State Estimation in Low-observable Distribution Systems Using Matrix Completion: Preprint
Author: Yingchen Zhang
Publisher:
Published: 2019
Total Pages: 7
ISBN-13:
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Robust Matrix Completion State Estimation in Distribution Systems: Preprint
Author:
Publisher:
Published: 2019
Total Pages: 0
ISBN-13:
DOWNLOAD EBOOKDue to the insufficient measurements in the distribution system state estimation (DSSE), full observability and redundant measurements are difficult to achieve without using the pseudo measurements. The matrix completion state estimation (MCSE) combines the matrix completion and power system model to estimate voltage by exploring the low-rank characteristics of the matrix. This paper proposes a robust matrix completion state estimation (RMCSE) to estimate the voltage in a distribution system under a low-observability condition. Tradition state estimation weighted least squares (WLS) method requires full observability to calculate the states and needs redundant measurements to proceed a bad data detection. The proposed method improves the robustness of the MCSE to bad data by minimizing the rank of the matrix and measurements residual with different weights. It can estimate the system state in a low-observability system and has robust estimates without the bad data detection process in the face of multiple bad data. The method is numerically evaluated on the IEEE 33-node radial distribution system. The estimation performance and robustness of RMCSE are compared with the WLS with the largest normalized residual bad data identification (WLS-LNR), and the MCSE.
Power System State Estimation
Author: Ali Abur
Publisher: CRC Press
Published: 2004-03-24
Total Pages: 350
ISBN-13: 9780203913673
DOWNLOAD EBOOKOffering an up-to-date account of the strategies utilized in state estimation of electric power systems, this text provides a broad overview of power system operation and the role of state estimation in overall energy management. It uses an abundance of examples, models, tables, and guidelines to clearly examine new aspects of state estimation, the testing of network observability, and methods to assure computational efficiency. Includes numerous tutorial examples that fully analyze problems posed by the inclusion of current measurements in existing state estimators and illustrate practical solutions to these challenges. Written by two expert researchers in the field, Power System State Estimation extensively details topics never before covered in depth in any other text, including novel robust state estimation methods, estimation of parameter and topology errors, and the use of ampere measurements for state estimation. It introduces various methods and computational issues involved in the formulation and implementation of the weighted least squares (WLS) approach, presents statistical tests for the detection and identification of bad data in system measurements, and reveals alternative topological and numerical formulations for the network observability problem.
Feedback Systems
Author: Karl Johan Åström
Publisher: Princeton University Press
Published: 2021-02-02
Total Pages:
ISBN-13: 069121347X
DOWNLOAD EBOOKThe essential introduction to the principles and applications of feedback systems—now fully revised and expanded This textbook covers the mathematics needed to model, analyze, and design feedback systems. Now more user-friendly than ever, this revised and expanded edition of Feedback Systems is a one-volume resource for students and researchers in mathematics and engineering. It has applications across a range of disciplines that utilize feedback in physical, biological, information, and economic systems. Karl Åström and Richard Murray use techniques from physics, computer science, and operations research to introduce control-oriented modeling. They begin with state space tools for analysis and design, including stability of solutions, Lyapunov functions, reachability, state feedback observability, and estimators. The matrix exponential plays a central role in the analysis of linear control systems, allowing a concise development of many of the key concepts for this class of models. Åström and Murray then develop and explain tools in the frequency domain, including transfer functions, Nyquist analysis, PID control, frequency domain design, and robustness. Features a new chapter on design principles and tools, illustrating the types of problems that can be solved using feedback Includes a new chapter on fundamental limits and new material on the Routh-Hurwitz criterion and root locus plots Provides exercises at the end of every chapter Comes with an electronic solutions manual An ideal textbook for undergraduate and graduate students Indispensable for researchers seeking a self-contained resource on control theory
Probabilistic Robotics
Author: Sebastian Thrun
Publisher: MIT Press
Published: 2005-08-19
Total Pages: 668
ISBN-13: 0262201623
DOWNLOAD EBOOKAn introduction to the techniques and algorithms of the newest field in robotics. Probabilistic robotics is a new and growing area in robotics, concerned with perception and control in the face of uncertainty. Building on the field of mathematical statistics, probabilistic robotics endows robots with a new level of robustness in real-world situations. This book introduces the reader to a wealth of techniques and algorithms in the field. All algorithms are based on a single overarching mathematical foundation. Each chapter provides example implementations in pseudo code, detailed mathematical derivations, discussions from a practitioner's perspective, and extensive lists of exercises and class projects. The book's Web site, www.probabilistic-robotics.org, has additional material. The book is relevant for anyone involved in robotic software development and scientific research. It will also be of interest to applied statisticians and engineers dealing with real-world sensor data.
Optimization by Vector Space Methods
Author: David G. Luenberger
Publisher: John Wiley & Sons
Published: 1997-01-23
Total Pages: 348
ISBN-13: 9780471181170
DOWNLOAD EBOOKEngineers must make decisions regarding the distribution of expensive resources in a manner that will be economically beneficial. This problem can be realistically formulated and logically analyzed with optimization theory. This book shows engineers how to use optimization theory to solve complex problems. Unifies the large field of optimization with a few geometric principles. Covers functional analysis with a minimum of mathematics. Contains problems that relate to the applications in the book.
The Economics of Artificial Intelligence
Author: Ajay Agrawal
Publisher: University of Chicago Press
Published: 2024-03-05
Total Pages: 172
ISBN-13: 0226833127
DOWNLOAD EBOOKA timely investigation of the potential economic effects, both realized and unrealized, of artificial intelligence within the United States healthcare system. In sweeping conversations about the impact of artificial intelligence on many sectors of the economy, healthcare has received relatively little attention. Yet it seems unlikely that an industry that represents nearly one-fifth of the economy could escape the efficiency and cost-driven disruptions of AI. The Economics of Artificial Intelligence: Health Care Challenges brings together contributions from health economists, physicians, philosophers, and scholars in law, public health, and machine learning to identify the primary barriers to entry of AI in the healthcare sector. Across original papers and in wide-ranging responses, the contributors analyze barriers of four types: incentives, management, data availability, and regulation. They also suggest that AI has the potential to improve outcomes and lower costs. Understanding both the benefits of and barriers to AI adoption is essential for designing policies that will affect the evolution of the healthcare system.
Subspace Identification for Linear Systems
Author: Peter van Overschee
Publisher: Springer Science & Business Media
Published: 2012-12-06
Total Pages: 263
ISBN-13: 1461304652
DOWNLOAD EBOOKSubspace Identification for Linear Systems focuses on the theory, implementation and applications of subspace identification algorithms for linear time-invariant finite- dimensional dynamical systems. These algorithms allow for a fast, straightforward and accurate determination of linear multivariable models from measured input-output data. The theory of subspace identification algorithms is presented in detail. Several chapters are devoted to deterministic, stochastic and combined deterministic-stochastic subspace identification algorithms. For each case, the geometric properties are stated in a main 'subspace' Theorem. Relations to existing algorithms and literature are explored, as are the interconnections between different subspace algorithms. The subspace identification theory is linked to the theory of frequency weighted model reduction, which leads to new interpretations and insights. The implementation of subspace identification algorithms is discussed in terms of the robust and computationally efficient RQ and singular value decompositions, which are well-established algorithms from numerical linear algebra. The algorithms are implemented in combination with a whole set of classical identification algorithms, processing and validation tools in Xmath's ISID, a commercially available graphical user interface toolbox. The basic subspace algorithms in the book are also implemented in a set of Matlab files accompanying the book. An application of ISID to an industrial glass tube manufacturing process is presented in detail, illustrating the power and user-friendliness of the subspace identification algorithms and of their implementation in ISID. The identified model allows for an optimal control of the process, leading to a significant enhancement of the production quality. The applicability of subspace identification algorithms in industry is further illustrated with the application of the Matlab files to ten practical problems. Since all necessary data and Matlab files are included, the reader can easily step through these applications, and thus get more insight in the algorithms. Subspace Identification for Linear Systems is an important reference for all researchers in system theory, control theory, signal processing, automization, mechatronics, chemical, electrical, mechanical and aeronautical engineering.
Computer Modelling of Electrical Power Systems
Author: Jos Arrillaga
Publisher:
Published: 1983
Total Pages: 450
ISBN-13:
DOWNLOAD EBOOKDescribes the use of power system component models and efficient computational techniques in the development of a new generation of programs representing the steady and dynamic states of electrical power systems. Presents main computational and transmission system developments. Derives steady state models of a.c. and d.c. power systems plant components, describes a general purpose phase a.c. load flow program emphasizing Newton Fast Decoupled Algorithm, and more. Considers all aspects of the power system in the dynamic state.
Power System Monitoring and Control
Author: Hassan Bevrani
Publisher: John Wiley & Sons
Published: 2014-06-09
Total Pages: 288
ISBN-13: 1118450698
DOWNLOAD EBOOKPOWER SYSTEM MONITORING AND CONTROL An invaluable resource for addressing the myriad critical technical engineering considerations in modern electric power system design and operation Power System Monitoring and Control (PSMC) is becoming increasingly significant in the design, planning, and operation of modern electric power systems. In response to the existing challenge of integrating advanced metering, computation, communication, and control into appropriate levels of PSMC, Power System Monitoring and Control presents a comprehensive overview of the basic principles and key technologies for the monitoring, protection, and control of contemporary wide-area power systems. A variety of topical issues are addressed, including renewable energy sources, smart grids, wide area stabilizing, coordinated voltage regulation and angle oscillation damping—as well as the advantages of phasor measurement units (PMUs) and global positioning system (GPS) time signal. Analysis and synthesis examples, along with case studies, add depth and clarity to all topics. Provides an up-to-date and comprehensive reference for researchers and engineers working on wide-area PSMC Links fundamental concepts of PSMC, advanced metering and control theory/techniques, and practical engineering considerations Covers PSMC problem understanding, design, practical aspects, and topics such as smart grid and coordinated angle oscillation damping and voltage regulation Incorporates the authors’ experiences teaching and researching in international locales including Japan, Singapore, Malaysia, and Australia Power System Monitoring and Control is ideally suited for a graduate course on this topic. It is also a practical reference for researchers and professional engineers working in power system monitoring, dynamic stability and control.
