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IEEE MELECON 2020
MELECON 2020 - 1.1

Technical Session

IEEE Mediterranean Eletrotechnical Conference 2020

IEEE MELECON 2020

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Session 1.1 - Electric vehicle transportation systems and their environmental impact, charging infrastructure and grid integration

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PRESENTATIONS
SESSION DETAILS

From electric mobility to hydrogen mobility: current state and possible future expansions

Gabriella Di Filippo - University of Palermo, Italy

PREVIEW e-BADGE PRESENTATION

From electric mobility to hydrogen mobility: current state and possible future expansions

ABSTRACT

The expansion of electric vehicles in Italy, has already started a few years ago, but some aspects prevent its expansion. Currently users prefer hybrid technology, mainly due to socio-economic factors related to initial investment and anxiety about autonomy. The aim of the document is to understand if the adoption of Fuel Cell technology can be a solution to overcome the problems of environmental pollution. The possibility to be able to use fuel cells to store electricity is very advantageous, especially on charging times that are significantly reduced. Based on the current situation and analyzing the available data, this work reports the current state of electric mobility in Italy and tries to provide forecasts to understand in which cities the Fuel Cell charging infrastructure should be more favorable.

Acoustic Impact of Electric Vehicles

Paolo Briante - University Mediterranea of Reggio Calabria, Italy

PREVIEW e-BADGE PRESENTATION

Acoustic Impact of Electric Vehicles

ABSTRACT

Electric vehicles (EV) diffusion depends on many factors among which policies, people options, and economic factors. Their noise-related performance could appear favourable. This notwithstanding, despite partisan opinions, the analyses carried out suggest that research and industry will have to minimise the collateral issues posed by a quite probable EV diffusion. The objective of the study presented in this paper is to analyse the acoustic impact of electric vehicles (EV) and to set up an overall framework for an effective management of their diffusion. After the objectives, EV overall characteristics are analysed. EV acoustic performance are then analysed. In the final discussion, the main characteristics of the required holistic approach are highlighted. This can benefit both researchers and practitioners.

Selective harmonic mitigation with asymmetrical staircase voltage waveform for a three-phase fivelevel Cascaded H-Bridge Inverter

Giuseppe Schettino - University of Studies of Palermo, Italy

PREVIEW e-BADGE PRESENTATION

Selective harmonic mitigation with asymmetrical staircase voltage waveform for a three-phase fivelevel Cascaded H-Bridge Inverter

ABSTRACT

Selective harmonics elimination or mitigation strategies are used in all applications where it is necessary to rise the efficiency and reliability of the overall system. This paper presents a simple approach to reduce the low order harmonics amplitude of an asymmetrical staircase voltage waveform for a five-level, three-phase Cascaded H-Bridge Inverter without solving non-linear equations. Through this simple approach, polynomial equations to evaluate the control angels in real-time operations have been found. The effectiveness of the harmonic mitigation method has been tested through the simulation analysis in MatLab/PLECS environment.

Cost-benefit analysis for multiple agents considering an electric vehicle charging/discharging strategy and grid integration

Mahsa Bagheri Tookanlou - Northumbria University, United Kingdom

PREVIEW e-BADGE PRESENTATION

Cost-benefit analysis for multiple agents considering an electric vehicle charging/discharging strategy and grid integration

ABSTRACT

An increasing number of electric vehicles (EVs) will be charged/discharged in EV charging stations (EVCSs) in distribution systems. Grid-2-vehicle (G2V) and vehicle-2- grid (V2G) operation of EVs are economically and technically rewarding only when an optimal G2V/V2G strategy is properly developed. In this study, a scheduling scheme is developed which mainly focus on guaranteeing the rewards of all agents (e.g EVs, EVCSs, and electricity suppliers (ESs)) participating in V2G and G2V operation. Based on the proposed strategy, EVs independently plan their charging/discharging depending on the shortest driving route and cost/benefit offered by EVCSs. Furthermore, each EVCS finds the best ES to purchase electricity from the wholesale market. The benefits of all agents in EV’s V2G and G2V operation are taken into account by formulating three optimization problems. Each problem belongs to each agent. To implement the proposed strategy, a cloud scheduling system is operated to collect required information from all agents, solve the optimization problems, and ultimately send the results to relevant agents. Optimal hourly electricity prices are determined for the three agents. For simulation purposes, nine EVCSs and three ESs are facilitated for charging/discharging of EVs to visualize and validate the modeling results. The results show that by implementing the proposed strategy, the cost of EVs decreases by 18%, and the revenues of EVCSs and ESs are raised by 21% and 23%, respectively, compared to the case in which EVs do not use the proposed strategy in EV’s V2G and G2V operation.

Modeling of Magnetorheological Fluids Relative Magnetic Permeability by using a Neural Network approach

Grazia Lo Sciuto - Università degli Studi di Catania, Italy

PREVIEW e-BADGE PRESENTATION

Modeling of Magnetorheological Fluids Relative Magnetic Permeability by using a Neural Network approach

ABSTRACT

In this paper, starting from the experimental data obtained with an empirical measurement device developed for this purpose, it has been determined a simple and accurate model (based on a small number of parameters) that allows to represent the relative magnetic permeability of the magnetorheological fluids as a function of the magnetic field in which it is immersed in. The model thus obtained is in excellent agreement with the experimental data. In fact the obtained error is approximately of 8%.

Outlier Removal for Improving the Accuracy of Electric Vehicle Behavior Prediction

Kunihiro Miyazaki - The University of Tokyo, Japan

PREVIEW e-BADGE PRESENTATION

Outlier Removal for Improving the Accuracy of Electric Vehicle Behavior Prediction

ABSTRACT

The concept of supplying electric power from an electric vehicle (EV) to a power system is called Vehicle to Grid (V2G). It is expected to bring about improvement in stability of the grid. As the demand for renewable energy rises in recent years, the stability of the power grid is simultaneously gathering more attention. It is important to predict EV behavior in V2G systems because if the behavior of EVs can be predicted in advance, it enables us to establish an efficient plan of power distribution. However, the irregular behavior of EVs makes prediction difficult. Prediction of EV cars is performed by extracting patterns from past actions, where unusual sudden actions hinder learning of the prediction model and cause a decrease in prediction accuracy. Therefore, to analyze and remove the irregularity of EVs are necessary in order to stabilize the V2G system. In this paper, we analyzed the behavior of EVs using realworld State of Charge (SoC) data. Then, using the technology of outlier removal, we excluded the irregular behaviors from a dataset. Finally, we attempted improvement of prediction accuracy by using the data without the irregularities. As a result, we successfully improved the accuracy of the prediction of EV behaviors. Also, in the process of behavior prediction, we performed a comprehensive analysis of EV SoC data, and introduced the results.

SESSION CHAIRS

Rosa Anna Mastromauro

University of Firenze, Italy

e-BADGE

Elena Breaz

UBTM, France

e-BADGE

Technical Session

IEEE Mediterranean Eletrotechnical Conference 2020

IEEE MELECON 2020

Session 1.1 - Electric vehicle transportation systems and their environmental impact, charging infrastructure and grid integration

From electric mobility to hydrogen mobility: current state and possible future expansions

Acoustic Impact of Electric Vehicles

Selective harmonic mitigation with asymmetrical staircase voltage waveform for a three-phase fivelevel Cascaded H-Bridge Inverter

Cost-benefit analysis for multiple agents considering an electric vehicle charging/discharging strategy and grid integration

Modeling of Magnetorheological Fluids Relative Magnetic Permeability by using a Neural Network approach

Outlier Removal for Improving the Accuracy of Electric Vehicle Behavior Prediction

SESSION CHAIRS

Rosa Anna Mastromauro

Elena Breaz