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Books in Electric power control and instrumentation

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    • Intelligent Control in Smart Energy Systems

      • 1st Edition
      • April 1, 2026
      • Satya Prakash Yadav + 3 more
      • English
      • Paperback
        9 7 8 0 4 4 3 3 3 4 6 3 4
      • eBook
        9 7 8 0 4 4 3 3 3 4 6 4 1
      Intelligent Control in Smart Energy Systems provides a clear and practical guide to the implementation of Artificial Intelligent (AI) techniques in modern, sustainable energy systems. Building from essential theory to advanced application processes, this book outlines the essential challenge of control for renewable and distributed energy sources and applies a range of AI solutions from deep learning, data-driven decision-making, advanced control, and optimization algorithms for smart grids. Case studies and latest results cover control across design, development, and operation of smart energy systems, touching on control in generation, distribution, and supply.Catering to newly interdisciplinary researchers as well as those with a basic understanding of AI technologies, this book supports higher-stage undergraduates, graduate students, researchers, and system engineers in implementing best practice control techniques for a sustainable energy grid.

    • Handbook of Artificial Intelligence Applications in Energy Systems

      • 1st Edition
      • March 1, 2026
      • Mir Sayed Shah Danish
      • English
      • Paperback
        9 7 8 0 4 4 3 3 6 6 8 8 8
      • eBook
        9 7 8 0 4 4 3 3 6 6 8 9 5
      ‘Handbook of Artificial Intelligence Applications in Energy Systems: Practical Techniques and Case Studies’ is a practical, step-by-step guidebook for integrating AI into energy systems, from foundational theories to hands-on implementation strategies. This book begins with the foundational principles and history of AI in Energy Systems, including fundamental methods for data preprocessing. A variety of optimization and control strategies are introduced in detail, including advanced methods (Adam, RMSprop, AdaGrad); next, machine learning techniques, libraries, and implementation strategies are broken down in depth. Modeling methods, evaluation metrics, deployment, and interpretability are addressed, before deep learning neural networks from CNNs to GANs, and finally hardware and software requirements for deploying AI in energy systems, including GPU/TPU usage, distributed training, and data storage solution. Packed with case studies, worked numerical examples, and practical tips for research and implementation in the area, the ‘Handbook of Artificial Intelligence Applications in Energy Systems’ brings the reader quickly up to speed with the practical opportunities of this critical technology in modern energy systems.

    • Power Converters for Photovoltaic Power Systems

      • 1st Edition
      • March 1, 2026
      • Ahteshamul Haque + 3 more
      • English
      • Paperback
        9 7 8 0 4 4 3 2 9 1 8 4 5
      • eBook
        9 7 8 0 4 4 3 2 9 1 8 5 2
      Power Converters for Photovoltaic Power Systems: Control, Fault Diagnosis, and Reliability Analysis guides readers through the latest technologies and applications of advanced converters for the renewable-integrated energy systems of the future. The book begins with an introduction to the design principles of converters for PV applications and grid synchronization techniques before breaking down complex control strategies for PV systems, including the injection of active and reactive power in solar inverters. Fault detection, analysis, and localization are covered in detail, as are failure modes, risk indices, criticality analysis, and more advanced condition monitoring techniques.Additiona... chapters cover optimizing thermal management to ensure efficient operation and reliability of photovoltaic systems, and thermal control methods for reliable operation and longevity of power electronic converters. Finally, guidance is provided on Digital Twin Integration for condition monitoring of photovoltaic-integra... energy systems.

    • Machine Learning and Data Analysis for Energy Efficiency in Buildings

      • 1st Edition
      • September 26, 2025
      • Tianyi Zhao + 2 more
      • English
      • Paperback
        9 7 8 0 4 4 3 2 8 9 5 3 8
      • eBook
        9 7 8 0 4 4 3 2 8 9 5 4 5
      Machine Learning and Data Analysis for Energy Efficiency in Buildings: Intelligent Operation, Maintenance, and Optimization of Building Energy Systems introduces data basics, from selecting and evaluating data to the identification and repair of abnormalities. Other sections cover data mining applied to energy forecasting, including long- and short-term predictions, the introduction of occupant-focused behavior analysis, and current methods for supply and demand applications. Case studies are included in each part to assist in evaluation and implementation of these techniques across building energy systems.Working from the fundamentals of big data analysis to a complete method for building energy assessment, flexibility, and management, this book provides students, researchers, and professionals with an essential, cutting-edge resource on this important technology.

    • Energy-Efficient Transformative Technologies for Data-Driven Smart Cities

      • 1st Edition
      • November 10, 2025
      • Hamed Nozari + 1 more
      • English
      • Paperback
        9 7 8 0 4 4 3 2 7 6 1 8 7
      • eBook
        9 7 8 0 4 4 3 2 7 6 1 9 4
      Energy-Efficient Transformative Technologies for Data-Driven Smart Cities delves into innovative solutions and groundbreaking methodologies essential for constructing smart cities that prioritize energy efficiency and security. With the modern urban landscape rapidly evolving, this book serves as a vital resource for policymakers, engineers, and researchers striving to harness data-driven technologies effectively. From sustainable energy systems to advanced data management frameworks, this comprehensive guide explores pivotal tools and strategies that address the challenges of urbanization and environmental impact.Beyond energy efficiency, the book emphasizes the importance of robust cybersecurity measures, seamless integration of IoT devices, and intelligent urban planning. It offers actionable insights for achieving smart city infrastructures that are both resilient and adaptive.

    • The PyPSA Handbook

      • 1st Edition
      • December 1, 2025
      • Neeraj Dhanraj Bokde + 1 more
      • English
      • Paperback
        9 7 8 0 4 4 3 2 6 6 3 1 7
      • eBook
        9 7 8 0 4 4 3 2 6 6 3 2 4
      The PyPSA Handbook: Integrated Power System Analysis and Renewable Energy Modeling is a comprehensive guide to the landmark open-source platform for modeling modern energy systems. Starting from core concepts in energy system analysis, the book builds a clear theoretical foundation before progressing to advanced topics such as renewable integration, storage, grid expansion, system stability, and future developments. Designed for both newcomers and experienced users, it features layered examples, hands-on exercises, and real-world case studies. This book is an indispensable resource for students, researchers, and energy professionals.

    • Switchgear Design, Operation, and Maintenance Using Industry Standards

      • 1st Edition
      • April 18, 2025
      • Gyan Ranjan Biswal + 1 more
      • English
      • Paperback
        9 7 8 0 4 4 3 2 4 7 1 8 7
      • eBook
        9 7 8 0 4 4 3 2 4 7 1 9 4
      ‘Switchgear Design, Operation, and Maintenance using Industry Standards: Protective Mechanisms, Sensing Technology, and Communication Standards’ is a practical handbook from both industry experts and academics covering the latest developments in switchgear.This book breaks down cutting-edge practical techniques according to the hierarchy of switchgear operations, with an emphasis on critical technologies for automation in the energy transition. Following a helpful refresher on switchgear fundamentals, Part I examines essential safety considerations from fault identification and resolution to DC-type circuit breakers and other protective mechanisms. Part II sets out operating principles and testing procedures for reliable smart substations, including communication protocols, validation, and cyber-security. Finally, Part III considers essential operational maintenance such as circuit-breaker maintenance, and the critical function of high-voltage DC switchgear for the energy transition.An up-to-date helping hand for the transfer from university programs to industry, ‘Switchgear Design, Operation, and Maintenance using Industry Standards’ will allow professionals to design, operate, and maintain the smart, automated substations the energy transition needs.

    • Development of Electric Vehicles in Smart Grid Concepts

      • 1st Edition
      • August 1, 2025
      • Supriya Jaiswal + 2 more
      • English
      • Paperback
        9 7 8 0 4 4 3 3 0 1 4 0 7
      • eBook
        9 7 8 0 4 4 3 3 0 1 4 1 4
      Development of Electric Vehicles in Smart Grid Concepts presents a guide to the design, development, and deployment of electric vehicles in smart grids. The book examines the current technological progression of power electronic converters for smart grid operation and EV technology as well as providing the international standards, policies, and market needs to ensure readers understand the nuanced requirements of the grid. The book begins by introducing EVs, encompassing their historical evolution, current status, and potential advancements. It delves into the architecture, components, working modes, and technological challenges within EVs.There is a dedicated chapter on international standards, governmental policies, and codes for implementation, followed by the integration of EVs into smart grids, discussing infrastructure requirements, impacts, and integration modes (V2G, G2V, V2B, and V2H). Technical aspects, modeling, and optimization methods for EV scheduling are explored alongside battery modeling, degradation, charging standards, SOC estimation, and battery management systems. Additionally, the book examines EV interaction with smart grids, renewable energy sources, energy storage systems, global market surveys, and future trends.

    • Intelligent Data Analytics for Solar Energy Prediction and Forecasting

      • 1st Edition
      • June 26, 2025
      • Amit Kumar Yadav + 2 more
      • English
      • Paperback
        9 7 8 0 4 4 3 1 3 4 8 2 1
      • eBook
        9 7 8 0 4 4 3 1 3 4 8 3 8
      Intelligent Data Analytics for Solar Energy Prediction and Forecasting: Advances in Resource Assessment and PV Systems Optimization explores the utilization of advanced neural networks, machine learning and data analytics techniques for solar radiation prediction, solar energy forecasting, installation and maximum power generation. The book addresses relevant input variable selection, solar resource assessment, tilt angle calculation, and electrical characteristics of PV modules, including detailed methods, coding, modeling and experimental analysis of PV power generation under outdoor conditions. It will be of interest to researchers, scientists and advanced students across solar energy, renewables, electrical engineering, AI, machine learning, computer science, information technology and engineers. In addition, R&D professionals and other industry personnel with an interest in applications of AI, machine learning, and data analytics within solar energy and energy systems will find this book to be a welcomed resource.

    • Reliable Non-Parametric Techniques for Energy System Operation and Control

      • 1st Edition
      • July 4, 2025
      • Hongcai Zhang + 3 more
      • English
      • Paperback
        9 7 8 0 4 4 3 3 6 4 9 2 1
      • eBook
        9 7 8 0 4 4 3 3 6 4 9 3 8
      Reliable Non-Parametric Techniques for Energy System Operation and Control: Fundamentals and Applications of Constraint Learning and Safe Reinforcement Learning Methods, a new Volume in the Advances in Intelligent Energy Systems, is a comprehensive guide to modern smart methods in energy system operation and control. This book covers fundamental concepts and applications in both deterministic and uncertain environments. It addresses the challenge of accuracy in imbalanced datasets and the limitations of measurements. The book delves into advanced topics such as safe reinforcement learning for energy system control, including training-efficient intrinsic-motivated reinforcement learning, and physical layer-based control, and more. Other chapters cover barrier function-based control and CVaR-based control for systems without hard operation constraints. Designed for graduate students, researchers, and engineers, this book stands out for its practical approach to advanced methods in energy system control, enabling sustainable developments in real-world conditions.