177 research outputs found
Automazione dei Sistemi Elettrici di Trasporto: Il nuovo presente dei veicoli nel trasporto pubblico e privato
No full textPreliminary analysis for the design of an energy-efficient and environmental sustainable integrated mobility system
No full textThe paper presents a new proposal for the design of a sustainable urban mobility system. Starting from an overview on the worldwide existing solutions and on the future trend, an innovative idea regarding the integration of two urban mobility systems is proposed: a metro transit system in underground and an electric and hybrid vehicles transport system on surface. The integration is aimed at the reduction of energy consumptions and environmental impact and at the optimization of the service thanks to the maximization of the transport bid in time. Moreover the proposed solution guarantees the minimum economic impact as a result of the optimization of the logistic and technological application of the existing electric power plant. The main results about the preliminary energy analysis, that is the basis of the project, are reported
Compatibility of Present 3 kV DC and 2×25 kV AC High-Speed Railway Power Supply Systems towards Future MVDC System
No full textIn recent years, due to the limitations and disadvantages of conventional DC and AC railway power supply systems (RPSS) the idea of reinforcing and replacing these systems with a more advanced and developed MVDC based system has become more prominent. The high power capability of these alternative systems together with convenient integration of distributed energy resources are the outstanding features which highlight their potential. In this paper, the adaptability of current Italian high-speed RPSS including 3 kV DC and 2×25 kV AC with new MVDC RPSS in terms of the configuration of traction power substations (TPSS), OCS structures, voltage drops, and rolling stocks has been addressed and interface power electronic-based converters are suggested
Infrastructuring of canadian transport using hydrogen from res: Comparison between BEV and FCV
No full textAn increase in electricity production from Renewable Energy Sources (RES) requires a consequent reinforcement of the transmission and distribution grids to deliver the energy towards the end-users. Since this has a great economic impact, a possible solution is the hydrogen production to be converted in electricity through fuel cells. This process has a low efficiency, but can be suitable for transportation, both for railway and road applications.This paper aims to compare the energy efficiency of the hydrogen applied directly in a fuel cell vehicle (FCV) or converted in electricity for a fast charge of a battery electric vehicle (BEV) in long distance journeys
Utilization of E-Bus Applied to Urban Lines
No full textElectricity instead of oil for vehicle propulsion will contribute to achieve the European Union targets on CO2 emissions reduction. So, in this paper, the performance of a full electric bus on a fixed route in the city of Milan is analyzed. In particular the study compares the performances of a conventional fuel and an electric bus from the point of view of the energy consumption, charging strategy and avoided harmful emissions. The analysis presented shows that significant benefits can be achieved by employing an electric bus instead of a diesel one, especially in terms of avoided harmful emissions
Assessing impact of PV systems on centralised generation
No full textIn response to climate change concerns, most of the industrialized countries have committed in recent years to increase their share of Renewable Energy Sources (RES), in order to reduce greenhouse gas emissions. Therefore, the rapid deployment of small-scale photovoltaic (PV) systems, mainly in residential applications, is starting to represent a considerable portion of the available electrical power generation and, for this reason the stochastic and intermittent nature of these systems is impacting on the operation of centralized resources. Network operators are constantly changing their approach to both short-term and long-term forecasting activities due to the higher complexity of the scenario in which more and more stakeholders have active roles in the network. The scope of this paper is to create a model to evaluate the impact of generation from aggregated rooftop PV systems along with a model to simulate future contributions. The model is developed in MATLAB and the methodology used is based on statistical assumptions concerning the available details about PV systems installed
Dual-loop generalized predictive control method for two-phase three-wire railway active power quality controller
No full textOne of the most challenging topics in electric railway networks (ERNs) is power quality (PQ) problems caused by single-phase feeding of time-varying and high-power locomotives. During previous years, many techniques and compensators have been offered to alleviate these problems. Railway active power quality controller (RAPQC) is considered as one of the most efficient approaches. Due to the time-variant, uncertainty and distorted features of ERNs, the controlling of RAPQCs has always been a substantial concern to experts. This paper presents, a new robust control system for two-phase three-wire RAPQC (ThRAPQC) based on generalized model predictive control integrated with modified instantaneous reactive power theory (GMPC-MIRP). A dual-loop balancing system has been adopted in the proposed control system to equalize the active powers of traction power substation (TPSS) adjacent feeders, compensate reactive powers and suppress harmonic simultaneously. The performance of the proposed method in comparison with the conventional Fryze-Buchholz-Depenbrock (FBD)-based current strategy together with hysteresis current controller (FBD-HCC) has been evaluated through the detailed simulations and Opal-RT 5600-based laboratory setup results. The fast response, high precision, lower fluctuation in reference current tracking and high capability of working in distorted conditions are the outstanding privileges of the proposed method that are confirmed by the output results
Monte Carlo BEV Users Simulation to Assess the Charging Stations Usage in Highway
No full textCar electrification is necessary to reduce Green-house Gasses(GHGs). Italy is behind the European Union average by both vehicle and charging infrastructure spread. The infrastructure planning needs to keep up with the expected growth of Electric Vehicles (EVs). This paper proposes a model based on Monte Carlo simulation of user charging behavior. The model tries to solve the dimensioning problem from the perspective of the policymaker in a high-demand scenario. It allows the assessment of the minimum number of charging ports for a specific service level. The case study of Al Milan-Bologna, an important highway section in Italy is shown
The Evolution of Railway Power Supply Systems Toward Smart Microgrids: The concept of the energy hub and integration of distributed energy resources
No full textIn recent years, the achievement of sustainable energy systems has become one of the foremost challenges of experts around the world. In this context, the reduction of energy consumption while providing optimum power flow to the end users is a substantial challenge in various fields of generation, transmission, and distribution. Environmental concerns like global greenhouse gas emissions and other problems related to fossil fuels, together with deficiency of resources, are other significant aspects
A-day-ahead photovoltaic power prediction based on long short term memory algorithm
No full textIn recent years, Photovoltaic System (PV) have been installed in parking lots in order to provide the green energy to Electric vehicles (EVs). Energy Synchronizing between PV generations and EVs demand is a function of different variables, and it is very challenging. Having an accurate prediction of PV generation helps to ease the complexity of this problem. Although various Machine Learning (ML) techniques have been applied and resulted well, traditional ML approaches need years of history of PV generations to make an accurate prediction. In many cases, parking lots or the houses recently equipped by PV panels, and this information is not available. Therefore, the primary motivation of this work is to build a reliable deep learning forecasting model based on Long Short Term Memory (LSTM) architecture in order to make a short-term prediction based on the limited previous observation. The proposed model is applied to a month of the PV power generation data and resulted in the promising accuracy with the Mean Absolute Percentage Error (MAPE) value of 0.028
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