We study how renewable energy impacts regional infrastructures considering the full deployment of electric mobility at that scale. We use the Sardinia Island in Italy as a paradigmatic case study of a semi-closed system both by energy and mobility point of view. Human mobility patterns are estimated by means of census data listing the mobility dynamics of about 700,000 vehicles, the energy demand is estimated by modeling the charging behavior of electric vehicle owners. Here we show that current renewable energy production of Sardinia is able to sustain the commuter mobility even in the theoretical case of a full switch from internal combustion vehicles to electric ones. Centrality measures from network theory on the reconstructed network of commuter trips allows to identify the most important areas (hubs) involved in regional mobility. The analysis of the expected energy flows reveals long-range effects on infrastructures outside metropolitan areas and points out that the most relevant unbalances are caused by spatial segregation between production and consumption areas. Finally, results suggest the adoption of planning actions supporting the installation of renewable energy plants in areas mostly involved by the commuting mobility, avoiding spatial segregation between consumption and generation areas.
The
expected electrification of mobility is viewed as a great step in the
progressive increase of its sustainability. According to the
International Energy Agency, achieving the goal of maximum 2 degrees
increase in global temperature established by the Paris Agreement would
mean that approximately 19% of the GHG reduction should be attained
through the mitigation of transport emissions. In addition, as
urbanization will increase in the next years, electric mobility
especially in large urban areas like megacities will play a fundamental
role1.
In fact, in 2011 the world’s gasoline share for mobility in 27
megacities was about 9%, and this share is expected to increase further2,3. Consequently, an increase of GHG emissions and air pollution, as well as a growing dependency on fuel import is expected.
Use of alternative, environmentally friendly fuels and power trains are therefore a key strategy for heading towards sustainable transport systems, and, together with Electric Vehicles (EV), renewable energy sources are considered a further winning strategy to reduce the GHG emissions from cities. As the number of EV is expected to increase, given the potential high number of vehicles involved, a reliable planning and control of the charging infrastructure will be fundamental for its successful integration in the power system. In particular, a correct sizing of the needed resources, in term of electricity, charging stations, communication and management infrastructures must be based on the local mobility needs and on both the distribution infrastructures and electricity market constraints4. In fact, electricity infrastructures, for decades based on a hierarchical, fossil based model of production and distribution needs to be replaced out by a new, flexible model of generation and distribution whose solid grounds are based on renewable energy sources, integration, and decentralization. In addition, thanks to an increasing level of digitalization of infrastructures, the integration between distributed generation and electric mobility is of great benefit. If well planned, it can simultaneously contribute to emission reduction and to grid resilience due to the ability of electric vehicles to act as distributed storage for stabilizing the power fluctuations on distributed electricity systems5,6,7.
With regards to electric mobility initiatives, the existing literature8,9,10 primarily focuses on the evaluation of the impact of electrical mobility infrastructure on a metropolitan scale. This does not take into account the long range impacts on both the mobility infrastructure and the grid. In fact, high penetration of EV in densely populated areas could impact on the surrounding electricity transmission system, leading to systemic effects which are difficult to identify by limiting the analysis to the sole city boundaries.
In the present paper a multi-layered approach based on complex networks theory11,12,13 is presented. We study the co-existence of two different network infrastructural layers, energy and mobility, to estimate the impact of electric mobility on a regional scale, with the aim to quantify both short range and long range effects. The proposed methodology allowed to perform a scale analysis which takes into account a multi-layered infrastructure scheme of the problem. The proposed approach exploits census data regarding commuting to estimate the origin-destination matrix for the EV trips. Commuting is particularly important for EV mobility, because it it composed by short and medium range trips, which combines well with the limited ranges of EVs. Moreover, the proposed methodology relies on the map of solar and wind generation plants to identify the municipalities that are able to produce the low carbon electricity to support the mobility of EV on regional scale. Using these two different datasets, it is possible to estimate the energy need of charging services both on cities and on freeways, as well as the investigating of the possible integration with the local grid and renewable generation plants.
The proposed planning of electric mobility is performed on different scales, according to the availability of data (including census, the mobility network and the installed generation plants). It is arranged in three steps:
The methodology has been applied on one of the major islands of Italy, the region of Sardinia, considering a scenario of full deployment of electric vehicles to cover the need of commuting mobility on regional scale. Results show that the current RES production in Sardinia is able to cover the full deployment of electric mobility for commuting. Moreover, the network analysis of the regional commuting patterns shows that a limited number of municipalities behave as hubs of the regional traffic. Also, in the majority of cases the energy needs are negative in such areas, i.e. they need further power to sustain the recharge infrastructure. Finally, the optimization analysis of energy flows reveals both long range effects and spatial segregation phenomena affecting in the energy transmission system.
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Use of alternative, environmentally friendly fuels and power trains are therefore a key strategy for heading towards sustainable transport systems, and, together with Electric Vehicles (EV), renewable energy sources are considered a further winning strategy to reduce the GHG emissions from cities. As the number of EV is expected to increase, given the potential high number of vehicles involved, a reliable planning and control of the charging infrastructure will be fundamental for its successful integration in the power system. In particular, a correct sizing of the needed resources, in term of electricity, charging stations, communication and management infrastructures must be based on the local mobility needs and on both the distribution infrastructures and electricity market constraints4. In fact, electricity infrastructures, for decades based on a hierarchical, fossil based model of production and distribution needs to be replaced out by a new, flexible model of generation and distribution whose solid grounds are based on renewable energy sources, integration, and decentralization. In addition, thanks to an increasing level of digitalization of infrastructures, the integration between distributed generation and electric mobility is of great benefit. If well planned, it can simultaneously contribute to emission reduction and to grid resilience due to the ability of electric vehicles to act as distributed storage for stabilizing the power fluctuations on distributed electricity systems5,6,7.
With regards to electric mobility initiatives, the existing literature8,9,10 primarily focuses on the evaluation of the impact of electrical mobility infrastructure on a metropolitan scale. This does not take into account the long range impacts on both the mobility infrastructure and the grid. In fact, high penetration of EV in densely populated areas could impact on the surrounding electricity transmission system, leading to systemic effects which are difficult to identify by limiting the analysis to the sole city boundaries.
In the present paper a multi-layered approach based on complex networks theory11,12,13 is presented. We study the co-existence of two different network infrastructural layers, energy and mobility, to estimate the impact of electric mobility on a regional scale, with the aim to quantify both short range and long range effects. The proposed methodology allowed to perform a scale analysis which takes into account a multi-layered infrastructure scheme of the problem. The proposed approach exploits census data regarding commuting to estimate the origin-destination matrix for the EV trips. Commuting is particularly important for EV mobility, because it it composed by short and medium range trips, which combines well with the limited ranges of EVs. Moreover, the proposed methodology relies on the map of solar and wind generation plants to identify the municipalities that are able to produce the low carbon electricity to support the mobility of EV on regional scale. Using these two different datasets, it is possible to estimate the energy need of charging services both on cities and on freeways, as well as the investigating of the possible integration with the local grid and renewable generation plants.
The proposed planning of electric mobility is performed on different scales, according to the availability of data (including census, the mobility network and the installed generation plants). It is arranged in three steps:
-
Data collection and geo-referencing by means of Geographic Information Systems (GIS).
-
Definition of the complex system able to
describe the expected interaction between mobility and power grids. The
proposed approach also includes the estimation of the expected traffic
flows starting from census commuting data, integrated by the energy
description of EVs.
-
Identification of the interactions between the
layers of the system to quantify the impact of the energy needs of
mobility on the power grid of the territory, in terms of the associated
energy flows.
The methodology has been applied on one of the major islands of Italy, the region of Sardinia, considering a scenario of full deployment of electric vehicles to cover the need of commuting mobility on regional scale. Results show that the current RES production in Sardinia is able to cover the full deployment of electric mobility for commuting. Moreover, the network analysis of the regional commuting patterns shows that a limited number of municipalities behave as hubs of the regional traffic. Also, in the majority of cases the energy needs are negative in such areas, i.e. they need further power to sustain the recharge infrastructure. Finally, the optimization analysis of energy flows reveals both long range effects and spatial segregation phenomena affecting in the energy transmission system.
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