars, E-scooter and E-bicycles, the introduction the electric buses. They carry out the path between the different faculties (Dalmine, Bergamo and Upper Town) utilizing the photovoltaic systems present on the buildings, in particular University Sport Centre (USC) and Faculty of Economics and Law in the City of Bergamo. Particular attention will revolted also at CO2 emissions.

REFERENCES [1] G.C. Lazaroiu, M. Roscia, “Definition methodology for the smart cities

model”, Energy, vol. 47, no. 1, pp. 326–332, Nov. 2012. [2] M. Longo, M. Roscia, G.C. Lazaroiu, “Innovating Multi-Agent

Systems applied to Smart City”, Research Journal of Applied Sciences, Engineering and Technology, 7(20) May 2014

[3] P. Zhang , L. Fangxing, N. Bhatt. " Generation Monitoring, Analysis, and Control for the Future Smart Control Center". IEEE Trans. Smart Grid, vol. 1, no.2, pp. 186 – 192, Sept. 2010

[4] Z. Liu, F. Wen, and G. Ledwich, “Optimal planning of electric-vehicle charging stations in distribution systems,” IEEE Trans. Power Del., vol. 28, no. 1, pp. 102–110, Jan. 2013.

[5] S. Hong, M. Lee, C. Lee, S.-J. Lee. "Security challenges for customer domain in the Smart Grid", in: Proc. Int. Conf. on Advanced Power System Automation and Protection (APAP), vol. 3, 16-20 Oct. 2011. pp. 2299 – 2303, DOI: 10.1109/APAP.2011.6180811

[6] A. Singhal, R.P. Saxena. " Software models for Smart Grid", in: Proc. International Workshop Software Engineering for the Smart Grid (SE4SG), June 2012, pp. 42 – 45, DOI 10.1109/SE4SG.2012.6225717.

[7] J. DongLi, M. Xiaoli, S. XiaoHui. "Study on technology system of self-healing control in smart distribution grid", in: Proc. Int. Conf. Advanced Power System Automation and Protection (APAP), 16-20 Oct. 2011, pp. 26 – 30, DOI: 10.1109/APAP.2011.6180379.

[8] M. Brenna, F. Foiadelli, D. Zaninelli, “Integration of recharging infrastructures for electric vehicles in urban transportation system”, 2012 IEEE, International Conference and Exhibition (ENERGYCON), 10.1109/EnergyCon.2012.6347726, Publication Year: 2012 , Page(s): 1060 – 1064.

[9] M. Brenna, F. Foiadelli, M. Roscia, D. Zaninelli, “Synergy between renewable sources and electric vehicles for energy integration in distribution systems”, 2012 IEEE 15th International Conference on Harmonics and Quality of Power (ICHQP), Digital Object Identifier: 10.1109/ICHQP.2012.6381274, Publication Year: 2012 , Page(s): 865 – 869.

[10] E. Sortomme and K. Cheung, “Intelligent dispatch of electric vehicles performing vehicle-to-grid regulation,” in Proc. IEEE Int. Electric Vehicle Conf., 2012, pp. 1–6.

[11] F. Locment, M. Sechilariu, C. Forgez. "Electric vehicle charging system with PV Grid-connected configuration", in: Proc. IEEE Vehicle Power and Propulsion Conference (VPPC), 1-3 Sept. 2010, pp. 1 – 6, DOI: 10.1109/VPPC.2010.5729016.

[12] I. Houssamo, F. Locment, M. Sechilariu. “Maximum power tracking for photovoltaic power system: Development and experimental comparison of two algorithms ”, Renewable Energy, vol. 35, no. 10, pp. 2381-2387, 2010.

[13] Y.-M. Wi, J.-U. Lee, S.-K. Joo, “Electric vehicle charging method for smart homes/buildings with a photovoltaic system”, IEEE Trans. on Consumer Electron., vol. 59, no. 2, pp. 323-328, May 2013.

[14] J. Huang, H. Wang, Y. Qian, C. Wang. "Priority-Based Traffic Scheduling and Utility Optimization for Cognitive Radio Communication Infrastructure-Based Smart Grid". IEEE Trans. Smart Grid, vol. 4, no. 1, Mar. 2013, pp. 78 – 86.

[15] X. Li, L. A. C. Lopes, and S. S. Williamson, “On the suitability of plug-in hybrid electric vehicle (PHEV) charging infrastructures based on wind and solar energy”, in: Proc. IEEE Power & Energy Society General Meeting, PES 2009.

1059