Download or read book Distributed learning optimization and control methods for future power grids written by Zhi-Wei Liu and published by Frontiers Media SA. This book was released on 2024-01-02 with total page 104 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Distributed Control and Optimization Technologies in Smart Grid Systems written by Fanghong Guo and published by CRC Press. This book was released on 2017-11-09 with total page 192 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book aims to equalize the theoretical involvement with industrial practicality and build a bridge between academia and industry by reducing the mathematical difficulties. It provides an overview of distributed control and distributed optimization theory, followed by specific details on industrial applications to smart grid systems, with a special focus on micro grid systems. Each of the chapters is written and organized with an introductory section tailored to provide the essential background of the theories required. The text includes industrial applications to realistic renewable energy systems problems and illustrates the application of proposed toolsets to control and optimization of smart grid systems.

Download or read book Big Data Analytics in Future Power Systems written by Ahmed F. Zobaa and published by CRC Press. This book was released on 2018-08-14 with total page 269 pages. Available in PDF, EPUB and Kindle. Book excerpt: Power systems are increasingly collecting large amounts of data due to the expansion of the Internet of Things into power grids. In a smart grids scenario, a huge number of intelligent devices will be connected with almost no human intervention characterizing a machine-to-machine scenario, which is one of the pillars of the Internet of Things. The book characterizes and evaluates how the emerging growth of data in communications networks applied to smart grids will impact the grid efficiency and reliability. Additionally, this book discusses the various security concerns that become manifest with Big Data and expanded communications in power grids. Provide a general description and definition of big data, which has been gaining significant attention in the research community. Introduces a comprehensive overview of big data optimization methods in power system. Reviews the communication devices used in critical infrastructure, especially power systems; security methods available to vet the identity of devices; and general security threats in CI networks. Presents applications in power systems, such as power flow and protection. Reviews electricity theft concerns and the wide variety of data-driven techniques and applications developed for electricity theft detection.

Download or read book Distributed Energy Management of Electrical Power Systems written by Yinliang Xu and published by John Wiley & Sons. This book was released on 2021-01-13 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: Go in-depth with this comprehensive discussion of distributed energy management Distributed Energy Management of Electrical Power Systems provides the most complete analysis of fully distributed control approaches and their applications for electric power systems available today. Authored by four respected leaders in the field, the book covers the technical aspects of control, operation management, and optimization of electric power systems. In each chapter, the book covers the foundations and fundamentals of the topic under discussion. It then moves on to more advanced applications. Topics reviewed in the book include: System-level coordinated control Optimization of active and reactive power in power grids The coordinated control of distributed generation, elastic load and energy storage systems Distributed Energy Management incorporates discussions of emerging and future technologies and their potential effects on electrical power systems. The increased impact of renewable energy sources is also covered. Perfect for industry practitioners and graduate students in the field of power systems, Distributed Energy Management remains the leading reference for anyone with an interest in its fascinating subject matter.

Download or read book Control and Optimization Methods for Electric Smart Grids written by Aranya Chakrabortty and published by Springer Science & Business Media. This book was released on 2011-12-16 with total page 377 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this book, leading experts in power, control and communication systems discuss the most promising recent research in smart grid modeling, control and optimization. The book goes on to the foundation for future advances in this critical field of study.

Download or read book Control and Optimization of Distributed Generation Systems written by Magdi S. Mahmoud and published by Springer. This book was released on 2016-10-13 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text is an introduction to the use of control in distributed power generation. It shows the reader how reliable control can be achieved so as to realize the potential of small networks of diverse energy sources, either singly or in coordination, for meeting concerns of energy cost, energy security and environmental protection. The book demonstrates how such microgrids, interconnecting groups of generating units and loads within a local area, can be an effective means of balancing electrical supply and demand. It takes advantage of the ability to connect and disconnect microgrids from the main body of the power grid to give flexibility in response to special events, planned or unplanned. In order to capture the main opportunities for expanding the power grid and to present the plethora of associated open problems in control theory Control and Optimization of Distributed Generation Systems is organized to treat three key themes, namely: system architecture and integration; modelling and analysis; and communications and control. Each chapter makes use of examples and simulations and appropriate problems to help the reader study. Tools helpful to the reader in accessing the mathematical analysis presented within the main body of the book are given in an appendix. Control and Optimization of Distributed Generation Systems will enable readers new to the field of distributed power generation and networked control, whether experienced academic migrating from another field or graduate student beginning a research career, to familiarize themselves with the important points of the control and regulation of microgrids. It will also be useful for practising power engineers wishing to keep abreast of changes in power grids necessitated by the diversification of generating methods.

Download or read book Distributed Optimization for the DER Rich Electric Power Grid written by JANNATUL ADAN; ANURAG K. SRIVASTAVA. and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a detailed overview of possible applications of distributed optimization in power systems. Centralized algorithms are widely used for optimization and control in power system applications. These algorithms require all the measurements and data to be accumulated at a central location and hence suffer from single-point-of-failure. Additionally, these algorithms lack scalability in the number of sensors and actuators, especially with the increasing integration of distributed energy resources (DERs). As the power system becomes a confluence of a diverse set of decision-making entities with a multitude of objectives, the preservation of privacy and operation of the system with limited information has been a growing concern. Distributed optimization techniques solve these challenges while also ensuring resilient computational solutions for the power system operation in the presence of both natural and man-made adversaries. There are numerous commonly-used distributed optimization approaches, and a comprehensive classification of these is discussed and detailed in this work. All of these algorithms have displayed efficient identification of global optimum solutions for convex continuous distributed optimization problems. The algorithms discussed in the literature thus far are predominantly used to manage continuous state variables, however, the inclusion of integer variables in the decision support is needed for specific power system problems.The mixed integer programming (MIP) problem arises in a power system operation and control due to tap changing transformers, capacitors and switches. There are numerous global optimization techniques for MIPs. Whilst most are able to solve NP-hard convexified MIP problems centrally, they are time consuming and do not scale well for large scale distributed problems. Decomposition and a solution approach of distributed coordination can help to resolve the scalability issue. Despite the fact that a large body of work on the centralized solution methods for convexified MIP problems already exists, the literature on distributed MIPs is relatively limited. The distributed optimization algorithms applied in power networks to solve MIPs are included in this book. Machine Learning (ML) based solutions can help to get faster convergence for distributed optimization or can replace optimization techniques depending on the problem. Finally, a summary and path forward are provided, and the advancement needed in distributed optimization for the power grid is also presented.

Download or read book Modern Optimization Techniques for Smart Grids written by Adel Ali Abou El-Ela and published by Springer Nature. This book was released on 2022-09-15 with total page 237 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modern Optimization Techniques for Smart Grids presents current research and methods for monitoring transmission systems and enhancing distribution system performance using optimization techniques considering the role of different single and multi-objective functions. The authors present in-depth information on integrated systems for smart transmission and distribution, including using smart meters such as phasor measurement units (PMUs), enhancing distribution system performance using the optimal placement of distributed generations (DGs) and/or capacitor banks, and optimal capacitor placement for power loss reduction and voltage profile improvement. The book will be a valuable reference for researchers, students, and engineers working in electrical power engineering and renewable energy systems. Predicts future development of hybrid power systems; Introduces enhanced optimization strategies; Includes MATLAB M-file codes.

Download or read book Advanced Technologies for Modeling Optimization and Control of the Future Distribution Grid written by Ningyi Dai and published by Frontiers Media SA. This book was released on 2022-04-20 with total page 132 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book A Proximal Atomic Coordination Algorithm for Distributed Optimization in Distribution Grids written by Jordan Joseph Romvary and published by . This book was released on 2018 with total page 304 pages. Available in PDF, EPUB and Kindle. Book excerpt: The control and regulation of power grids has historically relied upon large-scale scheduleable generation and relatively stable load demand profiles. With the advent of extensive local renewable energy generation technologies as well as the incorporation of load responsive demand response (DR) methodologies, it has become imperative that new distributed control strategies are developed to better regulate the increasingly volatile nature of modern generation and load profiles. In this thesis, we introduce a distributed control strategy called Proximal Atomic Coordination (PAC) to solve for optimal control strategies in distributed power grids, a problem called Optimal Power Flow (OPF). Using a convex relaxed variant of OPF, we show that PAC exhibits sub-linear convergence to the optimal ergodic cost, and linear convergence to the OPF solution. We demonstrate our results on various power grid topologies with large levels of renewable energy penetration and DR, and show that PAC converges to optimal control profiles in these scenarios. We further show that in certain regimes PAC outperforms the standard distributed 2-Block ADMM algorithm, and we discuss the benefits of using PAC over 2-Block ADMM and other standard distributed solvers.

Download or read book Distributed Optimization for the DER Rich Electric Power Grid written by Jannatul Adan and published by . This book was released on 2023-11 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a detailed overview of possible applications of distributed optimization in power systems. Centralized algorithms are widely used for optimization and control in power system applications. These algorithms require all the measurements and data to be accumulated at a central location and hence suffer from single-point-of-failure. Additionally, these algorithms lack scalability in the number of sensors and actuators, especially with the increasing integration of distributed energy resources (DERs). As the power system becomes a confluence of a diverse set of decision-making entities with a multitude of objectives, the preservation of privacy and operation of the system with limited information has been a growing concern. Distributed optimization techniques solve these challenges while also ensuring resilient computational solutions for the power system operation in the presence of both natural and man-made adversaries. There are numerous commonly-used distributed optimization approaches, and a comprehensive classification of these is discussed and detailed in this work. All of these algorithms have displayed efficient identification of global optimum solutions for convex continuous distributed optimization problems. The algorithms discussed in the literature thus far are predominantly used to manage continuous state variables, however, the inclusion of integer variables in the decision support is needed for specific power system problems.The mixed integer programming (MIP) problem arises in a power system operation and control due to tap changing transformers, capacitors and switches. There are numerous global optimization techniques for MIPs. Whilst most are able to solve NP-hard convexified MIP problems centrally, they are time consuming and do not scale well for large scale distributed problems. Decomposition and a solution approach of distributed coordination can help to resolve the scalability issue. Despite the fact that a large body of work on the centralized solution methods for convexified MIP problems already exists, the literature on distributed MIPs is relatively limited. The distributed optimization algorithms applied in power networks to solve MIPs are included in this book. Machine Learning (ML) based solutions can help to get faster convergence for distributed optimization or can replace optimization techniques depending on the problem. Finally, a summary and path forward are provided, and the advancement needed in distributed optimization for the power grid is also presented.

Download or read book Distributed Optimization with Application to Power Systems and Control written by Engelmann, Alexander and published by KIT Scientific Publishing. This book was released on 2022-11-21 with total page 226 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mathematical optimization techniques are among the most successful tools for controlling technical systems optimally with feasibility guarantees. Yet, they are often centralized—all data has to be collected in one central and computationally powerful entity. Methods from distributed optimization overcome this limitation. Classical approaches, however, are often not applicable due to non-convexities. This work develops one of the first frameworks for distributed non-convex optimization.

Download or read book Distributed Economic Operation in Smart Grid Model Based and Model Free Perspectives written by Jiahu Qin and published by Springer Nature. This book was released on 2023-01-25 with total page 246 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book aims to work out the distributed economic operation in smart grids in a systematic way, which ranges from model-based to model-free perspectives. The main contributions of this book can be summarized into three folds. First, we investigate the fundamental economic operation problems in smart grids from model-based perspective. Specifically, these problems can be modeled as deterministic optimization models, and we propose some distributed optimization algorithms by integrating the multi-agent consensus theory and optimization techniques to achieve the distributed coordination of various generation units and loads. Second, due to the randomness of the large-scale renewable energies and the flexibility of the loads, we further address these economic operation problems from a model-free perspective, and we propose learning-based approaches to address the uncertainty and randomness. At last, we extend the idea of model-based and model-free algorithms to plug-in electric vehicles (PEVs) charging/discharging scheduling problem, the key challenge of which involves multiple objectives simultaneously while the behavior of PEVs and the electricity price are intrinsically random. This book presents several recent theoretical findings on distributed economic operation in smart grids from model-based and model-free perspectives. By systematically integrating novel ideas, fresh insights, and rigorous results, this book provides a base for further theoretical research on distributed economic operation in smart grids. It can be a reference for graduates and researchers to study the operation and management in smart grids. Some prerequisites for reading this book include optimization theory, matrix theory, game theory, reinforcement learning, etc.

Download or read book Big Data Optimization for Distributed Resource Management in Smart Grid written by Hung Khanh Nguyen and published by . This book was released on 2017 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Electric power grids are experiencing the increasing adoption of distributed energy resources, which can bring huge economical and environmental benefit. However, the large-scale penetration of distributed energy resources will make both operations and long-term planning to be more and more complex due to the higher degree of output variability than traditional centralized sources. This variability creates irresistible challenges for grid operators to ensure system security and reliability. In addition, traditional optimization algorithms are no longer applicable for such integrated and complex systems in which economic efficiency, grid reliability, and privacy need to be simultaneously satisfied. Therefore, an innovative optimization framework is critical to tackle the emerging challenges due to the large-scale and independent decision-making nature of distributed resource management problem in the future power system. In this dissertation, we focus on the application of big data optimization methods for distributed resource management problem in smart grid to improve the reliability and security of the distribution system. First, we propose an incentive mechanism design to motivate microgrids to participate in the peak ramp minimization problem for the system to mitigate the ramping effect due to the high penetration of distributed renewable generations. Distributed algorithms to achieve the optimal operation point are proposed, which allow microgrids to execute their computation in either synchronous fashion or asynchronous fashion. Second, a large-scale optimization problem for microgrid optimal scheduling and the load curtailment problem is formulated. We propose a decomposition algorithm and implement parallel computation for the proposed algorithm to run on a computer cluster using the Hadoop MapReduce software framework. Third, a decentralized reactive power compensation model is studied to reduce the power losses and improve the voltage profile for distribution networks. Finally, we consider big data optimization methods for resource allocation problem in wireless network virtualization to prevent traffic disruption against physical network failures.

Download or read book Intelligent Solutions for Sustainable Power Grids written by Ashok Kumar, L. and published by IGI Global. This book was released on 2024-05-01 with total page 478 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the environment of energy systems, the effective utilization of both conventional and renewable sources poses a major challenge. The integration of microgrid systems, crucial for harnessing energy from distributed sources, demands intricate solutions due to the inherent intermittency of these sources. Academic scholars engaged in power system research find themselves at the forefront of addressing issues such as energy source estimation, coordination in dynamic environments, and the effective utilization of artificial intelligence (AI) techniques. Intelligent Solutions for Sustainable Power Grids focuses on emerging research areas, this book addresses the uncertainty of renewable energy sources, employs state-of-the-art forecasting techniques, and explores the application of AI techniques for enhanced power system operations. From economic aspects to the digitalization of power systems, the book provides a holistic approach. Tailored for undergraduate and postgraduate students as well as seasoned researchers, it offers a roadmap to navigate the intricate landscape of modern power systems. Dive into a wealth of knowledge encompassing smart energy systems, renewable energy integration, stability analysis of microgrids, power quality enhancement, and much more. This book is not just a guide; it is the solution to the pressing challenges in the dynamic field of energy systems.

Download or read book Applications of Deep Machine Learning in Future Energy Systems written by Mohammad-Hassan Khooban and published by Elsevier. This book was released on 2024-08-20 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: Applications of Deep Machine Learning in Future Energy Systems pushes the limits of current Artificial Intelligence techniques to present deep machine learning suitable for the complexity of sustainable energy systems. The first two chapters take the reader through the latest trends in power engineering and system design and operation, before laying out the current AI approaches and our outstanding limitations. Later chapters provide in-depth accounts of specific challenges and the use of innovative third-generation machine learning, including neuromorphic computing, to resolve issues from security to power supply. An essential tool for the management, control, and modelling of future energy systems, Applications of Deep Machine Learning maps a practical path towards AI capable of supporting sustainable energy. - Clarifies the current state and future trends of energy system machine learning and the pitfalls facing our transitioning systems - Provides guidance on 3rd-generation AI tools for meeting the challenges of modeling and control in modern energy systems - Includes case studies and practical examples of potential applications to inspire and inform researchers and industry developers

Download or read book Decentralized Frameworks for Future Power Systems written by Mohsen Parsa Moghaddam and published by Academic Press. This book was released on 2022-05-12 with total page 502 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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