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

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 costs impact the profitability of virtually all industrial processes. Stressing how plants use power, and how that power is actually generated, this book provides a clear and simple way to understand the energy usage in various processes, as well as methods for optimizing these processes using practical hands-on simulations and a unique approach that details solved problems utilizing actual plant data. Invaluable information offers a complete energy-saving approach essential for both the chemical and mechanical engineering curricula, as well as for practicing engineers.

An essential resource for optimizing energy systems to enhance design capability, performance and sustainability Optimization of Energy Systems comprehensively describes the thermodynamic modelling, analysis and optimization of numerous types of energy systems in various applications. It provides a new understanding of the system and the process of defining proper objective functions for determination of the most suitable design parameters for achieving enhanced efficiency, cost effectiveness and sustainability. Beginning with a general summary of thermodynamics, optimization techniques and optimization methods for thermal components, the book goes on to describe how to determine the most appropriate design parameters for more complex energy systems using various optimization methods. The results of each chapter provide potential tools for design, analysis, performance improvement, and greenhouse gas emissions reduction. Key features: Comprehensive coverage of the modelling, analysis and optimization of many energy systems for a variety of applications. Examples, practical applications and case studies to put theory into practice. Study problems at the end of each chapter that foster critical thinking and skill development. Written in an easy-to-follow style, starting with simple systems and moving to advanced energy systems and their complexities. A unique resource for understanding cutting-edge research in the thermodynamic analysis and optimization of a wide range of energy systems, Optimization of Energy Systems is suitable for graduate and senior undergraduate students, researchers, engineers, practitioners, and scientists in the area of energy systems.

Renewable Energy Systems: Modelling, Optimization and Control aims to cross-pollinate recent advances in the study of renewable energy control systems by bringing together diverse scientific breakthroughs on the modeling, control and optimization of renewable energy systems by leading researchers. The book brings together the most comprehensive collection of modeling, control theorems and optimization techniques to help solve many scientific issues for researchers in renewable energy and control engineering. Many multidisciplinary applications are discussed, including new fundamentals, modeling, analysis, design, realization and experimental results. The book also covers new circuits and systems to help researchers solve many nonlinear problems. This book fills the gaps between different interdisciplinary applications, ranging from mathematical concepts, modeling, and analysis, up to the realization and experimental work. - Covers modeling, control theorems and optimization techniques which will solve many scientific issues for researchers in renewable energy - Discusses many multidisciplinary applications with new fundamentals, modeling, analysis, design, realization and experimental results - Includes new circuits and systems, helping researchers solve many nonlinear problems

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.

Design and Optimization of Biogas Energy Systems presents an overview on planning, implementing, assessing and optimizing biogas systems, from fuel conversion to power generation. The book introduces the fundamental elements of bioenergy systems, highlighting the specificities of biogas systems. It discusses the current state of their adoption at a global level and the challenges faced by designers and operators. Methods for sizing, simulating and modeling are discussed, including prefeasibility analysis, available production processes, integration into hybrid energy systems, and the application of Big Data analysis and game theory concepts. All chapters include real-life examples and exercises to illustrate the topics being covered. The book goes beyond theory to offer practical knowledge of methods to reach solutions to key challenges in the field. This is a valuable resource for researchers, practitioners and graduate students interested in developing smart, reliable and sustainable biogas technologies. - Provides an applied approach to biogas systems, from technology fundamentals, to economic and environmental assessment - Explores control methods and reliability prediction of each system component, including modeling and simulation with HOMER and MATLAB - Discusses the use of Big Data analysis, numerical methods, and Game Theory for plant assessment

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 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.