Praise for the Third Edition: "This is one of the best books available. Its excellent organizational structure allows quick reference to specific models and its clear presentation . . . solidifies the understanding of the concepts being presented."IIE Transactions on Operations EngineeringThoroughly revised and expanded to reflect the latest developments in the field, Fundamentals of Queueing Theory, Fourth Edition continues to present the basic statistical principles that are necessary to analyze the probabilistic nature of queues. Rather than presenting a narrow focus on the subject, this update illustrates the wide-reaching, fundamental concepts in queueing theory and its applications to diverse areas such as computer science, engineering, business, and operations research.This update takes a numerical approach to understanding and making probable estimations relating to queues, with a comprehensive outline of simple and more advanced queueing models. Newly featured topics of the Fourth Edition include:Retrial queuesApproximations for queueing networksNumerical inversion of transformsDetermining the appropriate number of servers to balance quality and cost of serviceEach chapter provides a self-contained presentation of key concepts and formulae, allowing readers to work with each section independently, while a summary table at the end of the book outlines the types of queues that have been discussed and their results. In addition, two new appendices have been added, discussing transforms and generating functions as well as the fundamentals of differential and difference equations. New examples are now included along with problems that incorporate QtsPlus software, which is freely available via the book's related Web site.With its accessible style and wealth of real-world examples, Fundamentals of Queueing Theory, Fourth Edition is an ideal book for courses on queueing theory at the upper-undergraduate and graduate levels. It is also a valuable resource for researchers and practitioners who analyze congestion in the fields of telecommunications, transportation, aviation, and management science.

Fundamentals of Queueing Theory

Today’s electric vehicles are almost exclusively powered by lithium-ion batteries, but there is a long way to go before electric vehicles become dominant in the global automotive market. In addition to policy support, widespread deployment of electric vehicles requires high-performance and low-cost energy storage technologies, including not only batteries but also alternative electrochemical devices. Here, we provide a comprehensive evaluation of various batteries and hydrogen fuel cells that have the greatest potential to succeed in commercial applications. Three sectors that are not well served by current lithium-ion-powered electric vehicles, namely the long-range, low-cost and high-utilization transportation markets, are discussed. The technological properties that must be improved to fully enable these electric vehicle markets include specific energy, cost, safety and power grid compatibility. Six energy storage and conversion technologies that possess varying combinations of these improved characteristics are compared and separately evaluated for each market. The remainder of the Review briefly discusses the technological status of these clean energy technologies, emphasizing barriers that must be overcome. Recent years have seen significant growth of electric vehicles and extensive development of energy storage technologies. This Review evaluates the potential of a series of promising batteries and hydrogen fuel cells in their deployment in automotive electrification.

Batteries and fuel cells for emerging electric vehicle markets

A communication infrastructure is an essential part to the success of the emerging smart grid. A scalable and pervasive communication infrastructure is crucial in both construction and operation of a smart grid. In this paper, we present the background and motivation of communication infrastructures in smart grid systems. We also summarize major requirements that smart grid communications must meet. From the experience of several industrial trials on smart grid with communication infrastructures, we expect that the traditional carbon fuel based power plants can cooperate with emerging distributed renewable energy such as wind, solar, etc, to reduce the carbon fuel consumption and consequent green house gas such as carbon dioxide emission. The consumers can minimize their expense on energy by adjusting their intelligent home appliance operations to avoid the peak hours and utilize the renewable energy instead. We further explore the challenges for a communication infrastructure as the part of a complex smart grid system. Since a smart grid system might have over millions of consumers and devices, the demand of its reliability and security is extremely critical. Through a communication infrastructure, a smart grid can improve power reliability and quality to eliminate electricity blackout. Security is a challenging issue since the on-going smart grid systems facing increasing vulnerabilities as more and more automation, remote monitoring/controlling and supervision entities are interconnected.

https://digitalcommons.unl.edu/cgi/viewcontent.cgi?article=1315&context=electricalengineeringfacpub

A Survey on Smart Grid CommunicationInfrastructures: Motivations, Requirements andChallenges

This paper presents a comprehensive review and assessment of the latest research and advancement of electric vehicles (EVs) interaction with smart grid portraying the future electric power system model. The concept goal of the smart grid along with the future deployment of the EVs puts forward various challenges in terms of electric grid infrastructure, communication and control. Following an intensive review on advanced smart metering and communication infrastructures, the strategy for integrating the EVs into the electric grid is presented. Various EV smart charging technologies are also extensively examined with the perspective of their potential, impacts and limitations under the vehicle-to-grid (V2G) phenomenon. Moreover, the high penetration of renewable energy sources (wind and photovoltaic solar) is soaring up into the power system. However, their intermittent power output poses different challenges on the planning, operation and control of the power system networks. On the other hand, the deployment of EVs in the energy market can compensate for the fluctuations of the electric grid. In this context, a literature review on the integration of the renewable energy and the latest feasible solution using EVs with the insight of the promising research gap to be covered up are investigated. Furthermore, the feasibility of the smart V2G system is thoroughly discussed. In this paper, the EVs interactions with the smart grid as the future energy system model are extensively discussed and research gap is revealed for the possible solutions.

Electric vehicles and smart grid interaction: A review on vehicle to grid and renewable energy sources integration

The integration of distributed generation (DG) units in power distribution networks has become increasingly important in recent years. The aim of the optimal DG placement (ODGP) is to provide the best locations and sizes of DGs to optimize electrical distribution network operation and planning taking into account DG capacity constraints. Several models and methods have been suggested for the solution of the ODGP problem. This paper presents an overview of the state of the art models and methods applied to the ODGP problem, analyzing and classifying current and future research trends in this field.

/pdf/optimal-distributed-generation-placement-in-power-4b69hs7usu.pdf

Optimal Distributed Generation Placement in Power Distribution Networks: Models, Methods, and Future Research

This paper proposes a method to evaluate the worth of installing renewable distributed generation (DG) in distribution networks. Moreover, the work optimally allocates these DG units in the distribution network to maximize the worth of the connection to the local distribution company (LDC), as well as the customers connected to the system. The proposed methodology helps the LDC to better assess the benefits of the renewable DG units' proposed connections and to identify the optimal buses on which to connect these DG units. The benefits considered in this paper are deferral of upgrade investments, reduction of the cost of energy losses, and reliability improvement, which is represented by the interruption cost reduction. The proposed methodology takes into consideration the uncertainty and variability associated with the output power of renewable DG as well as the load variability. The planning problem of determining the optimal location and sizes of DG units is defined as multi-objective mixed integer programming.

DG allocation for benefit maximization in distribution networks

This paper proposes a novel online coordination method for the charging of plug-in electric vehicles (PEVs) in smart distribution networks. The goal of the proposed method is to optimally charge the PEVs in order to maximize the PEV owners' satisfaction and to minimize system operating costs without violating power system constraints. Unlike the solutions reported in the literature, the proposed charging architecture guarantees the feasibility of the charging decisions by means of a novel prediction unit that can forecast future PEVs power demand and through an innovative two-stage optimization unit that ensures effective charging coordination. Coordinated PEV discharging also enables improved utilization of power system resources. Simulation results for a typical distribution network are provided as a demonstration of the effectiveness of the proposed architecture.

/pdf/real-time-pev-charging-discharging-coordination-in-smart-4rp8bli0og.pdf

Real-Time PEV Charging/Discharging Coordination in Smart Distribution Systems

This paper proposes a novel model to estimate the electric energy consumption of light duty fleet of plug-in electric vehicles (PEVs) This model can be used to evaluate the impacts of plugging such loads in distribution networks Both vehicles users' habits and diversity of usage are considered in the presented model, as well as different electric ranges and ambient temperature effect Moreover, the paper proposes a method to optimally allocate distributed generation (DG) units in the distribution network to mitigate the impacts of high penetration of PEVs The proposed model shall help the local distribution companies (LDC) to better assess the expected effects of PEVs on their networks and evaluate the required upgrades Furthermore, the proposed DG allocation methodology helps to identify the optimal buses on which to connect these DG units in the presence of high PEVs penetration A genetic based approach is utilized for the planning problem of determining the optimal locations and sizes of DG units, which is defined as a multi-objective mixed integer programming

PEVs modeling and impacts mitigation in distribution networks

This paper proposes a multi-year multi-objective planning algorithm for enabling distribution networks to accommodate high penetrations of plug-in electric vehicles (PEVs) in conjunction with renewable distributed generation (DG). The proposed algorithm includes consideration of uncertainties and will help local distribution companies (LDC) better assess the expected impacts of PEVs on their networks and on proposed renewable DG connections. The goal of the proposed algorithm is to minimize greenhouse gas emissions and system costs during the planning horizon. An approach based on a non-dominated sorting genetic algorithm (NDSGA) is utilized to solve the planning problem of determining the optimal level of PEV penetration as well as the location, size, and year of installation of renewable DG units. The planning problem is defined in terms of multi-objective mixed integer nonlinear programming. The outcomes of the planning problem represent the Pareto frontier, which describes the optimal system solutions, from which the LDC can choose the system operating point, based on its preferences.

Mostafa F. Shaaban

Papers

DG allocation for benefit maximization in distribution networks

Real-Time PEV Charging/Discharging Coordination in Smart Distribution Systems

PEVs modeling and impacts mitigation in distribution networks

Accommodating High Penetrations of PEVs and Renewable DG Considering Uncertainties in Distribution Systems

Long-term multi-objective distribution network planning by DG allocation and feeders’ reconfiguration