Development Schemes of Electric Vehicle Charging Protocols and Implementation of Algorithms for Fast Charging under Dynamic Environments Leading towards Grid-to-Vehicle Integration

This thesis focuses on the development of electric vehicle (EV) charging protocols under a dynamic environment using artificial intelligence (AI), to achieve Vehicle-to-Grid (V2G) integration and promote automobile electrification. The proposed framework comprises three major complementary steps. Firstly, the DC fast charging scheme is developed under different ambient conditions such as temperature and relative humidity. Subsequently, the transient performance of the controller is improved while implementing the proposed DC fast charging scheme. Finally, various novel techno-economic scenarios and case studies are proposed to integrate EVs with the utility grid. The proposed novel scheme is composed of hierarchical stages; In the first stage, an investigation of the temperature or/and relative humidity impact on the charging process is implemented using the constant current-constant voltage (CC-CV) protocol. Where the relative humidity impact on the charging process was not investigated or mentioned in the literature survey. This was followed by the feedforward backpropagation neural network (FFBP-NN) classification algorithm supported by the statistical analysis of an instant charging current sample of only 10 seconds at any ambient condition. Then the FFBP-NN perfectly estimated the EV’s battery terminal voltage, charging current, and charging interval time with an error of 1% at the corresponding temperature and relative humidity. Then, a nonlinear identification model of the lithium-polymer ion battery dynamic behaviour is introduced based on the Hammerstein-Wiener (HW) model with an experimental error of 1.1876%. Compared with the CC-CV fast charging protocol, intelligent novel techniques based on the multistage charging current protocol (MSCC) are proposed using the Cuckoo optimization algorithm (COA). COA is applied to the Hierarchical technique (HT) and the Conditional random technique (CRT). Compared with the CC-CV charging protocol, an improvement in the charging efficiency of 8% and 14.1% was obtained by the HT and the CRT, respectively, in addition to a reduction in energy losses of 7.783% and 10.408% and a reduction in charging interval time of 18.1% and 22.45%, respectively. The stated charging protocols have been implemented throughout a smart charger. The charger comprises a DC-DC buck converter controlled by an artificial neural network predictive controller (NNPC), trained and supported by the long short-term memory neural network (LSTM). The LSTM network model was utilized in the offline forecasting of the PV output power, which was fed to the NNPC as the training data. The NNPC–LSTM controller was compared with the fuzzy logic (FL) and the conventional PID controllers and perfectly ensured that the optimum transient performance with a minimum battery terminal voltage ripple reached 1 mV with a very high-speed response of 1 ms in reaching the predetermined charging current stages. Finally, to alleviate the power demand pressure of the proposed EV charging framework on the utility grid, a novel smart techno-economic operation of an electric vehicle charging station (EVCS) in Egypt controlled by the aggregator is suggested based on a hierarchical model of multiple scenarios. The deterministic charging scheduling of the EVs is the upper stage of the model to balance the generated and consumed power of the station. Mixed-integer linear programming (MILP) is used to solve the first stage, where the EV charging peak demand value is reduced by 3.31% (4.5 kW). The second challenging stage is to maximize the EVCS profit whilst minimizing the EV charging tariff. In this stage, MILP and Markov Decision Process Reinforcement Learning (MDP-RL) resulted in an increase in EVCS revenue by 28.88% and 20.10%, respectively. Furthermore, the grid-to-vehicle (G2V) and vehicle-to-grid (V2G) technologies are applied to the stochastic EV parking across the day, controlled by the aggregator to alleviate the utility grid load demand. The aggregator determined the number of EVs that would participate in the electric power trade and sets the charging/discharging capacity level for each EV. The proposed model minimized the battery degradation cost while maximizing the revenue of the EV owner and minimizing the utility grid load demand based on the genetic algorithm (GA). The implemented procedure reduced the degradation cost by an average of 40.9256%, increased the EV SOC by 27%, and ensured an effective grid stabilization service by shaving the load demand to reach a predetermined grid average power across the day where the grid load demand decreased by 26.5% (371 kW)

Diseño de un cargador de vehículo eléctrico orientado a aplicaciones V2G

La concienciación y preocupación humana sobre el inminente cambio climático cada vez es más visible en la sociedad y, por tanto, las tecnologías emergentes capaces de cambiar el rumbo y crear un sector energético más sostenible jugarán un papel muy importante en un futuro próximo. Una de esas tecnologías es conocida como “vehículo a red” o V2G (Vehicle-to-Grid), ya que consigue que el flujo de energía se realice en ambas direcciones. Cuando esta tecnología se integra en el vehículo eléctrico (VE), éste podrá cargarse cuando el usuario lo necesite, pero en otras ocasiones, en la que sea la red la necesitada, el VE podrá proporcionarle esa energía, mejorándose así la utilización de las energías renovables y la estabilización de la conexión a la red eléctrica. En este trabajo, en primer lugar, se han estudiado las diferentes tecnologías V2G existentes en la literatura actual, y así poder escoger la más adecuada para las características del VE al que tiene que ser integrado. A continuación, se ha realizado el desarrollo de la solución adoptada, se ha implementado en PSIM y, por último, se presentan los resultados de las diferentes simulaciones con el fin de validar el correcto funcionamiento del convertidor.Gaur egungo gizartean gizakiak berehalako klima-aldaketari buruzko duen kontzientziazioa zein kezka gero eta nabarmenagoa egin da, eta, beraz, etorkizun hurbilean garrantzia handia izango dute norabidea aldatzeko eta sektore energetiko jasangarriago bat sortzeko gai diren teknologiek. Teknologia horietako bat “ibilgailutik sarera” edo V2G (Vehicle-to-Grid) bezala ezaguna da, energia fluxuaren bi norabideetan funtzionatzeko gai den teknologia baita. Hau da, teknologia hau ibilgailu elektrikoarekin integratzen denean adibidez, erabiltzaileak behar duenean ibilgailua kargatzeko aukera izango du, baina aldiz, sareak behar duen beste une batzuetan, ibilgailu elektrikoak azken honi energia eman ahal izango dio; horrela, energia berriztagarrien erabilera zein sare elektrikorako konexioaren egonkortasuna hobetuko dira. Lan honetan, lehenik eta behin, gaur egungo literaturan dauden V2G teknologiak aztertu dira, eta, horrela, integratu beharreko ibilgailu elektrikoaren ezaugarriekin bat datorren konfiguraziorik egokiena aukeratu ahal izan da. Jarraian, hautaturiko soluzioa garatu da, PSIM-en inplementazioa eginez ondoren, eta, azkenik, egindako simulazio ezberdinen emaitzak aurkeztu dira bihurgailuaren funtzionamendu egokia baliozkotzeko.Human concern as well as awareness about the forthcoming climate change is increasingly visible nowadays in society and, therefore, emerging technologies capable of changing the course and creating a more sustainable energy sector will play a really important role in the closer future. One of these novel technologies is known as Vehicle-to-Grid or V2G, since it is a technology which can work in both directions of energy flow. When this technology is integrated into the electric vehicle (EV), the vehicle can be charged when the user needs it (as it has been done until now), but the vehicle it also can provide energy to the grid when the network needs it, thus improving the use of renewable energies and stabilization of the connection to the grid. In this work, firstly, the different V2G technologies that appear in the current literature have been studied, being able like this to choose the most suitable for the characteristics of the EV to which it has to be then integrated. Subsequently, the development of the adopted solution has been carried out, it has been implemented in PSIM and, finally, the results of the different simulations have been presented in order to validate the correct operation of the converter

Unified power quality conditioner-based solar EV charging station using the GBDT–JS technique

This manuscript proposes a novel hybrid artificial intelligence (AI) approach for a unified power quality conditioner (UPQC) designed specifically for electric vehicle charging stations (EVCSs). The aim is to integrate multiple vehicle-to-grid (V2G) functionalities, thereby mitigating the challenges associated with electric vehicle (EV) grid integration and the incorporation of distributed energy resources (DERs). The hybrid technique presented in this manuscript combines the gradient boosting decision tree (GBDT) algorithm and the jellyfish search (JS) algorithm, referred to as the GBDT–JS technique. This innovative approach involves utilizing the charging station to offer EV charging services and facilitating the discharge of EVs to the power grid. Integration of the UPQC with DERs, such as photovoltaic (PV), is implemented to decrease the power rating of converters and fulfill power demand requirements. The initial converter within the UPQC is employed to manage the direct current (DC) voltage, while the second converter oversees the power charging or discharging processes of EVs. Additionally, it mitigates the impact of battery voltage fluctuations. The UPQC with vehicle-to-grid functionality minimizes the load pressure on the grid, preventing over-current issues. The presented approach regulates the UPQC converters to mitigate power quality issues such as harmonic currents and voltage sags. Subsequently, the effectiveness of this technique is demonstrated using the MATLAB/Simulink operating platform. The evaluation of GBDT–JS performance involves a comparative analysis with existing techniques. This assessment reveals that the proposed method effectively alleviates power quality issues, specifically reducing total harmonic distortion (THD), and delivers optimal outcomes

Unified power quality conditioner-based solar EV charging station using the GBDT–JS technique

This manuscript proposes a novel hybrid artificial intelligence (AI) approach for a unified power quality conditioner (UPQC) designed specifically for electric vehicle charging stations (EVCSs). The aim is to integrate multiple vehicle-to-grid (V2G) functionalities, thereby mitigating the challenges associated with electric vehicle (EV) grid integration and the incorporation of distributed energy resources (DERs). The hybrid technique presented in this manuscript combines the gradient boosting decision tree (GBDT) algorithm and the jellyfish search (JS) algorithm, referred to as the GBDT–JS technique. This innovative approach involves utilizing the charging station to offer EV charging services and facilitating the discharge of EVs to the power grid. Integration of the UPQC with DERs, such as photovoltaic (PV), is implemented to decrease the power rating of converters and fulfill power demand requirements. The initial converter within the UPQC is employed to manage the direct current (DC) voltage, while the second converter oversees the power charging or discharging processes of EVs. Additionally, it mitigates the impact of battery voltage fluctuations. The UPQC with vehicle-to-grid functionality minimizes the load pressure on the grid, preventing over-current issues. The presented approach regulates the UPQC converters to mitigate power quality issues such as harmonic currents and voltage sags. Subsequently, the effectiveness of this technique is demonstrated using the MATLAB/Simulink operating platform. The evaluation of GBDT–JS performance involves a comparative analysis with existing techniques. This assessment reveals that the proposed method effectively alleviates power quality issues, specifically reducing total harmonic distortion (THD), and delivers optimal outcomes

Diseño de un sistema de energías renovable

El objetivo de este proyecto es realizar el cálculo, diseño y simulación de un cargador bidireccional con aplicaciones vehículo a red para un vehículo eléctrico, principalmente para vehículos eléctricos particulares tipo Nissan Leaf, Nissan eNV200, Renault ZOE o Ford F-150 Lightning. Además de hacer el cálculo, diseño y simulación de un cargador bidireccional para aplicaciones vehículo a red, primero se hará una introducción de los diferentes conceptos para proporcionar ciertas nociones sobre que es la tecnología vehículo a red donde se explicarán las diferentes variables que tiene y sus aplicaciones, como funciona esta tecnología, las ventajas y desventajas que presenta y la normativa que tiene que cumplir esta tecnología. También se hará un estudio del arte para poder ver las diferentes topologías de electrónica de potencia aplicadas a esta tecnología, además se hará un pequeño estudio de mercado para ver los cargadores bidireccionales que hay actualmente en el mercado, sus características de funcionamiento y quien los fabrica. Una vez realizada la parte teórica se procederá al diseño, cálculo, modelado y simulación de una topología de electrónica de potencia aplicada a la tecnología vehículo a red. Primeramente se hará el diseño del circuito y el control de este, para después realizar los cálculos de los diferentes componentes que comprenden el circuito que se diseñara, una vez realizados los cálculos se modelara y simulara en diferentes entornos de funcionamiento, la herramienta con la que se modelara y simulara es SIMULINK la cual pertenece al grupo de aplicaciones de MATLAB.L'objectiu d'aquest projecte és fer el càlcul, el disseny i la simulació d'un carregador bidireccional amb aplicacions vehicle a xarxa per a un vehicle elèctric, principalment per a vehicles elèctrics particulars tipus Nissan Leaf, Nissan eNV200, Renault ZOE o Ford F-150 Lightning. A més de fer el càlcul, el disseny i la simulació d'un carregador bidireccional per a aplicacions vehicle a xarxa, primer es farà una introducció dels diferents conceptes per proporcionar certes nocions sobre què és la tecnologia vehicle a xarxa on s'explicaran les diferents variables que té i les seves aplicacions, com funciona aquesta tecnologia, els avantatges i els desavantatges que presenta i la normativa que ha de complir aquesta tecnologia. També es farà un estudi de l'art per poder veure les diferents topologies d'electrònica de potència aplicades a aquesta tecnologia, a més es farà un petit estudi de mercat per veure els carregadors bidireccionals que hi ha actualment al mercat, les seves característiques de funcionament i qui els fabrica. Un cop feta la part teòrica es procedirà al disseny, càlcul, modelatge i simulació d'una topologia d'electrònica de potència aplicada a la tecnologia vehicle a xarxa. Primerament es farà el disseny del circuit i el control d'aquest, per després realitzar els càlculs dels diferents components que comprenen el circuit que es dissenyés, un cop realitzats els càlculs es modelarà i simularà en diferents entorns de funcionament, l'eina amb què es modelarà i simularà és SIMULINK la qual pertany al grup d'aplicacions de MATLAB.The objective of this project is to carry out the calculation, design and simulation of a bidirectional charger with vehicle-to-grid applications for an electric vehicle, mainly for private electric vehicles such as Nissan Leaf, Nissan eNV200, Renault ZOE or Ford F-150 Lightning. In addition to calculating, designing, and simulating a bidirectional charger for vehicle-to-grid applications, first there will be an introduction to the different concepts to provide certain notions about what vehicle-to-grid technology is, where the different variables it has and its consequences will be explained. applications, how this technology works, the advantages and disadvantages it presents and the regulations that this technology must comply with. There will also be a study of the art to be able to see the different topologies of power electronics applied to this technology, in addition there will be a small market study to see the bidirectional chargers that are currently on the market, their operating characteristics and who makes them. Once the theoretical part has been completed, we will proceed to the design, calculation, modeling and simulation of a power electronics topology applied to vehicle-to-grid technology. Firstly, the design of the circuit and its control will be made, to later carry out the calculations of the different components that comprise the circuit to be designed, once the calculations have been made, it will be modeled and simulated in different operating environments, the tool with which It will be modeled and simulated is SIMULINK which belongs to the MATLAB group of applications

Multi-Objective Optimization of PV and Energy Storage Systems for Ultra-Fast Charging Stations

The installation of ultra-fast charging stations (UFCSs) is essential to push the adoption of electric vehicles (EVs). Given the high amount of power required by this charging technology, the integration of renewable energy sources (RESs) and energy storage systems (ESSs) in the design of the station represents a valuable option to decrease its impact on the grid and the environment. Therefore, this paper proposes a multi-objective optimization problem for the optimal sizing of photovoltaic (PV) system and battery ESS (BESS) in a UFCS of EVs. The proposed multi-objective function aims to minimize, on one side, the annualized cost of the station, and on the other side, the produced pollutant emissions. The decision variables are the number of PV panels and the capacity of the ESS to be installed. The optimization problem is reduced to a single-objective problem by applying the linear scalarization method. Then the equivalent single-objective function is optimized through a genetic algorithm (GA). The proposed optimization framework is applied to a study case and the results prove that PV and ESS could lead to a significant reduction of both the annualized cost and the pollutant emissions. Finally, a sensitivity analysis is also presented to validate the effectiveness of the proposed solution

DC & Hybrid Micro-Grids

This book is a printed version of the papers published in the Special Issue “DC & Hybrid Microgrids” of Applied Sciences. This Special Issue, co-organized by the University of Pisa, Italy and Østfold University College in Norway, has collected nine papers and the editorial, from 28 submitted, with authors from Asia, North America and Europe. The published articles provide an overview of the most recent research advances in direct current (DC) and hybrid microgrids, exploiting the opportunities offered by the use of renewable energy sources, battery energy storage systems, power converters, innovative control and energy management strategies

Prospects for Electric Mobility: Systemic, Economic and Environmental Issues

The transport sector, which is currently almost completely based on fossil fuels, is one of the major contributors to greenhouse gas emissions. Heading towards a more sustainable development of mobility could be possible with more energy efficient automotive technologies such as battery electric vehicles. The number of electric vehicles has been increasing over the last decade, but there are still many challenges that have to be solved in the future. This Special Issue “Prospects for Electric Mobility: Systemic, Economic and Environmental Issues” contributes to the better understanding of the current situation as well as the future prospects and impediments for electro mobility. The published papers range from historical development of electricity use in different transport modes and the recent challenges up to future perspectives

Impact de l'utilisation de composants au carbure de silicium sur la mise en oeuvre d'un chargeur bidirectionnel

Le nombre grandissant de véhicules électriques implique une grande quantité d’accumulateurs devant être alimentés par le réseau électrique. Le principe d’échange d’énergie véhicule-réseau (V2G) permet des transferts énergétiques bidirectionnels entre le réseau et les véhicules électriques. Il est ainsi possible de compter sur ces accumulateurs pour alimenter le réseau. Le chargeur intégré assure l’interface entre le réseau et ces accumulateurs. Son rendement constitue un élément majeur de la viabilité du principe V2G. Son caractère mobile est tout aussi important puisque cet appareil est intégré au véhicule. Les semi-conducteurs au carbure de silicium (SiC) présentent une percée substantielle pour atteindre le rendement et la densité énergétiques nécessaires pour un tel convertisseur. Les impacts de l’utilisation du SiC dans la conception et la mise en œuvre d’un chargeur bidirectionnel seront démontrés dans ce mémoire. La topologie du convertisseur est initialement déterminée puis dimensionnée pour les paramètres de l’étude, soit en tension et puissance. Les simulations du convertisseur exposent les différences entre une solution n’utilisant que des composants au SiC à une seconde n’utilisant que des composant au silicium (Si) traditionnellement utilisés. Une dernière solution combinant les deux types de composant a aussi été évaluée. Finalement, la mise en œuvre d’un chargeur bidirectionnel prototype démontre des phénomènes distincts entre les solutions exposant l’impact des semi-conducteurs au carbure de silicium sur le rendement du convertisseur bidirectionnel