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Symmetry in Renewable Energy and Power Systems
This book includes original research papers related to renewable energy and power systems in which theoretical or practical issues of symmetry are considered. The book includes contributions on voltage stability analysis in DC networks, optimal dispatch of islanded microgrid systems, reactive power compensation, direct power compensation, optimal location and sizing of photovoltaic sources in DC networks, layout of parabolic trough solar collectors, topologic analysis of high-voltage transmission grids, geometric algebra and power systems, filter design for harmonic current compensation. The contributions included in this book describe the state of the art in this field and shed light on the possibilities that the study of symmetry has in power grids and renewable energy systems.
Symmetry in Engineering Sciences II
This book presents a sample of theoretical and practical advances in symmetry in multidisciplinary engineering applications. It covers several applications, such as mechanical analysis of tunnel lining, prediction methods for the ring damper used in gears, calibration methods for manipulators, design methods for wheel configurations of mobile robots, analysis of elastic plastic damaged zones, 3D printed corneal models, analysis of multibody system dynamic networks, structural elements in architecture, railway transportation, transportation of hazardous materials, cable-driven mechanisms, and image processing. The contributions included in this book describe the state-of-the-art advances in this field and demonstrate the possibilities of the study of symmetry in multidisciplinary applications in the field of engineering.
Monitoring and Control of Electrical Power Systems using Machine Learning Techniques
Monitoring and Control of Electrical Power Systems using Machine Learning Techniques bridges the gap between advanced machine learning techniques and their application in the control and monitoring of electrical power systems, particularly relevant for heavily distributed energy systems and real-time application. The book reviews key applications of deep learning, spatio-temporal, and advanced signal processing methods for monitoring power quality. This reference introduces guiding principles for the monitoring and control of power quality disturbances arising from integration of power electronic devices and discusses monitoring and control of electrical power systems using benchmark test sy...
Optimization Methods Applied to Power Systems
This book presents an interesting sample of the latest advances in optimization techniques applied to electrical power engineering. It covers a variety of topics from various fields, ranging from classical optimization such as Linear and Nonlinear Programming and Integer and Mixed-Integer Programming to the most modern methods based on bio-inspired metaheuristics. The featured papers invite readers to delve further into emerging optimization techniques and their real application to case studies such as conventional and renewable energy generation, distributed generation, transport and distribution of electrical energy, electrical machines and power electronics, network optimization, intelligent systems, advances in electric mobility, etc.
Symmetry in Engineering Sciences
This book presents interesting samples of theoretical and practical advances of symmetry in multidisciplinary engineering applications. It covers several applications, such as accessibility and traffic congestion management, path planning for mobile robots, analysis of shipment service networks, fault diagnosis methods in electrical circuits and electrical machines, geometrical issues in architecture, geometric modeling and virtual reconstruction, design of noise detectors, filters, and segmentation methods for image processing, and cyclic symmetric structures in turbomachinery applications, to name but a few. The contributions included in this book depict the state of the art in this field and lay the foundation for the possibilities that the study of symmetry has in multidisciplinary applications in the field of engineering.
Prediction Techniques for Renewable Energy Generation and Load Demand Forecasting
This book provides an introduction to forecasting methods for renewable energy sources integrated with existing grid. It consists of two sections; the first one is on the generation side forecasting methods, while the second section deals with the different ways of load forecasting. It broadly includes artificial intelligence, machine learning, hybrid techniques and other state-of-the-art techniques for renewable energy and load predictions. The book reflects the state of the art in distributed generation system and future microgrids and covers theory, algorithms, simulations and case studies. It offers invaluable insights through this valuable resource to students and researchers working in the fields of renewable energy, integration of renewable energy with existing grid and electrical distribution network.
Surfaces and Interfaces for Renewable Energy
Environmental problems derived from the massive use of conventional energy resources are one of the main issues that our society has been facing in recent decades. Renewable energies (and particularly solar energy) have become a highly competitive means to meet the world’s increasing energy demands in a sustainable and clean manner. One of the key research challenges for the commercial deployment of several solar energy technologies is focused on the development of feasible and durable coatings that withstand appropriate optical and thermal performance over the lifetime of the solar facilities. This book addresses a number of relevant aspects related to coatings for renewable energies, inc...
Operation of Smart Homes
This book presents the latest research advancements in the operation of smart homes. It comprises new operation techniques including cooperative distributed energy scheduling, framework to react to malicious cyberattacks, framework for demand-side management, and framework for the design of smart homes to support residents’ wellness as well as new optimization techniques such as stochastic model predictive control and multi-time scale optimization. In addition, the book analyzes 11,000 studies that have been indexed in scientific databases and categorizes them based on various data points, including the field and the subject of the research, the name of the institutions, and the nationality of the authors. Presents new operation techniques of smart homes; Introduces new optimization techniques for operation of smart homes; Analyses 11,000 studies and categorizes them based on different data points.
Bioengineering and Biomedical Signal and Image Processing
This book constitutes the refereed proceedings of the First International Conference on Bioengineering and Biomedical Signal and Image Processing, BIOMESIP 2021, held in Meloneras, Gran Canaria, Spain, in July 2021. The 41 full and 5 short papers were carefully reviewed and selected from 121 submissions. The papers are grouped in topical issues on biomedical applications in molecular, structural, and functional imaging; biomedical computing; biomedical signal measurement, acquisition and processing; computerized medical imaging and graphics; disease control and diagnosis; neuroimaging; pattern recognition and machine learning for biosignal data; personalized medicine; and COVID-19.
Nature Inspired Computing for Data Science
This book discusses the current research and concepts in data science and how these can be addressed using different nature-inspired optimization techniques. Focusing on various data science problems, including classification, clustering, forecasting, and deep learning, it explores how researchers are using nature-inspired optimization techniques to find solutions to these problems in domains such as disease analysis and health care, object recognition, vehicular ad-hoc networking, high-dimensional data analysis, gene expression analysis, microgrids, and deep learning. As such it provides insights and inspiration for researchers to wanting to employ nature-inspired optimization techniques in their own endeavors.
