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The diffusion of electric vehicles (EVs) can be sustained by the presence of integrated solutions offering parking and clean power supply. The recourse to DC systems allows better integration of EV bidirectional energy exchange, photovoltaic panels, and energy storage. In this paper, a methodology for optimal techno-economic sizing of a DC-microgrid for covering EV mobility needs is carried out. It is based on the definition of different scenarios of operation, according to typical EV usage outlooks and environmental conditions. In each scenario, optimal operation is carried out by means of a specific approach for EV commitment on different stations. The sizing procedure is able to handle the modular structure of microgrid devices. The proposed approach is applied to a case study of an envisaged EV service fleet for the Bari port authority.

In this paper we argue for the need to apply a cognitive approach to understand deep dynamics and determinants of technological evolutions. After examining main contributions from innovation studies to the conceptualization of innovation and change in complex socio-technical environments, we highlight the contribution coming from the application of the cognitive approach to evolutionary studies on technologies and we introduce the concept of technological memory as an interpretative tool to understand those changes. We discuss our hypothesis with reference to several observations carried out in different local contexts – Mexico, India and Italy – in relation to technological change in the water sector. In those cases deliberate attempts to substitute traditional technologies with modern ones led to interesting trajectories of change ranging from the collapse of old technologies to the development of multifaceted hybridization patterns. Tema. Journal of Land Use, Mobility and Environment, 2014: INPUT 2014 - Smart City: planning for energy, transportation and sustainability of the urban system

Stone pavements are the historical, architectural, and cultural heritage of lots of cities in Italy and the world. Road managers should be able to make decisions on the global conditions to define the most suitable strategies and maintenance interventions for every type of pavement. There are no standard monitoring methods or criteria for evaluating stone pavement performance. These pavements have more uneven surfaces than traditional pavements, but this characteristic could be accepted if type of vehicles and relative travel conditions are considered. Therefore, it is useful to define criteria for assessing roughness considering the comfort experienced by users in different vehicles. In this research, both traditional and innovative methodologies for assessing irregularities have been investigated using true stone surface profiles. In this regard, traditional performance indicators such as the International Roughness Index (IRI) defined by the ASTM E1926, the ISO 8608 classification, and the frequency-weighted vertical acceleration (awz) provided by ISO 2631-1 for comfort assessment have been considered. In the case of comfort assessment, three dynamic vehicle models (bike, automobile, and bus) have been adopted. Finally, this two-part paper also proposes an innovative straightedge analysis for stone pavements (SASP) to evaluate the effect on traffic of both pavement profile roughness and localized irregularities. In this way, the authors aim to provide an effective tool to monitor stone pavements.

The aim of this investigation is the analysis of the opportunity introduced by the use of railway infrastructures for the power supply of fast charging stations located in highways. Actually, long highways are often located far from urban areas and electrical infrastructure, therefore the installations of high power charging areas can be difficult. Specifically, the aim of this investigation is the analysis of the opportunity introduced by the use of railway infrastructures for the power supply of fast charging stations located in highways. Specifically, this work concentrates on fast-charging electric cars in motorway service areas by using high-speed lines for supplying the required power. Economic, security, safety and environmental pressures are motivating and pushing countries around the globe to electrify transportation, which currently accounts for a significant amount, above 70 percent of total oil demand. Electric cars require fast-charging station networks to allowing owners to rapidly charge their batteries when they drive relatively long routes. In other words, this means about the infrastructure towards building charging stations in motorway service areas and addressing the problem of finding solutions for suitable electric power sources. A possible and promising solution is proposed in the study that involves using the high-speed railway line, because it allows not only powering a high load but also it can be located relatively near the motorway itself. This paper presents a detailed investigation on the modelling and simulation of a 2 × 25 kV system to feed the railway. A model has been developed and implemented using the SimPower systems tool in MATLAB/Simulink to simulate the railway itself. Then, the model has been applied to simulate the battery charger and the system as a whole in two successive steps. The results showed that the concept could work in a real situation. Nonetheless if more than twenty 100 kW charging bays are required in each direction or if the line topology is changed for whatever reason, it cannot be guaranteed that the railway system will be able to deliver the additional power that is necessary.

The diffusion of Electric Vehicles (EV) fostered by the evolution of the power system towards the new concept of Smart Grid introduces several technological challenges related to the synergy among electricity-propelled vehicle fleets and the energy grid ecosystem. EVs promise to reduce carbon emissions by exploiting Renewable Energy Sources (RESes) for battery recharge, and could potentially serve as storage bank to flatten the fluctuations of power generation caused by the intermittent nature of RESes by relying on a load aggregator, which intelligently schedules the battery charge/discharge of a fleet of vehicles according to the users’ requests and grid’s needs. However, the introduction of such vehicle-to-grid (V2G) infrastructure rises also privacy concerns: plugging the vehicles in the recharging infrastructures may expose private information regarding the user’s locations and travelling habits. Therefore, this paper proposes a privacy-preserving V2G infrastructure which does not disclose to the aggregator the current battery charge level, the amount of refilled energy, nor the time periods in which the vehicles are actually plugged in. The communication protocol relies on the Shamir Secret Sharing threshold cryptosystem. We evaluate the security properties of our solution and compare its performance to the optimal scheduling achievable by means of an Integer Linear Program (ILP) aimed at maximizing the ratio of the amount of charged/discharged energy to/from the EV’s batteries to the grid power availability/request. This way, we quantify the reduction in the effectiveness of the scheduling strategy due to the preservation of data privacy.

This Round Robin Test program aims to establish the influence of the combined wave and current effect on the power capture and performance of a generic tidal turbine prototype. Three facilities offering similar range of experimental conditions have been selected on the basis that their dimensions along with the rotor diameter of the turbine translate into low blockage ratio conditions. The performance of the turbine shows differences between the facilities up to 25% in terms of average power coefficient, depending on the wave and current cases. To prevent the flow velocity increasing these differences, the turbine performance coefficients have been systematically normalized using a time-average disc-integrated velocity, accounting for vertical gradients over the turbine swept area. Differences linked to blockage effects and turbulence characteristics between facilities are both responsible for 5 to 10% of the power coefficient gaps. The intrinsic differences between the tanks play a significant role as well. A first attempt is given to show how the wave-current interaction effects can be responsible for differences in the turbine performance. In these tanks, the simultaneous generation of wave and current is a key part often producing disruptions in both of these flow characteristics.

One of the most encouraging sorts of renewable energy is ocean wave energy. In spite of a large number of investigations in this field during the last decade, wave energy technologies are recognised as neither mature nor broadly commercialised compared to other renewable energy technologies. In this paper, we develop and optimise Power Take-off (PTO) configurations of a well-known wave energy converter (WEC) called a point absorber. This WEC is a fully submerged buoy with three tethers, which was proposed and developed by Carnegie Clean Energy Company in Australia. Optimising the WEC’s PTO parameters is a challenging engineering problem due to the high dimensionality and complexity of the search space. This research compares the performance of five state-of-the-art metaheuristics (including Covariance Matrix Adaptation Evolution Strategy, Gray Wolf optimiser, Harris Hawks optimisation, and Grasshopper Optimisation Algorithm) based on the real wave scenario in Sydney sea state. The experimental achievements show that the Multiverse optimisation (MVO) algorithm performs better than the other metaheuristics applied in this work.