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This book serves as an introductory reference guide for those studying the application of models in energy systems. The book opens with a taxonomy of energy models and treatment of descriptive and analytical models, providing the reader with a foundation of the basic principles underlying the energy models and positioning these principles in the context of energy system studies. In turn, the book provides valuable insights into the varied applications of different energy models to answer complex questions, including those concerning specific aspects of energy policy measures dealing with issues of supply and demand. Case studies are provided in all of the chapters, offering real-world examples of how existing models fit the classification methods outlined here. The book’s remaining chapters address a broad range of principles and applications, taking the reader from the basic principles involved, to state-of-the-art energy production and consumption processes, using modeling and validation/illustration in case studies to do so. With its in-depth mathematical foundation, this book serves as a comprehensive collection of work on modeling energy systems and processes, taking inexperienced graduate students from the basics through to a high-level understanding of the modeling processes in question, while also providing professionals and academic researchers in the field of energy planning with an up-to-date reference guide covering the latest works.
Energy Systems Engineering is one of the most exciting and fastest growing fields in engineering. Modeling and simulation plays a key role in Energy Systems Engineering because it is the primary basis on which energy system design, control, optimization, and analysis are based. This book contains a specially curated collection of recent research articles on the modeling and simulation of energy systems written by top experts around the world from universities and research labs, such as Massachusetts Institute of Technology, Yale University, Norwegian University of Science and Technology, National Energy Technology Laboratory of the US Department of Energy, University of Technology Sydney, McMaster University, Queens University, Purdue University, the University of Connecticut, Technical University of Denmark, the University of Toronto, Technische Universität Berlin, Texas A&M, the University of Pennsylvania, and many more. The key research themes covered include energy systems design, control systems, flexible operations, operational strategies, and systems analysis. The addressed areas of application include electric power generation, refrigeration cycles, natural gas liquefaction, shale gas treatment, concentrated solar power, waste-to-energy systems, micro-gas turbines, carbon dioxide capture systems, energy storage, petroleum refinery unit operations, Brayton cycles, to name but a few.
This book presents a comprehensive definition of smart grids and their benefits, and compares smart and traditional grids. It also introduces a design methodology for stand-alone hybrid renewable energy system with and without applying the smart grid concepts for comparison purposes. It discusses using renewable energy power plants to feed loads in remote areas as well as in central power plants connected to electric utilities. Smart grid concepts used in the design of the hybrid renewable power systems can reduce the size of components, which can be translated to a reduction in the cost of generated energy. The proposed hybrid renewable energy system includes wind, photovoltaic, battery, and diesel, and is used initially to feed certain loads, covering the load required completely. The book introduces a novel methodology taking the smart grid concept into account by dividing the loads into high and low priority parts. The high priority part should be supplied at any generated conditions. However, the low priority loads can be shifted to the time when the generated energy from renewable energy sources is greater than the high priority loads requirements. The results show that the use of this smart grid concept reduces the component size and the cost of generated energy compared to that without dividing the loads. The book also describes the use of smart optimization techniques like particle swarm optimization (PSO) and genetic algorithm (GA) to optimally design the hybrid renewable energy system. This book provides an excellent background to renewable energy sources, optimal sizing and locating of hybrid renewable energy sources, the best optimization methodologies for sizing and designing the components of hybrid renewable energy systems, and offers insights into using smart grid concepts in the system’s design and sizing. It also helps readers understand the dispatch methodology and how to connect the system’s different components, their modeling, and the cost analysis of the system.
Energy Systems Modeling and Policy Analysis covers a wide spectrum of topics including policy analysis and the optimal operational planning of integrated energy systems using a systems approach. This book details the importance of energy modeling and policy analysis, system dynamics and linear programming, modeling of energy supplies, energy demand, and environmental impact. Integrated energy systems at micro- and macro-levels, the application of simulation techniques for integrated rural energy systems, and integrated electric power systems/smart grids are covered as well. Features: Covers topics such as modeling, optimization and control of energy systems, and data analysis collected using a Supervisory Control and Data Acquisition (SCADA) system Uses system dynamics methodology (based on control systems theory) as well as other modeling tools Focuses on energy and environmental issues Provides optimal operational planning and management of integrated electric power systems and smart grids Covers the simulated planning and management of integrated national electric power systems using system dynamics This book is aimed at graduate students in electrical engineering, energy technology, microgrids, energy policy, and control systems.
This book comprises five peer-reviewed articles covering original research articles on the modeling and simulation of electricity systems for transport and energy storage. The topics include: 1 - Optimal siting and sizing methodology to design an energy storage system (ESS) for railway lines; 2 - Technical–economic comparison between a 3 kV DC railway and the use of trains with on-board storage systems; 3 - How to improve electrical feeding substations, by changing transformer technology and by installing dedicated high-power-oriented storage systems; 4 - Algorithm applied to a vehicle-to-grid (V2G) technology. 5 - Thermal investigation and optimization of an air-cooled lithium-ion battery pack.
Modelling, Assessment, and Optimization of Energy Systems provides comprehensive methodologies for the thermal modelling of energy systems based on thermodynamic, exergoeconomic and exergoenviromental approaches. It provides advanced analytical approaches, assessment criteria and the methodologies to obtain analytical expressions from the experimental data. The concept of single-objective and multi-objective optimization with application to energy systems is provided, along with decision-making tools for multi-objective problems, multi-criteria problems, for simplifying the optimization of large energy systems, and for exergoeconomic improvement integrated with a simulator EIS method. This book provides a comprehensive methodology for modeling, assessment, improvement of any energy system with guidance, and practical examples that provide detailed insights for energy engineering, mechanical engineering, chemical engineering and researchers in the field of analysis and optimization of energy systems. - Offers comprehensive analytical tools for the modeling and simulation of energy systems with applications for decision-making tools - Provides methodologies to obtain analytical models of energy systems for experimental data - Covers decision-making tools in multi-objective problems
Ocean Energy Modeling and Simulation with Big Data: Computational Intelligence for System Optimization and Grid Integration offers the fundamental and practical aspects of big data solutions applied to ocean and offshore energy systems. The book explores techniques for assessment of tidal, wave and offshore wind energy systems. It presents the use of data mining software to simulate systems and Hadoop technology to evaluate control systems. The use of Map Reduce algorithms in systems optimization is examined, along with the application of NoSQL in systems management. Actual data collection through web-based applications and social networks is discussed, along with practical applications of recommendations. - Introduces computational methods for processing and analyzing data to predict ocean energy system production, assess their efficiency, and ensure their reliable connection to power grids - Covers data processing solutions like Hadoop, NoSQL, Map Reduce and Lambda, discussing their applications in ocean energy for system design and optimization - Provides practical exercises that demonstrate the concepts explored in each chapter
This book provides readers with an overview of recent theories and methods for studying complex mechanical systems used in energy production, such as wind turbines, but not limited to them. The emphasis is put on strategies for increasing energy efficiency, and on recent industrial applications. Topics cover dynamics and vibration, vibroacoustics, engineering design, modelling and simulation, fault diagnostics, signal processing and prognostics. The book is based on peer-review contributions and invited talks presented at the first International Workshop on MOdelling and Simulation of COmplex Systems for Sustainable Energy Efficiency, MOSCOSSEE 2021, held online on February 25-26, 2021, and organized by the LAboratory of Mechanics, Modelling and Production (LA2MP) from University of Sfax, Tunisia and the Department of Mechanical and Aeronautical engineering, Centre of Asset Integrity Management (C-AIM) from University of Pretoria, South Africa. By offering authoritative information on innovative methods and tools for application in renewable energy production, it provides a valuable resource to both academics and professionals, and a bridge to facilitate communication between the two groups.
Modern power and energy systems are characterized by the wide integration of distributed generation, storage and electric vehicles, adoption of ICT solutions, and interconnection of different energy carriers and consumer engagement, posing new challenges and creating new opportunities. Advanced testing and validation methods are needed to efficiently validate power equipment and controls in the contemporary complex environment and support the transition to a cleaner and sustainable energy system. Real-time hardware-in-the-loop (HIL) simulation has proven to be an effective method for validating and de-risking power system equipment in highly realistic, flexible, and repeatable conditions. Controller hardware-in-the-loop (CHIL) and power hardware-in-the-loop (PHIL) are the two main HIL simulation methods used in industry and academia that contribute to system-level testing enhancement by exploiting the flexibility of digital simulations in testing actual controllers and power equipment. This book addresses recent advances in real-time HIL simulation in several domains (also in new and promising areas), including technique improvements to promote its wider use. It is composed of 14 papers dealing with advances in HIL testing of power electronic converters, power system protection, modeling for real-time digital simulation, co-simulation, geographically distributed HIL, and multiphysics HIL, among other topics.
This book creates the emergence of disruptive technologies that have led to a significant change in the role of mathematics and statistics for problem solving, with the use of sophisticated software and hardware in solving complex systems and process. In the era of digital technology, mathematics and statistics need to be highly relevant to be able to cater for the needs of IR4.0 such as big data analytics, simulation, autonomous system, and cloud computing. Motivated by this development, a total of 26 chapters are contributed by respectable experts for this book. The main scope of the book is to conduct a new system of modeling and simulations on solving differential equations, nonlinear equations, energy, epidemiology, and risk assessment. This book is of interest for postgraduate students, researchers as well as other scientists who are working in numerical modeling and simulations based on efficient mathematical and statistical techniques.