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| energy trading data analytics: Big Data and Analytics Dr. Jugnesh Kumar, Dr. Anubhav Kumar, Dr. Rinku Kumar, 2024-03-05 Unveiling insights, unleashing potential: Navigating the depths of big data and analytics for a data-driven tomorrow KEY FEATURES ● Learn about big data and how it helps businesses innovate, grow, and make decisions efficiently. ● Learn about data collection, storage, processing, and analysis, along with tools and methods. ● Discover real-life examples of big data applications across industries, addressing challenges like privacy and security. DESCRIPTION Big data and analytics is an indispensable guide that navigates the complex data management and analysis. This comprehensive book covers the core principles, processes, and tools, ensuring readers grasp the essentials and progress to advanced applications. It will help you understand the different analysis types like descriptive, predictive, and prescriptive. Learn about NoSQL databases and their benefits over SQL. The book centers on Hadoop, explaining its features, versions, and main components like HDFS (storage) and MapReduce (processing). Explore MapReduce and YARN for efficient data processing. Gain insights into MongoDB and Hive, popular tools in the big data landscape. WHAT YOU WILL LEARN ● Grasp big data fundamentals and applications. ● Master descriptive, predictive, and prescriptive analytics. ● Understand HDFS, MapReduce, YARN, and their functionalities. ● Explore data storage, retrieval, and manipulation in a NoSQL database. ● Gain practical insights and apply them to real-world scenarios. WHO THIS BOOK IS FOR This book caters to a diverse audience, including data professionals, analysts, IT managers, and business intelligence practitioners. TABLE OF CONTENTS 1. Introduction to Big Data 2. Big Data Analytics 3. Introduction of NoSQL 4. Introduction to Hadoop 5. Map Reduce 6. Introduction to MongoDB |
| energy trading data analytics: Machine Learning and Data Science in the Power Generation Industry Patrick Bangert, 2021-01-14 Machine Learning and Data Science in the Power Generation Industry explores current best practices and quantifies the value-add in developing data-oriented computational programs in the power industry, with a particular focus on thoughtfully chosen real-world case studies. It provides a set of realistic pathways for organizations seeking to develop machine learning methods, with a discussion on data selection and curation as well as organizational implementation in terms of staffing and continuing operationalization. It articulates a body of case study–driven best practices, including renewable energy sources, the smart grid, and the finances around spot markets, and forecasting. - Provides best practices on how to design and set up ML projects in power systems, including all nontechnological aspects necessary to be successful - Explores implementation pathways, explaining key ML algorithms and approaches as well as the choices that must be made, how to make them, what outcomes may be expected, and how the data must be prepared for them - Determines the specific data needs for the collection, processing, and operationalization of data within machine learning algorithms for power systems - Accompanied by numerous supporting real-world case studies, providing practical evidence of both best practices and potential pitfalls |
| energy trading data analytics: The Intersection of Blockchain and Energy Trading Sidique Gawusu, Abubakari Ahmed, Seidu Abdulai Jamatutu, 2024-11-15 The Intersection of Blockchain and Energy Trading: Exploring Decentralized Solutions for Next-Generation Energy Markets equips readers with a practical understanding of the opportunities and challenges of this cutting-edge technology for the renewable energy markets of the future. Its multidisciplinary team of authors and editors provide a holistic guide to blockchain in energy markets, beginning with the fundamentals of energy trading and foundational principles of blockchain technology. Subsequent chapters demonstrate the applied opportunities for a variety of energy outcomes including renewable energy, decentralized energy, and electric vehicles. Essential use-cases such as demand response and ancillary services are covered, and the final chapters offer guidance on the impact of the technology for energy poverty and sustainability. Packed with models, case studies, and tools for implementation and practice, this book is an essential guide for researchers and professionals at the forefront of energy market innovation. - Introduces readers to the fundamentals of this innovative technique and its benefits for the energy trading sector - Provides clear and practical tools for the implementation of the technologies, from a multidisciplinary perspective - Demonstrates the challenges and opportunities of blockchain in enabling renewable and sustainable energy |
| energy trading data analytics: Demand-Side Peer-to-Peer Energy Trading Vahid Vahidinasab, Behnam Mohammadi-Ivatloo, 2023-08-01 Demand-Side Peer-to-Peer Energy Trading provides a comprehensive study of the latest developments in technology, protocols, implementation, and application of peer-to-peer and transactive energy concepts in energy systems and their role in worldwide energy evolution and decarbonization efforts. It presents practical aspects and approaches with evidence from applications to real-world energy systems through in-depth technical discussions, use cases, and examples. This multidisciplinary reference is suitable for researchers and industry stakeholders who focus on the field of energy systems and energy economics, as well as researchers and developers from different branches of engineering, energy, computer sciences, data, economic, and operation research fields. |
| energy trading data analytics: IoT and Analytics in Renewable Energy Systems (Volume 1) O.V. Gnana Swathika, K. Karthikeyan, Sanjeevikumar Padmanaban, 2023-08-11 Smart grid technologies include sensing and measurement technologies, advanced components aided with communications and control methods along with improved interfaces and decision support systems. Smart grid techniques support the extensive inclusion of clean renewable generation in power systems. Smart grid use also promotes energy saving in power systems. Cyber security objectives for the smart grid are availability, integrity and confidentiality. Five salient features of this book are as follows: AI and IoT in improving resilience of smart energy infrastructure IoT, smart grids and renewable energy: an economic approach AI and ML towards sustainable solar energy Electrical vehicles and smart grid Intelligent condition monitoring for solar and wind energy systems |
| energy trading data analytics: Artificial Intelligence-Empowered Modern Electric Vehicles in Smart Grid Systems Aparna Kumari, Sudeep Tanwar, 2024-05-23 Artificial Intelligence-Empowered Modern Electric Vehicles in Smart Grid Systems: Fundamentals, Technologies, and Solutions is an essential reference for energy researchers, graduate students and engineers who aim to understand the opportunities offered by artificial intelligence for the integration of electric vehicles into smart grids. This book begins by building foundational knowledge for the reader, covering the essentials of artificial intelligence and its applications for electric vehicles in a clear and holistic manner. Next, it breaks down two essential areas of application in more detail: energy management (from to energy harvesting to demand response and complex forecasting), and market strategies (including peer-to-peer, vehicle-to-vehicle, and vehicle-to-everything trading, plus the cyber-security implications). A final part provides detailed case studies and close consideration of challenges, including code and data sets for replication of techniques. Providing a clear pathway from fundamentals to practical implementation, Artificial Intelligence-Empowered Modern Electric Vehicles in Smart Grid Systems will provide multidisciplinary guidance for implementing this cutting-edge technology in the energy systems of the future. - Supports fundamental understanding of artificial intelligence and its opportunities for energy system specialists - Collects the real-world experiences of global experts - Enables practical implementation of artificial intelligence strategies that support renewable energy integration across energy systems, markets, and grids |
| energy trading data analytics: Smart Energy Grid Engineering Hossam Gabbar, 2016-10-12 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 |
| energy trading data analytics: Artificial Intelligence-based Smart Power Systems Sanjeevikumar Padmanaban, Sivaraman Palanisamy, Sharmeela Chenniappan, Jens Bo Holm-Nielsen, 2022-12-20 Authoritative resource describing the artificial intelligence and advanced technologies in smart power systems with simulation examples and case studies Artificial Intelligence-based Smart Power Systems presents advanced technologies used in various aspects of smart power systems, especially grid-connected and industrial evolution, covering many new topics such as distribution Phasor management, blockchain technologies for smart power systems, the application of deep learning and reinforced learning, and artificial intelligence techniques. The text also explores the potential consequences of artificial intelligence and advanced technologies in smart power systems in the forthcoming years. To enhance and reinforce learning, the highly qualified editors include many learning resources throughout the text, including MATLAB and HIL codes, end-of-chapter problems, end-of-book solutions, practical examples, and case studies. Artificial Intelligence-based Smart Power Systems includes specific information on topics such as: Modeling and analysis of smart power systems, covering steady state analysis, dynamic analysis, voltage stability, and more Recent advancement in power electronics for smart power systems, covering power electronic converters for renewable energy sources, electric vehicles, and HDVC/FACTs Distribution Phasor Measurement Units (PMU) in smart power systems, covering the need for PMU in distribution and automation of system reconfigurations Power and energy management systems for microgrids Engineering colleges and universities, along with industry research centers, can use the in-depth subject coverage and the extensive supplementary learning resources found in Artificial Intelligence-based Smart Power Systems to gain a holistic understanding of the subject and be able to harness that knowledge within a myriad of practical applications. |
| energy trading data analytics: Trading in Local Energy Markets and Energy Communities Miadreza Shafie-khah, Amin Shokri Gazafroudi, 2023-02-13 This book presents trading in local energy markets and communities. It covers electrical, business, economics, telecommunication, information technology (IT), environment, building, industrial, and computer science and examines the intersections of these areas with these markets and communities. Additionally, it delivers an vision for local trading and communities in smart cities. Since it also lays out concepts, structures, and technologies in a variety of applications intertwined with future smart cities, readers running businesses of all types will find material of use in the book. Manufacturing firms, electric generation, transmission and distribution utilities, hardware and software computer companies, automation and control manufacturing firms, and other industries will be able to use this book to enhance their energy operations, improve their comfort and privacy, as well as to increase the benefit from the energy system. This book is also used as a textbook for graduate level courses. |
| energy trading data analytics: The Handbook for ETRM Mittal Shah, 2022-12-05 This is probably the first book written in simple language to understand Energy Trading and Risk Management. The book is an asset, and a must-read for students, product owners, IT consultants and energy trading evangelists. The book begins with an Introduction to Energy Trading and progresses to discuss Energy Trading Markets and products in detail. The energy and commodities trading lifecycle is different from capital markets as this involves the physical movement of the underlying. The crude oil trade life cycle is elaborately explained, including the end-of-day process. The reader gets a detailed understanding of Risk and Risk Management which is vital to energy trading. Electricity, Coal and Gas trading is increasing, and this book will give you a high-level description of all three different forms of energy. Technology is at the centre of everything, including energy trading. The book list Block Chain, Robotics Process Automation, Data, Analytics and Insights, Machine Learning and Artificial Intelligence use cases and concepts. Basic concepts like INCO Terms, and Letters of Credit, among others, will be refreshed for the reader. History is full of exciting stories, and some related to energy trading make for an interesting read. The book ends with some key definitions involved in Energy Trading. |
| energy trading data analytics: Energy Markets Tom James, 2012-11-27 Price Risk Management and Trading. Energy risk management expert, Tom James, does it again. His latest book is a timely addition to the rapidly developing energy trading markets. This book should be on every energy trader, risk manager and corporate planer's desk. it is an easy read as Tom goes into great detail to explain the intricacies of this market and its various unique elements. - Peter C. Fusaro, Chairman, Global Change Associates Inc., Best-selling Author and Energy Expert This sensible and practical guide is essential for those seeking an understanding of commerce in energy derivatives. beyond merely informative, this hand book for the practitioner details the finer points of the use of derivatives as tools for price-risk management. No energy trading desk should be without it. - Ethan L. Cohen, Senior Director, Utility and Energy Technology, UtiliPoint International Inc. Energy markets are much more volatile than other commodity markets, so risk mitigation is more of a concern. Energy prices, for example, can be affected by weather, geopo9litical turmoil, changes in tax and legal systems, OPEC decisions, analysis' reports, transportation issues, and supply and demand - to name just a few factors. Tom James's book is a practical guide to assessing and managing these risks. It is a must-read for senior management as well as risk and financial professionals.- Don Stowers, Editor, Oil & Gas Financial Journal This book is the most comprehensive on price risk management-centric efforts. It provides the reader with a tangible experience of derivatives in today's capital and energy markets. The breadth and scope of the passages are immense, in that both developed and developing countries' energy markets are considered and examples applied. Terrific read! - Rashpal Bhatti, Marketing Manager, Energy Trading Asia, Enron/BHP Billiton Tom James has simplified the intricacies of a very complex market. In this new market of hot commodities, he has been able to give a fresh course to those who are new to the energy markets and a solid review for those that are well seasoned. he covers everything within the oil market from A to Z in this book and does it well. Coming from a financial background myself, it's good to finally find a book that can bring a better understanding to the field of energy commodities. - Carl Larry, Vice President Citi Energy Global Commodities |
| energy trading data analytics: Computational Intelligence and Blockchain in Complex Systems Fadi Al-Turjman, 2024-03-26 Computational Intelligence and Blockchain in Complex Systems provides readers with a guide to understanding the dynamics of AI, Machine Learning, and Computational Intelligence in Blockchain, and how these rapidly developing technologies are revolutionizing a variety of interdisciplinary research fields and applications. The book examines the role of Computational Intelligence and Machine Learning in the development of algorithms to deploy Blockchain technology across a number of applications, including healthcare, insurance, smart grid, smart contracts, digital currency, precision agriculture, and supply chain. The authors cover the unique and developing intersection between cyber security and Blockchain in modern networks, as well as in-depth studies on cyber security challenges and multidisciplinary methods in modern Blockchain networks. Readers will find mathematical equations throughout the book as part of the underlying concepts and foundational methods, especially the complex algorithms involved in Blockchain security aspects for hashing, coding, and decoding. Computational Intelligence and Blockchain in Complex Systems provides readers with the most in-depth technical guide to the intersection of Computational Intelligence and Blockchain, two of the most important technologies for the development of next generation complex systems. - Covers the research issues and concepts of machine learning technology in blockchain - Provides in-depth information about handling and managing personal data by machine learning methods in blockchain - Helps readers understand the links between computational intelligence, blockchain, complex systems, and developing secure applications in multidisciplinary sectors |
| energy trading data analytics: Big Data Analytics Strategies for the Smart Grid Carol L. Stimmel, 2014-07-25 By implementing a comprehensive data analytics program, utility companies can meet the continually evolving challenges of modern grids that are operationally efficient, while reconciling the demands of greenhouse gas legislation and establishing a meaningful return on investment from smart grid deployments. Readable and accessible, Big Data Analytics Strategies for the Smart Grid addresses the needs of applying big data technologies and approaches, including Big Data cybersecurity, to the critical infrastructure that makes up the electrical utility grid. It supplies industry stakeholders with an in-depth understanding of the engineering, business, and customer domains within the power delivery market. The book explores the unique needs of electrical utility grids, including operational technology, IT, storage, processing, and how to transform grid assets for the benefit of both the utility business and energy consumers. It not only provides specific examples that illustrate how analytics work and how they are best applied, but also describes how to avoid potential problems and pitfalls. Discussing security and data privacy, it explores the role of the utility in protecting their customers’ right to privacy while still engaging in forward-looking business practices. The book includes discussions of: SAS for asset management tools The AutoGrid approach to commercial analytics Space-Time Insight’s work at the California ISO (CAISO) This book is an ideal resource for mid- to upper-level utility executives who need to understand the business value of smart grid data analytics. It explains critical concepts in a manner that will better position executives to make the right decisions about building their analytics programs. At the same time, the book provides sufficient technical depth that it is useful for data analytics professionals who need to better understand the nuances of the engineering and business challenges unique to the utilities industry. |
| energy trading data analytics: Energy Trading and Risk Management Tadahiro Nakajima, Shigeyuki Hamori, 2022-11-03 This book introduces empirical methods for analyzing energy markets. Even beginners in econometrics and mathematical finance must be able to learn how to utilize these methodologies and how to interpret the analysis results. This book provides some example analyses of the North American, European, and Asian energy markets. The reader will experience some theories and practices of energy trading and risk management. This book reveals the characteristics of energy markets using quantitative analyses. Examples include unit root, cointegration, long-term equilibrium, stochastic arbitrage simulation, multivariate generalized autoregressive conditional heteroscedasticity (GARCH) models, exponential GARCH (EGARCH) models, optimal hedge ratio, copula, value-at-risk (VaR), expected shortfall, vector autoregressive (VAR) models, vector moving average (VMA) models, connectedness, and frequency decomposition. This book is suitable for people interested in the empirical study of energy markets and energy trade. |
| energy trading data analytics: Energy Trading and Risk Management Felix Müsgens, |
| energy trading data analytics: Navigating the Circular Age of a Sustainable Digital Revolution Tanveer, Umair, Ishaq, Shamaila, Huy, Truong Quang, Hoang, Thinh Gia, 2024-08-26 In the face of rapid digitalization and environmental challenges, the world stands at a critical juncture. The relentless pace of technological advancement has brought unparalleled convenience and efficiency but has also contributed to unsustainable consumption patterns, resource depletion, and environmental degradation. Despite growing awareness, many industries need help integrating sustainable practices into their operations, hindered by a lack of understanding, resources, and clear guidelines. Moreover, the complexity of the circular economy and the ethical dimensions of digitalization pose significant challenges, requiring innovative solutions and comprehensive guidance. Navigating the Circular Age of a Sustainable Digital Revolution offers a timely and comprehensive solution to these pressing challenges. By exploring the intricate relationship between technology and sustainability, this book provides a roadmap for businesses, policymakers, and individuals to embrace sustainable practices in the digital era. Researchers and scholars gain profound insights from this book into the dynamics between digitalization and sustainable practices while policymakers find nuanced analyses to shape regulatory frameworks. Business leaders and professionals discover practical guidance for sustainable business models and digital transformation, and technology practitioners align their fields with sustainable advancements. Ultimately, the book empowers individuals and organizations to shape a future where technology and sustainability coexist, fostering a more sustainable and prosperous world. |
| energy trading data analytics: Artificial Intelligence in the Operation and Control of Digitalized Power Systems Sasan Azad, |
| energy trading data analytics: Accounting Paul D. Kimmel, Jerry J. Weygandt, Jill E. Mitchell, 2021-12-02 Accounting: Tools for Business Decision Making by Paul Kimmel, Jerry Weygandt, and Jill Mitchell provides a practical introduction to financial and managerial accounting with a focus on how to use accounting information to make business decisions. Through significant course updates, the 8th Edition presents an active, hands-on approach to spark efficient and effective learning and develops the necessary skills to inspire and prepare students to be the accounting and business professionals of tomorrow. To ensure maximum understanding, students work through integrated assessment at different levels of difficulty right at the point of learning. The course's varied assessment also presents homework and assessment within real-world contexts to help students understand the why and the how of accounting information and business application. Throughout the course, students also work through various hands-on activities including Cookie Creations Cases, Expand Your Critical Thinking Questions, Excel Templates, and Analytics in Action problems, all within the accounting context. These applications all map to chapter material, making it easier for instructors to determine where and how to incorporate key skill development in their syllabus. With Kimmel Accounting, students will understand the foundations of introductory accounting and develop the necessary tools for business decision-making, no matter what path they take. |
| energy trading data analytics: Intelligent Data Mining and Analysis in Power and Energy Systems Zita A. Vale, Tiago Pinto, Michael Negnevitsky, Ganesh Kumar Venayagamoorthy, 2022-12-02 Intelligent Data Mining and Analysis in Power and Energy Systems A hands-on and current review of data mining and analysis and their applications to power and energy systems In Intelligent Data Mining and Analysis in Power and Energy Systems: Models and Applications for Smarter Efficient Power Systems, the editors assemble a team of distinguished engineers to deliver a practical and incisive review of cutting-edge information on data mining and intelligent data analysis models as they relate to power and energy systems. You’ll find accessible descriptions of state-of-the-art advances in intelligent data mining and analysis and see how they drive innovation and evolution in the development of new technologies. The book combines perspectives from authors distributed around the world with expertise gained in academia and industry. It facilitates review work and identification of critical points in the research and offers insightful commentary on likely future developments in the field. It also provides: A thorough introduction to data mining and analysis, including the foundations of data preparation and a review of various analysis models and methods In-depth explorations of clustering, classification, and forecasting Intensive discussions of machine learning applications in power and energy systems Perfect for power and energy systems designers, planners, operators, and consultants, Intelligent Data Mining and Analysis in Power and Energy Systems will also earn a place in the libraries of software developers, researchers, and students with an interest in data mining and analysis problems. |
| energy trading data analytics: Computer Vision and Machine Intelligence for Renewable Energy Systems Ashutosh Kumar Dubey, Abhishek Kumar, Umesh Chandra Pati, Fausto Pedro Garcia Marquez, Vicente García-Díaz, Arun Lal Srivastav, 2024-09-20 Computer Vision and Machine Intelligence for Renewable Energy Systems offers a practical, systemic guide to the use of computer vision as an innovative tool to support renewable energy integration.This book equips readers with a variety of essential tools and applications: Part I outlines the fundamentals of computer vision and its unique benefits in renewable energy system models compared to traditional machine intelligence: minimal computing power needs, speed, and accuracy even with partial data. Part II breaks down specific techniques, including those for predictive modeling, performance prediction, market models, and mitigation measures. Part III offers case studies and applications to a wide range of renewable energy sources, and finally the future possibilities of the technology are considered. The very first book in Elsevier's cutting-edge new series Advances in Intelligent Energy Systems, Computer Vision and Machine Intelligence for Renewable Energy Systems provides engineers and renewable energy researchers with a holistic, clear introduction to this promising strategy for control and reliability in renewable energy grids. - Provides a sorely needed primer on the opportunities of computer vision techniques for renewable energy systems - Builds knowledge and tools in a systematic manner, from fundamentals to advanced applications - Includes dedicated chapters with case studies and applications for each sustainable energy source |
| energy trading data analytics: Internet of Energy for Smart Cities Anish Jindal, Neeraj Kumar, Gagangeet Singh Aujla, 2021-07-19 Machine learning approaches has the capability to learn and adapt to the constantly evolving demands of large Internet-of-energy (IoE) network. The focus of this book is on using the machine learning approaches to present various solutions for IoE network in smart cities to solve various research gaps such as demand response management, resource management and effective utilization of the underlying ICT network. It provides in-depth knowledge to build the technical understanding for the reader to pursue various research problems in this field. Moreover, the example problems in smart cities and their solutions using machine learning are provided as relatable to the real-life scenarios. Aimed at Graduate Students, Researchers in Computer Science, Electrical Engineering, Telecommunication Engineering, Internet of Things, Machine Learning, Green computing, Smart Grid, this book: Covers all aspects of Internet of Energy (IoE) and smart cities including research problems and solutions. Points to the solutions provided by machine learning to optimize the grids within a smart city set-up. Discusses relevant IoE design principles and architecture. Helps to automate various services in smart cities for energy management. Includes case studies to show the effectiveness of the discussed schemes. |
| energy trading data analytics: Web 3.0 Prabhat Kumar Srivastav, Prateek Singhal, Basudeo Singh Roohani, Nitin Sharma, 2024-08-01 The book underscores AI's transformative impact on reshaping physical, digital, and biological boundaries, converging with technologies like robotics, IoT, 3D printing, genetic engineering, and quantum computing—termed Web 3.0 Industrial Revolution. This global revolution integrates advanced production techniques beyond connected machines, extending into gene sequencing, nanotechnology, renewable energies, and quantum computing. The book's main goals include providing a collaborative platform for academia and industry researchers to share contributions and shape the future through knowledge exchange. Recognizing recent progress driven by increased computing power, it highlights the positive impact of digital technology—AI, IoT, AR/VR, Additive Manufacturing, CPS, cloud computing, and robotics—on industrial efficiency and quality. Revolutionary AI Fusion: AI revolutionizes by blending physical, digital, and biological boundaries through cutting-edge technologies like robotics, IoT, 3D printing, genetic engineering, and quantum computing. Global Manufacturing Cooperation: AI creates a collaborative landscape where virtual and physical systems flexibly cooperate on a global scale. AI's Diverse Impact: Beyond smart machines, AI drives breakthroughs in gene sequencing, nanotechnology, renewable energies, and quantum computing, distinguishing it from prior industrial revolutions. Progress and Digital Interface: Recent progress, powered by computing advancements, boosts industrial efficiency. The digital technology interface (AI, IoT, AR/VR, 3D Printing, CPS, CC, Robotics) significantly impacts industrial performance. In conclusion, AI spearheads a transformative revolution, redefining the boundaries of the physical, digital, and biological realms. The fusion of AI with Web 3.0 Industrial Revolution, integrating advanced production techniques and global manufacturing cooperation, surpassing past industrial shifts. The book aims to be a collaborative platform for academia and industry researchers, fostering knowledge exchange to shape the future. In AI-driven manufacturing within Web 3.0, a paradigm shift envisions maximum output with minimal resource use. Coupled with 'Digital Reality,' it transforms business practices, consumer behaviour, and employment dynamics, redistributing wealth toward innovation and technology. |
| energy trading data analytics: Generative AI and Multifactor Productivity in Business Adedoyin, Festus Fatai, Christiansen, Bryan, 2024-04-26 As organizations grapple with the challenges of a dynamic market, the integration of Artificial Intelligence (AI) emerges not only as a technological progression but a strategic necessity. The transformative potential of AI, particularly through OpenAI, holds the promise of redefining operational paradigms, accelerating innovation, and unlocking unprecedented growth opportunities. However, lurking beneath this promise are challenges that demand urgent attention – from tailoring relevance for specific business units to ethical and safe integration practices. The specifics of how OpenAI can amplify labor productivity and enhance decision-making processes remain elusive. Generative AI and Multifactor Productivity in Business offers a guide surrounding the complexities of OpenAI's role in business operations. It contends that understanding OpenAI is not just beneficial; it is essential for organizations seeking to navigate economic uncertainties and unlock high levels of efficiency and growth. The book delves into the effects of OpenAI on business, with a primary objective of illuminating the scholarly and practitioner-based contributions that push the boundaries of OpenAI in business research. This exploration encompasses applications of advanced generative AI tools, language models, and innovative technologies specific to diverse businesses across sectors, scales, and regions. It emphasizes that as AI becomes more seamlessly integrated into business processes, the potential for multifactor productivity to fuel economic growth, new industries, and job opportunities is unparalleled. |
| energy trading data analytics: Big Data Analytics Framework for Smart Grids Rajkumar Viral, Divya Asija, Surender Salkuti, 2023-12-22 The text comprehensively discusses smart grid operations and the use of big data analytics in overcoming the existing challenges. It covers smart power generation, transmission, and distribution, explains energy management systems, artificial intelligence, and machine learning–based computing. Presents a detailed state-of-the-art analysis of big data analytics and its uses in power grids Describes how the big data analytics framework has been used to display energy in two scenarios including a single house and a smart grid with thousands of smart meters Explores the role of the internet of things, artificial intelligence, and machine learning in smart grids Discusses edge analytics for integration of generation technologies, and decision-making approaches in detail Examines research limitations and presents recommendations for further research to incorporate big data analytics into power system design and operational frameworks The text presents a comprehensive study and assessment of the state-of-the-art research and development related to the unique needs of electrical utility grids, including operational technology, storage, processing, and communication systems. It further discusses important topics such as complex adaptive power system, self-healing power system, smart transmission, and distribution networks, and smart metering infrastructure. It will serve as an ideal reference text for senior undergraduate, graduate students, and academic researchers in the areas such as electrical engineering, electronics and communications engineering, computer engineering, and information technology. |
| energy trading data analytics: Emerging Technologies for Sustainable and Smart Energy Anirbid Sircar, Gautami Tripathi, Namrata Bist, Kashish Ara Shakil, Mithileysh Sathiyanarayanan, 2022-08-03 Considering the alarming issue of global climate change and its drastic consequences, there is an urgent need to further develop smart and innovative solutions for the energy sector. The goal of sustainable and smart energy for present and future generations can be achieved by integrating emerging technologies into the existing energy infrastructure. This book focuses on the role and significance of emerging technologies in the energy sector and covers the various technological interventions for both conventional and unconventional energy resources and provides meaningful insights into smart and sustainable energy solutions. The book also discusses future directions for smart and sustainable developments in the energy sector. |
| energy trading data analytics: Smart Metering Applications Nikolaos Efkarpidis, Martin Geidl, Holger Wache, Marco Peter, Marc Adam, 2022-10-03 This book presents a large number of smart metering applications from the points of view of different stakeholders. The applications are clustered with respect to three types of stakeholders: (a) end-customers, (b) energy service providers, and (c) authorities/research institutions or other organizations. The goal of the book is to examine the implementation potential for each application, considering the interests and benefits for the key stakeholders, main technical and regulatory requirements, as well as limitations and barriers. A business case for each application is created that can provide guidelines to the stakeholders involved in its realization. The book additionally investigates current business models for smart metering applications. A survey on the current techno-economic potential of such applications is conducted based on a questionnaire filled by various stakeholders. The book will be of interest to academic/research institutions, but also engineers in industry, authorities or other organizations. |
| energy trading data analytics: Green Hydrogen in Power Systems Vahid Vahidinasab, |
| energy trading data analytics: Topics in Artificial Intelligence Applied to Industry 4.0 Mahmoud Ragab AL-Refaey, Amit Kumar Tyagi, Abdullah Saad AL-Malaise AL-Ghamdi, Swetta Kukreja, 2024-03-28 Topics in Artificial Intelligence Applied to Industry 4.0 Forward thinking resource discussing emerging AI and IoT technologies and how they are applied to Industry 4.0 Topics in Artificial Intelligence Applied to Industry 4.0 discusses the design principles, technologies, and applications of emerging AI and IoT solutions on Industry 4.0, explaining how to make improvements in infrastructure through emerging technologies. Providing a clear connection with different technologies such as IoT, Big Data, AR and VR, and Blockchain, this book presents security, privacy, trust, and other issues whilst delving into real-world problems and case studies. The text takes a highly practical approach, with a clear insight on how readers can increase productivity by drastically shortening the time period between the development of a new product and its delivery to customers in the market by 50%. This book also discusses how to save energy across systems to ensure competitiveness in a global market, and become more responsive in how they produce products and services for their consumers, such as by investing in flexible production lines. Written by highly qualified authors, Topics in Artificial Intelligence Applied to Industry 4.0 explores sample topics such as: Quantum machine learning, neural network implementation, and cloud and data analytics for effective analysis of industrial data Computer vision, emerging networking technologies, industrial data spaces, and an industry vision for 2030 in both developing and developed nations Novel or improved nature-inspired optimization algorithms in enhancing Industry 5.0 and the connectivity of any components for smart environment Future professions in agriculture, medicine, education, fitness, R&D, and transport and communication as a result of new technologies Aimed at researchers and students in the interdisciplinary fields of Smart Manufacturing and Smart Applications, Topics in Artificial Intelligence Applied to Industry 4.0 provides the perfect overview of technology from the perspective of modern society and operational environment. |
| energy trading data analytics: AI Applications for Clean Energy and Sustainability Riswandi, Budi Agus, Singh, Bhupinder, Kaunert, Christian, Vig, Komal, 2024-08-16 The global demand for clean energy solutions the urgency of addressing climate change continue to intensify, and as such, the need for innovative approaches becomes increasingly paramount. However, navigating the complex landscape of clean energy production and sustainability presents significant challenges. Traditional methods often fall short in efficiently optimizing renewable energy systems and mitigating environmental impacts. Moreover, the integration of artificial intelligence (AI) into the energy sector remains underexplored, despite its potential to revolutionize operations and drive sustainable development. AI Applications for Clean Energy and Sustainability emerges, working to tackle these pressing issues. This comprehensive volume delves into the transformative power of AI in revolutionizing clean energy production, distribution, and management. By harnessing machine learning algorithms, data analytics, and optimization techniques, the book offers innovative solutions to enhance the efficiency, reliability, and scalability of renewable energy systems. Through real-world case studies and practical examples, it illustrates AI's potential to optimize energy infrastructure, monitor marine ecosystems, and predict climate change impacts, thereby paving the way for a more sustainable future. |
| energy trading data analytics: Intelligent Systems and Applications Kohei Arai, |
| energy trading data analytics: Internet of Things Brojo Kishore Mishra, Amit Vishwasrao Salunkhe, 2023-10-13 The Internet of Things has revolutionized many industries and sectors by connecting devices to the Internet with the use of smart sensors and actuators, resulting in many advantages to businesses and organizations, such as better information and resource sharing, better supply chain efficiency, resulting in better overall efficiency and cost savings. This new book investigates the potential for initiating data-enabled and IoT-intensive applications to provide control and optimization of industrial operations and services. It presents an informative selection of quantitative research, case studies, conceptual chapters, model articles and theoretical papers on many important technological advances, applications, and challenges in the current status of IoT. The book features examples of IoT applications in such areas as food processing, automotive engineering, mental health, health tracking, security, and more. It discusses applying IoT in reverse logistics processes, developments in the Internet of Vehicles, the use of smart antennas, and machine learning in IoT. One chapter discusses a ground-breaking new device that uses IoT to convert audio recordings to Braille. Also discussed is the growing use of IoT in biometric technology (the use of technology to identify a person based on some aspect of their biology, such as fingerprint and eye unique pattern recognition). The enlightening information shared here offers state-of-the-art IoT solutions to many of today’s challenges of improving efficiency and bringing important information to the surface more quickly than systems depending on human intervention. The volume will be of value for computer science engineers and researchers, instructors and students in the field, and professionals that are interested in exploring the areas of next-generations IoT. |
| energy trading data analytics: Cases on Green Energy and Sustainable Development Yang, Peter, 2019-07-26 Despite the urgent need for action, there is a widespread lack of understanding of the benefits of using green energy sources for not only reducing carbon emissions and climate change, but also for growing a sustainable economy and society. Future citizens of the world face increasing sustainability issues and need to be better prepared for energy transformation and sustainable future economic development. Cases on Green Energy and Sustainable Development is a critical research book that focuses on the important role renewable energy and energy efficiency play in energy transition and sustainable development and covers economic and promotion policies of major renewable energy and energy-efficiency technologies. Highlighting a wide range of topics such as economics, energy storage, and transportation technologies, this book is ideal for environmentalists, academicians, researchers, engineers, policymakers, and students. |
| energy trading data analytics: Crafting a Sustainable Future Through Education and Sustainable Development Martínez-Falcó, Javier, Marco-Lajara, Bartolomé, Sánchez-García, Eduardo, Millan-Tudela, Luis A., 2023-09-25 In an era where the planet faces unprecedented environmental challenges, such as climate change, loss of biodiversity, and water scarcity, sustainable development has become paramount. Crafting a Sustainable Future Through Education and Sustainable Development delves into the crucial role of educational institutions in shaping a sustainable future from economic, social, and environmental perspectives. By examining new currents and challenges within this discipline, this book provides a valuable study resource that sheds light on the intricate relationship between education and achieving sustainability goals. The book emphasizes the vital role of educational institutions as spaces for fostering new paradigms of human behavior towards the environment. Crafting a Sustainable Future Through Education and Sustainable Development serves as a comprehensive study guide, offering critical reflections and constructive critiques. It covers an array of relevant topics, ranging from artificial intelligence and big data to gender equality, game-based learning, and socio-technological innovation. It is ideal for academics, academic students, and policymakers, this book provides invaluable support for undergraduate and master’s students in business, as well as professionals seeking to deepen their knowledge of the role of education in achieving sustainable development. |
| energy trading data analytics: Data Science and Applications for Modern Power Systems Le Xie, Yang Weng, Ram Rajagopal, 2023-06-20 This book offers a comprehensive collection of research articles that utilize data—in particular large data sets—in modern power systems operation and planning. As the power industry moves towards actively utilizing distributed resources with advanced technologies and incentives, it is becoming increasingly important to benefit from the available heterogeneous data sets for improved decision-making. The authors present a first-of-its-kind comprehensive review of big data opportunities and challenges in the smart grid industry. This book provides succinct and useful theory, practical algorithms, and case studies to improve power grid operations and planning utilizing big data, making it a useful graduate-level reference for students, faculty, and practitioners on the future grid. |
| energy trading data analytics: Smart Energy and Electric Power Systems Sanjeevikumar Padmanaban, Jens Bo Holm-Nielsen, Kayal Padmanandam, Rajesh Kumar Dhanaraj, Balamurugan Balusamy, 2022-09-17 Smart Energy and Electric Power Systems: Current Trends and New Intelligent Perspectives reviews key applications of intelligent algorithms and machine learning techniques to increasingly complex and data-driven power systems with distributed energy resources to enable evidence-driven decision-making and mitigate catastrophic power shortages. The book reviews foundations towards the integration of machine learning and smart power systems before addressing key challenges and issues. The work then explores AI- and ML-informed techniques to rebalancing of supply and demand. Methods discussed include distributed energy resources and prosumer markets, electricity demand prediction, component fault detection, and load balancing. Security solutions are introduced, along with potential solutions to cyberattacks, security data detection and critical loads in power systems. The work closes with a lengthy discussion, informed by case studies, on integrating AI and ML into the modern energy sector. - Helps improve the prediction capability of AI algorithms to make evidence-based decisions in the smart supply of electricity, including load shedding - Focuses on how to integrate AI and ML into the energy sector in the real-world, with many chapters accompanied by case studies - Addresses a number of proven AI and ML- informed techniques in rebalancing supply and demand |
| energy trading data analytics: Energy Efficiency Analysis and Intelligent Optimization of Process Industry Zhiqiang Geng, Xiang Zhang, Yongming Han, Xingxing Zhang, 2023-10-09 |
| energy trading data analytics: Blockchain-Based Systems for the Modern Energy Grid Sanjeevikumar Padmanaban, Rajesh Kumar Dhanaraj, Jens Bo Holm-Nielsen, Sathya Krishnamoorthi, Balamurugan Balusamy, 2022-09-13 Blockchain-Based Systems for a Paradigm Shift in the Energy Grid explores the technologies and tools to utilize blockchain for energy grids and assists professionals and researchers to find alternative solutions for the future of the energy sector. The focus of this globally edited book is on the application of blockchain technology and the balance between supply and demand for energy and where it is achievable. Looking at the integration of blockchain and how it will make the network resistant to any failure in sub-components, this book has very clearly explores the areas of energy sector that need in-depth study of Blockchain for expanding energy markets. Meeting the demands of energy by local trading, verifying use of green energy certificates and providing a greater understanding of smart energy grids and Blockchain use cases. Exhaustively exploring the use of Blockchain for energy, this reference useful for all those in the energy industry looking to avoid disruption in the grid and sustain and control successful flow of electricity. - Methods and techniques of Blockchain-based trading and payments are included - Provides process diagrams in techniques and balancing demand and supply - Internet of Energy and its architecture for the future energy sector is explained |
| energy trading data analytics: Decentralized Frameworks for Future Power Systems Mohsen Parsa Moghaddam, Reza Zamani, Hassan Haes Alhelou, Pierluigi Siano, 2022-05-12 Decentralized Frameworks for Future Power Systems: Operation, Planning and Control Perspectives is the first book to consider the principles and applications of decentralized decision-making in future power networks. The work opens by defining the emerging power system network as a system-of-systems (SoS), exploring the guiding principles behind optimal solutions for operation and planning problems. Chapters emphasize the role of regulations, prosumption behaviors, and the implementation of transactive energy processes as key components in decentralizing power systems. Contributors explore local markets, distribution system operation and proactive load management. The role of cryptocurrencies in smoothing transactive distributional challenges are presented. Final sections cover energy system planning, particularly in terms of consumer smart meter technologies and distributed optimization methods, including artificial intelligence, meta-heuristic, heuristic, mathematical and hybrid approaches. The work closes by considering decentralization across the cybersecurity, distributed control, market design and power quality optimization vertices. - Develops a novel framework for transactive energy management to enhance flexibility in future power systems - Explores interactions between multiple entities in local power markets based on a distributed optimization approach - Focuses on practical optimization, planning and control of smart grid systems towards decentralized decision-making |
| energy trading data analytics: Financial Accounting Paul D. Kimmel, Jerry J. Weygandt, Jill E. Mitchell, 2021-12-02 Financial Accounting: Tools for Business Decision Making by Paul Kimmel, Jerry Weygandt, and Jill Mitchell provides a practical introduction to financial accounting with a focus on how to use accounting information to make business decisions. Through significant course updates, the 10th Edition presents an active, hands-on approach to spark efficient and effective learning and develops the necessary skills to inspire and prepare students to be the accounting and business professionals of tomorrow. To ensure maximum understanding, students work through integrated assessment at different levels of difficulty right at the point of learning. The course's varied assessment also presents homework and assessment within real-world contexts to help students understand the why and the how of accounting information and business application. Throughout the course, students also work through various hands-on activities including Cookie Creations Cases, Expand Your Critical Thinking Questions, Excel Templates, and Analytics in Action problems, all within the accounting context. These applications all map to chapter material, making it easier for instructors to determine where and how to incorporate key skill development in their syllabus. With Financial Accounting, students will understand the foundations of financial accounting and develop the necessary tools for business decision-making, no matter what path they take. |
| energy trading data analytics: Applying Predictive Analytics Within the Service Sector Sahu, Rajendra, Dash, Manoj, Kumar, Anil, 2017-02-07 Value creation is a prime concern for any contemporary business. This can be accomplished through the incorporation of various techniques and processes, such as the integration of analytics to improve business functions. Applying Predictive Analytics Within the Service Sector is a pivotal reference source for the latest innovative perspectives on the incorporation of analysis techniques to enhance business performance. Examining a wide range of relevant topics, such as alternative clustering, recommender systems, and social media tools, this book is ideally designed for researchers, academics, students, professionals, and practitioners seeking scholarly material on business improvement in the service industry. |
A new age for energy and commodity trading - McKinsey & Company
2 Jun 2021 · Traders can employ five levers to tap new sources of value. Advises clients on energy markets and trading as well as smart grid, digital, and renewable technologies across the value chain. Advises clients in gas, power, and commodities markets on strategy, investment, growth, and transformation.
Data Analytics - Maximise Energy Trading Insight - Trayport
Data Analytics was built to support our trading clients, with a suite of sophisticated tools and features purpose-built for the energy markets. Utilise analytics tools to generate insights, spot trends, risks and opportunities to enhance your trading decisions. Develop powerful models and algorithms using the new Analytics API.
Driving digital transformation in energy trading: Key ...
Discover how AI, data analytics, and digital transformation are revolutionizing the energy sector, improving efficiency, sustainability, and customer support in trading and utilities.
Energy Trading Data Management – A Strategic Approach
11 Jun 2024 · Truly solving the data and analytics issue in energy trading requires a more strategic approach, one that is supportable, accessible, reliable and secure.
Energy Aspects - Global data & intelligence for energy ...
EA Quant models and tracks derivative flows across futures, options, and swaps markets. Our proprietary analytics offer daily comprehensive updates on positioning, risk, and trading activity of major financial traders, including CTAs, discretionary hedge funds, risk parity funds, and ETFs.
Energy Trading and Risk Management Systems Reviews ... - Gartner
An energy trading and risk management (ETRM) system is a software solution that can capture and manage wholesale energy market transactions, from execution to settlement, invoicing, managing, reporting market and credit exposures, and market integration for energy commodities.
Energy market modeling and data | Oil & Gas - McKinsey & Company
We provide strategic and tactical market intelligence services, access to distinctive energy market modeling, deep market insight, and proprietary data in the fields of energy markets and the energy transition.
A new age for energy and commodity trading - McKinsey & Company
2 Jun 2021 · Traders can employ five levers to tap new sources of value. Advises clients on energy markets and trading as well as smart grid, digital, and renewable technologies across the value chain. Advises clients in gas, power, and commodities markets on strategy, investment, growth, and transformation.
Data Analytics - Maximise Energy Trading Insight - Trayport
Data Analytics was built to support our trading clients, with a suite of sophisticated tools and features purpose-built for the energy markets. Utilise analytics tools to generate insights, spot trends, risks and opportunities to enhance your trading decisions. Develop powerful models and algorithms using the new Analytics API.
Driving digital transformation in energy trading: Key ...
Discover how AI, data analytics, and digital transformation are revolutionizing the energy sector, improving efficiency, sustainability, and customer support in trading and utilities.
Energy Trading Data Management – A Strategic Approach
11 Jun 2024 · Truly solving the data and analytics issue in energy trading requires a more strategic approach, one that is supportable, accessible, reliable and secure.
Energy Aspects - Global data & intelligence for energy ...
EA Quant models and tracks derivative flows across futures, options, and swaps markets. Our proprietary analytics offer daily comprehensive updates on positioning, risk, and trading activity of major financial traders, including CTAs, discretionary hedge funds, risk parity funds, and ETFs.
Energy Trading and Risk Management Systems Reviews ... - Gartner
An energy trading and risk management (ETRM) system is a software solution that can capture and manage wholesale energy market transactions, from execution to settlement, invoicing, managing, reporting market and credit exposures, and market integration for energy commodities.
Energy market modeling and data | Oil & Gas - McKinsey & Company
We provide strategic and tactical market intelligence services, access to distinctive energy market modeling, deep market insight, and proprietary data in the fields of energy markets and the energy transition.
