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Artificial Intelligence for Renewable Energy Systems
ARTIFICIAL INTELLIGENCE FOR RENEWABLE ENERGY SYSTEMS Renewable energy systems, including solar, wind, biodiesel, hybrid energy, and other relevant types, have numerous advantages compared to their conventional counterparts. This book presents the application of machine learning and deep learning techniques for renewable energy system modeling, forecasting, and optimization for efficient system design. Due to the importance of renewable energy in today’s world, this book was designed to enhance the reader’s knowledge based on current developments in the field. For instance, the extraction and selection of machine learning algorithms for renewable energy systems, forecasting of wind and so...
Supervised Machine Learning in Wind Forecasting and Ramp Event Prediction
Supervised Machine Learning in Wind Forecasting and Ramp Event Prediction provides an up-to- date overview on the broad area of wind generation and forecasting, with a focus on the role and need of Machine Learning in this emerging field of knowledge. Various regression models and signal decomposition techniques are presented and analyzed, including least-square, twin support and random forest regression, all with supervised Machine Learning. The specific topics of ramp event prediction and wake interactions are addressed in this book, along with forecasted performance. Wind speed forecasting has become an essential component to ensure power system security, reliability and safe operation, making this reference useful for all researchers and professionals researching renewable energy, wind energy forecasting and generation. - Features various supervised machine learning based regression models - Offers global case studies for turbine wind farm layouts - Includes state-of-the-art models and methodologies in wind forecasting
Supervised Machine Learning in Wind Forecasting and Ramp Event Prediction
Supervised Machine Learning in Wind Forecasting and Ramp Event Prediction provides an up-to- date overview on the broad area of wind generation and forecasting, with a focus on the role and need of Machine Learning in this emerging field of knowledge. Various regression models and signal decomposition techniques are presented and analyzed, including least-square, twin support and random forest regression, all with supervised Machine Learning. The specific topics of ramp event prediction and wake interactions are addressed in this book, along with forecasted performance. Wind speed forecasting has become an essential component to ensure power system security, reliability and safe operation, making this reference useful for all researchers and professionals researching renewable energy, wind energy forecasting and generation.
Decision and Control in Hybrid Wind Farms
This book focuses on two of the most important aspects of wind farm operation: decisions and control. The first part of the book deals with decision-making processes, and explains that hybrid wind farm operation is governed by a set of alternatives that the wind farm operator must choose from in order to achieve optimal delivery of wind power to the utility grid. This decision-making is accompanied by accurate forecasts of wind speed, which must be known beforehand. Errors in wind forecasting can be compensated for by pumping power from a reserve capacity to the grid using a battery energy storage system (BESS). Alternatives based on penalty cost are assessed using certain criteria, and MCDM...
Innovations in Infrastructure
The book covers innovative research and its applications in infrastructure development and related areas. This book discusses the state-of-art development, challenges and unsolved problems in the field of infrastructure/smart development, control engineering, power system infrastructure, smart infrastructure, waste management and renewable energy. The solutions discussed in this book encourage the researchers and IT professionals to put the methods into their practice.
Wind and Solar Energy Applications
This book examines the recent advances, from theoretical and applied perspectives, addressing the major issues associated with renewable energy systems, with each chapter covering fundamental issues and latest developments. This book covers important themes, including solar energy equipment, wind and solar energy systems, energy storage and bioenergy applications, hybrid renewable energy systems, as well as the measurement techniques that are used for these systems. Further, it focusses on original research outcomes on various technological developments and provides insights to taxonomy of challenges, issues, and research directions in renewable energy applications. Features: Covers research...
Renewable Energy Technologies
RENEWABLE ENERGY TECHNOLOGIES With the goal of accelerating the growth of green energy utilization for the sustainability of life on earth, this volume, written and edited by a global team of experts, goes into the practical applications that can be utilized across multiple disciplines and industries, for both the engineer and the student. Green energy resources are gaining more attention in academia and industry as one of the preferred choices for sustainable energy conversion. Due to the energy demand, environmental impacts, economic needs, and social issues, green energy resources are being researched, developed, and funded more than ever before. Researchers are facing numerous challenges...
Neural Networks, Machine Learning, and Image Processing
SECTION I Mathematical Modeling and Neural Network’ Mathematical Essence Chapter 1 Mathematical Modeling on Thermoregulation in Sarcopenia 1.1. Introduction 1.2. Discretization 1.3. Modeling and Simulation of Basal Metabolic Rate and Skin Layers Thickness 1.4. Mathematical Model and Boundary Conditions 1.5. Solution of the Model 1.6. Numerical Results and discussion 1.7. Conclusion References Chapter 2 Multi-objective University Course Scheduling for Uncertainly Generated Courses 2.1 Introduction 2.2 Literature review 2.3 Formulation of problem 2.4 Methodology 2.5 Numerical Example 2.6 Result and Discussion 2.7 Conclusion References Chapter 3 MChCNN : A Deep Learning Approach to Detect Tex...
Soft Computing: Theories and Applications
This book focuses on soft computing and how it can be applied to solve real-world problems arising in various domains, ranging from medicine and health care, to supply chain management, image processing and cryptanalysis. It gathers high-quality papers presented at the International Conference on Soft Computing: Theories and Applications (SoCTA 2022), held at University Institute of Technology, Himachal Pradesh University Shimla, Himachal Pradesh, India. The book offers valuable insights into soft computing for teachers and researchers alike; the book inspires further research in this dynamic field.
Futuristic Sustainable Energy & Technology
Futuristic Sustainable Energy and Technology provides a structured overview of the concept of Futuristic Sustainable Energy and Technology. It also explores the promotion of the sustainable development of renewable energy from the perspectives of technology, modelling, application, sustainability and policy. This book is dedicated to the advancement of energy efficiency to mitigate consumption, ensure and replenish, expand and reuse elective energy supplies, and to replicate the damage caused by previous energy initiatives. This book has offered a large stage of experimentation for practitioners, experts, researchers and teachers to incorporate and analyze their latest developments, as well as the trends and difficulties encountered and the ongoing evolution of the stage in these areas.
