Vikas Khare - Böcker

Tidal Energy Systems: Design, Optimization and Control provides a comprehensive overview of concepts, technologies, management and the control of tidal energy systems and tidal power plants. It presents the fundamentals of tidal energy, including the structure of tidal currents and turbulence. Technology, principles, components, operation, and a performance assessment of each component are also covered. Other sections consider pre-feasibility analysis methods, plant operation, maintenance and power generation, reliability assessment in terms of failure distribution, constant failure rate and the time dependent failure model. Finally, the most recent research advances and future trends are reviewed.

In addition, applicable real-life examples and a case study of India's tidal energy scenario are included. The book provides ocean energy researchers, practitioners and graduate students with all the information needed to design, deploy, manage and operate tidal energy systems. Senior undergraduate students will also find this to be a useful resource on the fundamentals of tidal energy systems and their components.

Presents the fundamentals of tidal energy, including system components, pre-feasibility analysis, and plant management, operations and control Explores concepts of sustainability and a reliability analysis of tidal energy systems, as well as their economic aspects and future trends Covers the assessment of tidal energy systems by optimization technique and game theory

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

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

Decision Science and Operations Management of Solar Energy System looks beyond developing a solar power plant by also considering the requirements necessary to manage effective power plant operation for the long-term. This book includes data of solar power plants and quantitative techniques of statistical analysis used to inform decision-making for solar energy systems, thus enabling readers to predict future individual solar power system forecasts using different technical and financial parameters. Including data visualization, descriptive statistics, sampling techniques, plant layout, manufacturing economics, inventory management and total quality management of solar energy system, this book covers new insights as well as established fundamentals.

The detailed information in this reference bridges the gap between theory and practice in the operation of solar energy systems for researchers, professionals and students working in the area of solar and renewable energy.

Features a pre-feasibility assessment of a solar system by data visualization Details the technical parameters of a solar system by probability and sampling techniques Analyzes the relationship between different parameters of a solar system

Cognitive Science, Computational Intelligence, and Data Analytics: Methods and Applications with Python introduces readers to the foundational concepts of data analysis, cognitive science, and computational intelligence, including AI and Machine Learning. The book's focus is on fundamental ideas, procedures, and computational intelligence tools that can be applied to a wide range of data analysis approaches, with applications that include mathematical programming, evolutionary simulation, machine learning, and logic-based models. It offers readers the fundamental and practical aspects of cognitive science and data analysis, exploring data analytics in terms of description, evolution, and applicability in real-life problems.The authors cover the history and evolution of cognitive analytics, methodological concerns in philosophy, syntax and semantics, understanding of generative linguistics, theory of memory and processing theory, structured and unstructured data, qualitative and quantitative data, measurement of variables, nominal, ordinals, intervals, and ratio scale data. The content in this book is tailored to the reader's needs in terms of both type and fundamentals, including coverage of multivariate analysis, CRISP methodology and SEMMA methodology. Each chapter provides practical, hands-on learning with real-world applications, including case studies and Python programs related to the key concepts being presented.Demystifies the theory of data analytics using a step-by-step approachCovers the intersection of cognitive science, computational intelligence, and data analytics by providing examples and case studies with applied algorithms, mathematics, and Python programming codeIntroduces foundational data analytics techniques such as CRISP-DM, SEMMA, and Object Detection Models in the context of computational intelligence methods and toolsCovers key concepts of multivariate and cognitive data analytics such as factor analytics, principal component analytics, linear regression analysis, logistic regression analysis, and value chain applications

Comprehensive examination of green hydrogen’s transformative potential in reducing carbon emissions across various sectors Hydrogen Technologies in Decarbonizing Industries and Energy Systems is a thorough discussion of green hydrogen’s transformative potential in reducing carbon emissions across various sectors, covering technological, managerial, and policy aspects. Practical insights are provided through detailed case studies and real-world examples to ensure concepts are relatable and practicable. The book begins by introducing the fundamentals of green hydrogen, tracing its historical development, and explaining its critical role in global decarbonization efforts. It then delves into the latest technological innovations, such as advancements in electrolysis, storage, transportation, and integration with renewable energy sources. Discussion on industrial applications highlights how green hydrogen can decarbonize heavy industries like steel, cement, and chemicals, and explains its use in transportation and power generation. From a management perspective, the book explores strategic planning for adopting green hydrogen, operational changes, supply chain management, workforce development, and risk management. The book also includes information on: The current policy and regulatory landscape, identifying challenges and offering recommendations to promote green hydrogen adoptionCost-benefit aspects of green hydrogen projects, investment trends, and the global economic impact of this technologyEnvironmental and social impacts of green hydrogen, including job creation and community effectsEnergy conservation and demand response, covering smart thermostats and peak load managementThermochemical water splitting, covering splitting cycles, reaction materials and catalysts, process engineering and reactor design and energy input and efficiencyHydrogen Technologies in Decarbonizing Industries and Energy Systems empowers industry professionals, policymakers, and researchers and academics to contribute to the decarbonization of industries and energy systems, fostering a sustainable future for all.