Soteris Kalogirou – författare

Thermal Solar Desalination: Methods and Systems presents numerous thermal seawater desalination technologies varying from the very simple, easy to construct and operate solar stills, to the more advance membrane and indirect distillation methods. All types of solar thermal desalination technologies are presented in detail to enable readers to comprehend the subject, from design details to enabling further research to be carried out in this area.

The various units used in desalination are outlined, along with diagrams of all detailed working principles of desalination methods and systems. The authors consider the economic aspects of these processes, demonstrating successful implementation of desalination units suitable for areas where supplies of fresh water in natural ways is limited or non-existent.

Includes detailed descriptions and design of all types of solar thermal desalination systems Lists a comprehensive record of seawater and fresh water thermophysical properties required in the design of desalination systems Contains equations to calculate and analyze the performance of the processes examined and assesses their practicality and application

Handbook of Artificial Intelligence Techniques in Photovoltaic Systems: Modelling, Control, Optimization, Forecasting and Fault Diagnosis provides readers with a comprehensive and detailed overview of the role of artificial intelligence in PV systems. Covering up-to-date research and methods on how, when and why to use and apply AI techniques in solving most photovoltaic problems, this book will serve as a complete reference in applying intelligent techniques and algorithms to increase PV system efficiency. Sections cover problem-solving data for challenges, including optimization, advanced control, output power forecasting, fault detection identification and localization, and more.Supported by the use of MATLAB and Simulink examples, this comprehensive illustration of AI-techniques and their applications in photovoltaic systems will provide valuable guidance for scientists and researchers working in this area. Includes intelligent methods in real-time using reconfigurable circuits FPGAs, DSPs and MCs Discusses the newest trends in AI forecasting, optimization and control applications Features MATLAB and Simulink examples highlighted throughout

Green Hydrogen Energy Systems explores the vital technologies and methods for generating, storing, and utilizing green hydrogen. By adopting an energy systems approach, the book offers a comprehensive review of green hydrogen systems, integrating principles, configurations, progress, and applications, bolstered by technoeconomic analyses and performance data. Addressing common challenges, it explains processes for developing and constructing basic and advanced green hydrogen systems. The book details the fundamentals of hydrogen technologies, including thermodynamics, kinetics, energy loss mechanisms, and costs.It covers aspects such as heat release, clean water usage in electrolyzers, system configurations, and includes real-world performance data, case studies, hydrogen hubs, safety, and economics.Presents a systems approach to hydrogen energyProvides in-depth analysis of all key green hydrogen energy systems and related technologies, with all content supported by performance dataOffers technoeconomic analyses, design and operation modes, and integration mechanisms for green hydrogen energy systems

Soft Computing in Green and Renewable Energy Systems provides a practical introduction to the application of soft computing techniques and hybrid intelligent systems for designing, modeling, characterizing, optimizing, forecasting, and performance prediction of green and renewable energy systems. Research is proceeding at jet speed on renewable energy (energy derived from natural resources such as sunlight, wind, tides, rain, geothermal heat, biomass, hydrogen, etc.) as policy makers, researchers, economists, and world agencies have joined forces in finding alternative sustainable energy solutions to current critical environmental, economic, and social issues. The innovative models, environmentally benign processes, data analytics, etc. employed in renewable energy systems are computationally-intensive, non-linear and complex as well as involve a high degree of uncertainty. Soft computing technologies, such as fuzzy sets and systems, neural science and systems, evolutionary algorithms and genetic programming, and machine learning, are ideal in handling the noise, imprecision, and uncertainty in the data, and yet achieve robust, low-cost solutions. As a result, intelligent and soft computing paradigms are finding increasing applications in the study of renewable energy systems. Researchers, practitioners, undergraduate and graduate students engaged in the study of renewable energy systems will find this book very useful.