Design and Operation of Stationary Distributed Battery Micro-storage Systems

Due to some technical and environmental constraints, expanding the current electric power generation and transmission system is being challenged by even increasing the deployment of distributed renewable generation and storage systems. Energy storage can be used to store energy from utility during low-demand (off-peak) hours and deliver this energy back to the utility during high-demand (on-peak) hours. Furthermore, energy storage can be used with renewable sources to overcome some of their limitations such as their strong dependence on the weather conditions, which cannot be perfectly predicted, and their unmatched or out-of-synchronization generation peaks with the demand peaks. Generally, energy storage enhances the performance of distributed renewable sources and increases the efficiency of the entire power system. Moreover, energy storage allows for leveling the load, shaving peak demands, and furthermore, transacting power with the utility grid. This research proposes an energy management system (EMS) to manage the operation of distributed grid-tied battery micro-storage systems for stationary applications when operated with and without renewable sources. The term micro refers to the capacity of the energy storage compared to the grid capacity. The proposed management system employs four dynamic models; economic model, battery model, and load and weather forecasting models. These models, which are the main contribution of this research, are used in order to optimally control the operation of the micro-storage system (MSS) to maximize the economic return for the end-user when operated in an electricity spot market system. Chapter 1 presents an introduction to the drawbacks of the current power system, the role of energy storage in deregulated electricity markets, limitations of renewable sources, ways for participating in spot electricity markets, and an outline of the main contributions in this dissertation. In Chapter 2, some hardware design considerations for distributed micro-storage systems as well as some economic analyses are presented. Chapters 3 and 4 propose a battery management system (BMS) that handles three main functions: battery charging, state-of-charge (SOC) estimation and state-of-health (SOH) estimation. Chapter 5 proposes load and weather forecasting models using artificial neural networks (ANNs) to develop an energy management strategy to control the operation of the MSS in a spot market system when incorporated with other renewable energy sources. Finally, conclusions and future work are presented in Chapter 6

Technology development of electric vehicles: A review

To reduce the dependence on oil and environmental pollution, the development of electric vehicles has been accelerated in many countries. The implementation of EVs, especially battery electric vehicles, is considered a solution to the energy crisis and environmental issues. This paper provides a comprehensive review of the technical development of EVs and emerging technologies for their future application. Key technologies regarding batteries, charging technology, electric motors and control, and charging infrastructure of EVs are summarized. This paper also highlights the technical challenges and emerging technologies for the improvement of efficiency, reliability, and safety of EVs in the coming stages as another contribution

E-transportation: the role of embedded systems in electric energy transfer from grid to vehicle

Electric vehicles (EVs) are a promising solution to reduce the transportation dependency on oil, as well as the environmental concerns. Realization of E-transportation relies on providing electrical energy to the EVs in an effective way. Energy storage system (ESS) technologies, including batteries and ultra-capacitors, have been significantly improved in terms of stored energy and power. Beside technology advancements, a battery management system is necessary to enhance safety, reliability and efficiency of the battery. Moreover, charging infrastructure is crucial to transfer electrical energy from the grid to the EV in an effective and reliable way. Every aspect of E-transportation is permeated by the presence of an intelligent hardware platform, which is embedded in the vehicle components, provided with the proper interfaces to address the communication, control and sensing needs. This embedded system controls the power electronics devices, negotiates with the partners in multi-agent scenarios, and performs fundamental tasks such as power flow control and battery management. The aim of this paper is to give an overview of the open challenges in E-transportation and to show the fundamental role played by embedded systems. The conclusion is that transportation electrification cannot fully be realized without the inclusion of the recent advancements in embedded systems

Ecolabelling. Criteria development for rechargeable batteries in ICT products

This research puts together two massive areas: voluntary certification programmes, specifically Type I ecolabelling (ISO 14024), aimed to incentivise and assist in providing customers with sustainable in all meanings products; and rechargeable batteries – inalienable element of portable electronic products. Moreover, the importance of batteries lifts up to an absolutely new level – with a rapid development of electric vehicles and energy storage systems, often used to accumulate energy from renewable energy sources. Mass application of rechargeable batteries in consumer electronic products, first of all, increases the number of batteries on the market, and, thus, the battery waste stream. Secondly, this encourages producers to search for new chemical compounds for the creation of batteries with the increased energy density and faster recharge time. Upcoming revision of the Battery Directive; application of new chemical compounds in cathodes production; potential risks associated with supply of such resources as cobalt and lithium; increased waste battery stream; the End-of-Life management; reaching higher rates for collection, sorting, and recycling of waste batteries; arising social conflicts around certain materials; product redesign and the necessity to be in compliance with the waste management hierarchy. All the listed aspects and challenges create a predisposition for Type I ecolabelling – to face these challenges and, thereby, to reconsider existing requirements to rechargeable batteries, initiating positive changes. This research aims to define new potential aspects and to improve existing criteria for rechargeable batteries in portable ICT products – to meet arising environmental and social challenges, related to all life cycle stages of rechargeable batteries. To achieve this, the author conducted a research, observing background on battery technologies and the battery market; current requirements of Type I ecolabelling programmes to both – ICT products equipped with rechargeable batteries, and rechargeable batteries themselves. Numerous stakeholders, from electronics producers, waste battery collectors, and recyclers – to battery specialists and certification programmes, contributed with their view on rechargeable batteries. The outcome of the research is the list of potential aspects of rechargeable batteries to be considered by Type I ecolabelling programmes for further implementation in the standards for mobile phones; tablets, laptops and notebook computers

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)

A Comparative Study on the Influence of DC/DC-Converter Induced High Frequency Current Ripple on Lithium-Ion Batteries

Modern battery energy systems are key enablers of the conversion of our energy and mobility sector towards renewability. Most of the time, their batteries are connected to power electronics that induce high frequency current ripple on the batteries that could lead to reinforced battery ageing. This study investigates the influence of high frequency current ripple on the ageing of commercially available, cylindrical 18,650 lithium-ion batteries in comparison to identical batteries that are aged with a conventional battery test system. The respective ageing tests that have been carried out to obtain numerous parameters such as the capacity loss, the gradient of voltage curves and impedance spectra are explained and evaluated to pinpoint how current ripple possibly affects battery ageing. Finally, the results suggest that there is little to no further influence of current ripple that is severe enough to stand out against ageing effects due to the underlying accelerated cyclic ageing

A comprehensive study of key Electric Vehicle (EV) components, technologies, challenges, impacts, and future direction of development

Abstract: Electric vehicles (EV), including Battery Electric Vehicle (BEV), Hybrid Electric Vehicle (HEV), Plug-in Hybrid Electric Vehicle (PHEV), Fuel Cell Electric Vehicle (FCEV), are becoming more commonplace in the transportation sector in recent times. As the present trend suggests, this mode of transport is likely to replace internal combustion engine (ICE) vehicles in the near future. Each of the main EV components has a number of technologies that are currently in use or can become prominent in the future. EVs can cause significant impacts on the environment, power system, and other related sectors. The present power system could face huge instabilities with enough EV penetration, but with proper management and coordination, EVs can be turned into a major contributor to the successful implementation of the smart grid concept. There are possibilities of immense environmental benefits as well, as the EVs can extensively reduce the greenhouse gas emissions produced by the transportation sector. However, there are some major obstacles for EVs to overcome before totally replacing ICE vehicles. This paper is focused on reviewing all the useful data available on EV configurations, battery energy sources, electrical machines, charging techniques, optimization techniques, impacts, trends, and possible directions of future developments. Its objective is to provide an overall picture of the current EV technology and ways of future development to assist in future researches in this sector

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

Battery cell balance of electric vehicles under fast-DC charging

Electric vehicle (EV) range, recharge opportunities and time to recharge are major barriers to mainstream acceptance. Fast-DC charging has the potential to overcome these barriers. This research investigates the impact of fast-DC charging on battery cell balance, charge capacity and range for an EV travelling long distances on an 'electric-highway'. Two commercially available EVs were exposed to a series of discharge and fast-DC charge cycles to measure cell balance and charge capacity. The vehicles' battery management systems (BMS) were capable of successfully balancing individual cells and hence maintaining the batteries' charge capacity. Although fast-DC charge levels and discharge safety margins significantly reduced the vehicles' charge capacity and range as stated by the manufacturer, these values remained stable for the test period. In regards to cell balance and charge capacity, our research suggests that fast-DC charging technology is a feasible option for EVs to travel large distances in a day

Interface Development for a Conversion of an Electric Vehicle

Após a conversão de um veículo de combustíveis fósseis em elétrico, é necessário desenvolver um ecrã que contenha uma interface capaz de mostrar informação relevante ao utilizador, como o estado da bateria, rotações por minuto do motor, ou a temperatura de certos componentes. Este projeto consiste em desenvolver uma interface que recebe informação do sistema CAN Bus do veículo, e depois apresentá-la de forma clara e intuitiva ao condutor.After the conversion of a fossil fuel vehicle into fully electric, it is necessary to have a display loaded with an interface capable of showing information to the user, such as the battery percentage, rotations per minute of the motor and the temperatures of pivotal components. This project consists in developing an interface capable of receiving all the information from the CAN Bus system, and present it in a clear and intuitive way to the drive