Sensitivity Analysis of a Bidirectional Wireless Charger for EV

Bidirectional chargers are required to fully integrate Electric Vehicle (EV) into the smart grids. Additionally, wireless chargers ease the charge/discharge process of the EV batteries so that they are becoming more popular to fulfill a V2G scenario. When considering the load of wireless chargers, it is a requirement to know the real output power that these systems offer. The designed output power may differ from the real one as components suffer from tolerance. This paper defines six sensitivity factors to model the severity of the effects of tolerance into the output power. To do so, an electric circuit analysis is used and a mathematical formulation is derived. The six sensitivity factors are computed for a laboratory prototype.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Electric Vehicles Integrated with Renewable Energy Sources for Sustainable Mobility

Across the globe, governments have been tackling the concerning problem of air-polluting emissions by committing significant resources to improving air quality. Achieving the goal of air purification will require that both the private and public sectors invest in clean energy technology. It will also need a transition from conventional houses to smart houses and from conventional vehicles to electric vehicles (EVs). It will be necessary to integrate renewable energy sources (RESs) such as solar photovoltaics, wind energy systems and diverse varieties of bioenergies. In addition, there are opportunities for decarbonisation within the transportation sector itself. Paradoxically, it appears that the same transportation sector might also present an opportunity for a speedy decarbonisation. Statistics indicate that transportation is responsible for 14% of global greenhouse gas (GHG) emissions. However, there are numerous options for viable clean technology, including the plug-in electric vehicles (PEVs). There are indeed many technologies and strategies, which reduce transportation emissions such as public transportation, vehicle light weighing, start-stop trains, improved engine technology, fuel substitution and production improvement, hydrogen, power-to-gas, and natural gas heavy fleets. This work concentrates on EV adoption integrated with RES. Specifically, this chapter examines the feasibility of significantly reducing GHG emissions by integrating EVs with RESs for sustainable mobility

simulation and optimisation study of the integration of distributed generation and electric vehicles in smart residential district

This paper presents an optimisation methodology for simulating the integration of distributed generation and electric vehicles (EVs) in a residential district. A model of a smart residential district is proposed. Different charging scenarios (CS) for private cars are considered for simulating different power demand distributions during the day. Four different case studies are investigated, namely the Base Case, in which no EVs are present in the district and three study cases with different CSs. A global optimisation method based on a genetic algorithm approach was applied on the model to find the total power from PV panels installed and co-generative micro gas turbines while minimising the annual energy cost in the district for the four different scenarios. In conclusion, the results showed that the use of EVs in the district introduces considerable savings with respect to the Base Case. Moreover, the impact of the chosen CS is nearly insignificant under a purely economic perspective even if it is relevant for grid management. Additionally, the optimum amounts of installed power vary in a limited range if the distance travelled by EVs, users' departure and arrival time change broadly

Electric Vehicles Charging Technology Review and Optimal Size Estimation

AbstractMany different types of electric vehicle (EV) charging technologies are described in literature and implemented in practical applications. This paper presents an overview of the existing and proposed EV charging technologies in terms of converter topologies, power levels, power flow directions and charging control strategies. An overview of the main charging methods is presented as well, particularly the goal is to highlight an effective and fast charging technique for lithium ions batteries concerning prolonging cell cycle life and retaining high charging efficiency. Once presented the main important aspects of charging technologies and strategies, in the last part of this paper, through the use of genetic algorithm, the optimal size of the charging systems is estimated and, on the base of a sensitive analysis, the possible future trends in this field are finally valued

Innovative Energy Approach for Design and Sizing of Electric Vehicle Charging Infrastructure

In Italy, the availability of service areas (SAs) equipped with charging stations (CSs) for electric vehicles (EVs) on highways is limited in comparison to the total number of service areas. The scope of this work is to create a prototype and show a different approach to assessing the number of inlets required on highways. The proposed method estimates the energy requirements for the future electric fleet on highways. It is based on an energy conversion that starts with the fuel sold in the highway network and ends with the number of charging inlets. A proposed benchmark method estimates energy requirements for the electric fleet using consolidated values and statistics about refueling attitudes, with factors for range correction and winter conditions. The results depend on assumptions about future car distribution, with varying numbers of required inlets. The analysis revealed that vehicle traffic is a critical factor in determining the number of required charging inlets, with significant variance between different SAs. This study highlights the necessity of incorporating factors like weather, car charging power, and the future EV range into these estimations. The findings are useful for planning EV charging infrastructure, especially along major traffic routes and in urban areas with high-range vehicles relying on High-Power DC (HPDC) charging. The model’s applicability to urban scenarios can be improved by considering the proportion of energy recharged at the destination. A key limitation is the lack of detailed origin–destination (OD) highway data, leading to some uncertainty in the calculated range ratio coefficient and underscoring the need for future research to refine this model

numerical simulation analysis of the impact of photovoltaic systems and energy storage technologies on centralised generation a case study for australia

In response to climate change concerns, most of the industrialised countries have committed in recent years to increase their share of Renewable Energy Sources 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 are affecting the operation of centralised generation (CG) 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. An increasing number of customers must be treated as prosumers and no longer only as consumers. In this context, storage technologies are considered the suitable solution. These can be necessary in order to solve and fill the problems of the renewable distributed sources are introducing in the management of the network infrastructure. The aim of this work was to create a model in order to evaluate the impact of power generation considering PV systems in Australia along with a model to simulate Battery Energy Storage Systems (BESSs) and Electric Vehicles future contributions using MATLAB. The methodology used to develop these models was based on statistical assumptions concerning the available details about PV systems installed and current storage technologies. It has been shown that in all the scenarios analysed, the future adoption of rooftop PV panels and impact on the CG is incredibly higher than the uptake of energy storage systems. Hence, the influence on the demand will be driven by the behaviour of the PV systems. Only in the hypothetical scenario in which the installations of BESSs will assume comparable levels of the PV systems, it will be possible to better manage the centralised resources

Future Mobility Advances and Trends

The trends of main interest on a global scale are those that can influence the development of humanity in the long term and are sometimes referred to as megatrends. The changes they bring with them can span several generations, profoundly changing society and, consequently, the competitive landscape of companies. The megatrends are numerous and each one involves the development of entire areas of activity. It is important to identify the megatrends of interest for strategic mobility planning and follow their developments, in order to consider them in the planning processes and correctly pilot investments. Megatrends are made possible and also influenced by the offer of new technologies, and lead to changes in cultural models. This chapter shows an era characterized by major technological innovations that are changing people’s ways of thinking and acting, with the establishment of new mobility models in order to meet new emerging needs

Application of genetic algorithms for driverless subway train energy optimization

After an introduction on the basic aspects of electric railway transports, focusing mainly on driverless subways and their related automation systems (ATC, ATP, and ATO), a technique for energy optimization of the train movement through their control using genetic algorithms will be presented. Genetic algorithms are a heuristic search and iterative stochastic method used in computing to find exact or approximate solutions to optimization problems. This optimization process has been calculated and tested on a real subway line in Milan through the implementation of a dedicated Matlab code. The so-defined algorithm provides the optimization of the trains movement through a coast control table created by the use of a genetic algorithm that minimizes the energy consumption and the train scheduled time. The obtained results suggest that the method is promising in minimizing the energy consumption of the electric trains

Transient Analysis of Large Scale PV Systems with Floating DC Section

The increasing penetration of renewable sources with power-electronic interfaces in power systems is raising technical problems and the overall efficiency of photovoltaic systems can decrease dramatically. In this context, the optimal layout for the photovoltaic system is required. The most adequate strategy to connect the renewable system to the electrical power grid or to supply the end users must be adopted. The present paper proposes a design layout of a PV plant using a DC bus system to improve the overall energy conversion efficiency. An analysis of steady-state system stability, voltage drop and DC cable conduction losses is conducted. The leakage currents to the ground are investigated through simulations. Experimental results are shown focused on the analysis of optimal layout of photovoltaic systems under particular operating conditions