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Smart Energy Management: A Computational Approach

Smart Energy Management: A Computational Approach
Author: Krithi Ramamritham
Publisher: World Scientific
Total Pages: 312
Release: 2021-12-28
Genre: Science
ISBN: 9811252300

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The focus of this book is smart energy management with the recurring theme being the use of computational and data-driven methods that use requirements/measurement/monitoring data to drive actuation/control, optimization, and resource management. The computational perspective is applied to manage energy, with an emphasis on smart buildings and the smart electric grids.The book also presents computational thinking and techniques such as inferencing and learning for energy management. To this end, this book is designed to help understand the recent research trends in energy management, focusing specifically on the efforts to increase energy efficiency of buildings, campuses, and cities.


Smart Energy Management

Smart Energy Management
Author: Kaile Zhou
Publisher: Springer Nature
Total Pages: 317
Release: 2022-02-04
Genre: Business & Economics
ISBN: 9811693609

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This book provides a relatively whole view of data-driven decision-making methods for energy service innovation and energy system optimization. Through personalized energy services provision and energy efficiency improvement, the book can contribute to the green transformation of energy system and the sustainable development of the society. The book gives a new way to achieve smart energy management, based on various data mining and machine learning methods, including fuzzy clustering, shape-based clustering, ensemble clustering, deep learning, and reinforcement learning. The applications of these data-driven methods in improving energy efficiency and supporting energy service innovation are presented. Moreover, this book also investigates the role of blockchain in supporting peer-to-peer (P2P) electricity trading innovation, thus supporting smart energy management. The general scope of this book mainly includes load clustering, load forecasting, price-based demand response, incentive-based demand response, and energy blockchain-based electricity trading. The intended readership of the book includes researchers and engineers in related areas, graduate and undergraduate students in university, and some other general interested audience. The important features of the book are: (1) it introduces various data-driven methods for achieving different smart energy management tasks; (2) it investigates the role of data-driven methods in supporting various energy service innovation; and (3) it explores energy blockchain in P2P electricity trading, and thus supporting smart energy management.


Energy Management—Collective and Computational Intelligence with Theory and Applications

Energy Management—Collective and Computational Intelligence with Theory and Applications
Author: Cengiz Kahraman
Publisher: Springer
Total Pages: 554
Release: 2018-03-21
Genre: Technology & Engineering
ISBN: 3319756907

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This book presents a selection of recently developed collective and computational intelligence techniques, which it subsequently applies to energy management problems ranging from performance analysis to economic analysis, and from strategic analysis to operational analysis, with didactic numerical examples. As a form of intelligence emerging from the collaboration and competition of individuals, collective and computational intelligence addresses new methodological, theoretical, and practical aspects of complex energy management problems. The book offers an excellent reference guide for practitioners, researchers, lecturers and postgraduate students pursuing research on intelligence in energy management. The contributing authors are recognized researchers in the energy research field.


Building Energy Management Systems and Techniques

Building Energy Management Systems and Techniques
Author: Fengji Luo
Publisher: Elsevier
Total Pages: 334
Release: 2024-03-01
Genre: Technology & Engineering
ISBN: 032399301X

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Building Energy Management Systems and Techniques: Principles, Methods, and Modelling presents basic concepts, methodologies, modeling techniques, and fundamental design schemes of building energy management systems. Covering the latest developments and methodologies from academia and industry, the book brings together energy management, demand response, evolutionary computation, and fundamental programming. The authors explore the basic concepts related to building energy management systems and put them into the context of smart grids, demand response and demand-side management, internet of things, and distributed renewable energy. Advanced topics provide the reader with an understanding of various energy management scenarios and procedures for modern buildings in an automatic and highly renewable-penetrated building environment. This includes a range of energy management techniques for building-side energy resources such as battery energy storage systems, plug-in appliances, and HVAC systems. The fundamental principles of evolutionary computation are covered and applied to building energy management problems. The authors also introduce the paradigm of occupant-to-grid integration and its implementation through personalized recommendation technology to guide the occupants’ choices on energy-related products and their energy usage behaviors, as well as to enhance the energy efficiency of buildings. The book includes several application examples throughout, illustrating for the reader the key aspects involved in the implementation of building energy management schemes. Building Energy Management Systems and Techniques is an invaluable resource for undergraduate and postgraduate students enrolled in courses related to energy-efficient building systems and smart grids and researchers working in the fields of smart grids, smart buildings/homes, and energy demand response. The book will be of use to professional electrical, civil, computing, and communications engineers, architects, and building energy consultants. Integrates the latest techniques in the building energy management paradigm, such as appliance scheduling, peer-to-peer energy trading, and occupant-to-grid integration Provides extensive application examples to help readers understand the design principles of different building energy management systems Includes step-by-step guidance on the methods, modeling techniques, and applications presented in the book, including evolutionary computations Provides pseudocodes and optimization algorithms for the application examples to enable the reader to gain insight into the modeling details


Smart Energy Management for Smart Grids

Smart Energy Management for Smart Grids
Author: Khmaies Ouahada
Publisher: MDPI
Total Pages: 350
Release: 2020-03-16
Genre: Technology & Engineering
ISBN: 3039281429

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This book is a contribution from the authors, to share solutions for a better and sustainable power grid. Renewable energy, smart grid security and smart energy management are the main topics discussed in this book.


Hybrid Intelligent Approaches for Smart Energy

Hybrid Intelligent Approaches for Smart Energy
Author: Senthil Kumar Mohan
Publisher: John Wiley & Sons
Total Pages: 341
Release: 2022-11-08
Genre: Computers
ISBN: 111982124X

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HYBRID INTELLIGENT APPROACHES FOR SMART ENERGY Green technologies and cleaner energy are two of the most important topics facing our world today, and the march toward efficient energy systems, smart cities, and other green technologies, has been, and continues to be, a long and intricate one. Books like this one keep the veteran engineer and student, alike, up to date on current trends in the technology and offer a reference for the industry for its practical applications. Energy optimization and consumption prediction are necessary to prevent energy waste, schedule energy usage, and reduce the cost. Today, smart computing technologies are slowly replacing the traditional computational methods in energy optimization, consumption, scheduling, and usage. Smart computing is an important core technology in today’s scientific and engineering environment. Smart computation techniques such as artificial intelligence, machine learning, deep learning and Internet of Things (IoT) are the key role players in emerging technologies across different applications, industries, and other areas. These newer, smart computation techniques are incorporated with traditional computation and scheduling methods to reduce power usage in areas such as distributed environment, healthcare, smart cities, agriculture and various functional areas. The scope of this book is to bridge the gap between traditional power consumption methods and modern consumptions methods using smart computation methods. This book addresses the various limitations, issues and challenges of traditional energy consumption methods and provides solutions for various issues using modern smart computation technologies. These smart technologies play a significant role in power consumption, and they are cheaper compared to traditional technologies. The significant limitations of energy usage and optimizations are rectified using smart computations techniques, and the computation techniques are applied across a wide variety of industries and engineering areas. Valuable as reference for engineers, scientists, students, and other professionals across many areas, this is a must-have for any library.


Big Data Analytics

Big Data Analytics
Author: P. Krishna Reddy
Publisher: Springer
Total Pages: 316
Release: 2017-12-04
Genre: Computers
ISBN: 3319724134

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This book constitutes the refereed conference proceedings of the 5th International Conference on Big Data Analytics, BDA 2017, held in Hyderabad, India, in December 2017. The 21 revised full papers were carefully reviewed and selected from 80 submissions and cover topics on big data analytics, information and knowledge management, mining of massive datasets, computational modeling, data mining and analysis.


Smart Energy Grid Engineering

Smart Energy Grid Engineering
Author: Hossam Gabbar
Publisher: Academic Press
Total Pages: 568
Release: 2016-10-12
Genre: Science
ISBN: 0128092327

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Smart Energy Grid Engineering provides in-depth detail on the various important engineering challenges of smart energy grid design and operation by focusing on advanced methods and practices for designing different components and their integration within the grid. Governments around the world are investing heavily in smart energy grids to ensure optimum energy use and supply, enable better planning for outage responses and recovery, and facilitate the integration of heterogeneous technologies such as renewable energy systems, electrical vehicle networks, and smart homes around the grid. By looking at case studies and best practices that illustrate how to implement smart energy grid infrastructures and analyze the technical details involved in tackling emerging challenges, this valuable reference considers the important engineering aspects of design and implementation, energy generation, utilization and energy conservation, intelligent control and monitoring data analysis security, and asset integrity. Includes detailed support to integrate systems for smart grid infrastructures Features global case studies outlining design components and their integration within the grid Provides examples and best practices from industry that will assist in the migration to smart grids


Applied Operations Research and Financial Modelling in Energy

Applied Operations Research and Financial Modelling in Energy
Author: André B. Dorsman
Publisher: Springer Nature
Total Pages: 283
Release: 2021-10-12
Genre: Business & Economics
ISBN: 3030849813

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This book on Applied Operations Research and Financial Modelling in Energy (AORFME) presents several applications of operations research (OR) and financial modelling. The contributions by a group of OR and Finance researchers focus on a variety of energy decisions, presenting a quantitative perspective, and providing policy implications of the proposed or applied methodologies. The content is divided into three main parts: Applied OR I: Optimization Approaches, Applied OR II: Forecasting Approaches and Financial Modelling: Impacts of Energy Policies and Developments in Energy Markets. The book appeals to scholars in economics, finance and operations research, and to practitioners working in the energy sector. This is the eighth volume in a series of books on energy organized by the Centre for Energy and Value Issues (CEVI). For this volume, CEVI collaborated with Hacettepe University’s Energy Markets Research and Application Center. The previous volumes in the series are: Financial Aspects in Energy (2011), Energy Economics and Financial Markets (2012), Perspectives on Energy Risk (2014), Energy Technology and Valuation Issues (2015), Energy and Finance (2016), Energy Economy, Finance and Geostrategy (2018), and Financial Implications of Regulations in the Energy Industry (2020).


Artificial Intelligence Enabled Computational Methods for Smart Grid Forecast and Dispatch

Artificial Intelligence Enabled Computational Methods for Smart Grid Forecast and Dispatch
Author: Yuanzheng Li
Publisher: Springer Nature
Total Pages: 271
Release: 2023-05-05
Genre: Technology & Engineering
ISBN: 9819907993

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With the increasing penetration of renewable energy and distributed energy resources, smart grid is facing great challenges, which could be divided into two categories. On the one hand, the endogenous uncertainties of renewable energy and electricity load lead to great difficulties in smart grid forecast. On the other hand, massive electric devices as well as their complex constraint relationships bring about significant difficulties in smart grid dispatch. Owe to the rapid development of artificial intelligence in recent years, several artificial intelligence enabled computational methods have been successfully applied in the smart grid and achieved good performances. Therefore, this book is concerned with the research on the key issues of artificial intelligence enabled computational methods for smart grid forecast and dispatch, which consist of three main parts. (1) Introduction for smart grid forecast and dispatch, in inclusion of reviewing previous contribution of various research methods as well as their drawbacks to analyze characteristics of smart grid forecast and dispatch. (2) Artificial intelligence enabled computational methods for smart grid forecast problems, which are devoted to present the recent approaches of deep learning and machine learning as well as their successful applications in smart grid forecast. (3) Artificial intelligence enabled computational methods for smart grid dispatch problems, consisting of edge-cutting intelligent decision-making approaches, which help determine the optimal solution of smart grid dispatch. The book is useful for university researchers, engineers, and graduate students in electrical engineering and computer science who wish to learn the core principles, methods, algorithms, and applications of artificial intelligence enabled computational methods.