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Cyber-Physical Power System State Estimation updates classic state estimation tools to enable real-time operations and optimize reliability in modern electric power systems. The work introduces and contextualizes the core concepts and classic approaches to state estimation modeling. It builds on these classic approaches with a suite of data-driven models and non-synchronized measurement tools to reflect current measurement trends required by increasingly more sophisticated grids. Chapters outline core definitions, concepts and the network analysis procedures involved in the real-time operation of EPS. Specific sections introduce power flow problem in EPS, highlighting network component modeling and power flow equations for state estimation before addressing quasi static state estimation in electrical power systems using Weighted Least Squares (WLS) classical and alternatives formulations. Particularities of the state estimation process in distribution systems are also considered. Finally, the work goes on to address observability analysis, measurement redundancy and the processing of gross errors through the analysis of WLS static state estimator residuals. Develops advanced approaches to smart grid real-time monitoring through quasi-static model state estimation and non-synchronized measurements system models Presents a novel, extended optimization, physics-based model which identifies and corrects for measurement error presently egregiously discounted in classic models Demonstrates how to embed cyber-physical security into smart grids for real-time monitoring Introduces new approaches to calculate power flow in distribution systems and for estimating distribution system states Incorporates machine-learning based approaches to complement the state estimation process, including pattern recognition-based solutions, principal component analysis and support vector machines
State Estimation in Electric Power Systems: A Generalized Approach provides for the first time a comprehensive introduction to the topic of state estimation at an advanced textbook level. The theory as well as practice of weighted least squares (WLS) is covered with significant rigor. Included are an in depth analysis of power flow basics, proper justification of Stott's decoupled method, observability theory and matrix solution methods. In terms of practical application, topics such as bad data analysis, combinatorial bad data analysis and multiple snap shot estimation are covered. The book caters both to the specialist as well as the newcomer to the field. State estimation will play a crucial role in the emerging scenario of a deregulated power industry. Many market decisions will be based on knowing the present state of the system accurately. State Estimation in Electric Power Systems: A Generalized Approach crystallizes thirty years of WLS state estimation theory and practice in power systems and focuses on techniques adopted by state estimation developers worldwide. The book also reflects the experience of developing industrial-grade state estimation software that is used in the USA, South America, and many other places in world.
State estimation is one of the most important functions in power system operation and control. This area is concerned with the overall monitoring, control, and contingency evaluation of power systems. It is mainly aimed at providing a reliable estimate of system voltages. State estimator information flows to control centers, where critical decisions are made concerning power system design and operations. This valuable resource provides thorough coverage of this area, helping professionals overcome challenges involving system quality, reliability, security, stability, and economy. Engineers are introduced to new techniques for their work in the field, including current measurements and phasor measurement units. Moreover, the book includes a novel discussion on state estimation for distributed systems. Professionals find expert guidance for their current projects and discover cutting-edge developments that will help prepare them for work with future energy management systems.
A guide to the role of static state estimation in the mitigation of potential system failures With contributions from a noted panel of experts on the topic, Advances in Electric Power and Energy: Static State Estimation addresses the wide-range of issues concerning static state estimation as a main energy control function and major tool for evaluating prevailing operating conditions in electric power systems worldwide. This book is an essential guide for system operators who must be fully aware of potential threats to the integrity of their own and neighboring systems. The contributors provide an overview of the topic and review common threats such as cascading black-outs to model-based anomaly detection to the operation of micro-grids and much more. The book also includes a discussion of an effective mathematical programming approach to state estimation in power systems. Advances in Electric Power and Energy reviews the most recent developments in the field and: Offers an introduction to the topic to help non-experts (and professionals) get up-to-date on static state estimation Covers the essential information needed to understand power system state estimation written by experts on the subject Discusses a mathematical programming approach Written for electric power system planners, operators, consultants, power system software developers, and academics, Advances in Electric Power and Energy is the authoritative guide to the topic with contributions from experts who review the most recent developments.
Offering 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.
The heart of the data processing activities of a modern electric utility energy control center is the power system state estimator. A state estimator provides the same information on-line that are provided by a load flow study off-line. This information is used for contingency evaluation, security assessment, control strategy and economic dispatch. An energy control center gathers information on the state of a power system that may include large errors which called bad data. In view of the above consideration, it is necessary to have a method to establish a reliable and complete data base for on-line monitoring and control. In this book, the fast supper decoupled state (FSDS) estimator is developed and applied to systems having low as well as high R/X ratio lines, well-behaved systems, ill-conditioned systems as well as bad data processing. The FSDS estimator is investigated using a single-rotation angle for all measurements. Comparisons are made with respect to the fast decoupled state estimator. The FSDS estimator is found to be efficient and effective especially for systems having high R/X ratio lines, ill-conditioned system and bad data.
"A static state estimator (SSE) is a collection of digital computer programs which convert telemetered data into a reliable estimate of the transmission network structure and state by accounting for small random metering-communication errors; uncertainties in system parameter values; bad data due to transients and meter-communication failures; and errors in the network structure due to faulty switch-circuit breaker status information. Failure of SSE at System Operators' facilities has been cited as one of the primary causes for some major blackouts over the two decades"--
Computer Aided State Estimation of Electric Power Networks is a fundamental introduction to the topic of state estimation at an advanced textbook level for teaching a course at either the graduate or undergraduate level, as well as for Post Graduate students and Research Scholars who want to review of the latest techniques and best mathematical approaches for estimating the state of a general system. Theory as well as practice of Distribution System State Estimation (DSSE) is covered with imperative rigidity. The authors present the theory of state estimation clearly providing the right amount of essential information and linked reports in order to enable the researchers and graduate students to apply state estimation techniques across a variety of fields in power systems engineering. A prerequisite knowledge of basic power system operation, control, data acquisition and measurement, in addition to basic statistics is helpful in understanding the book. Key Features include: • Advanced Topics based on Cloud Computing and Standards used for Preparation of Smart Grid • Provides Entire Coding Information for Estimating the State Estimation Topology Performance • Enables both the Researchers and Graduate Students for Pursuing their Research Projects • Covers the Important Topics on Data Attacks and Solution Strategy • Provides an Introduction to Distribution System State Estimation This book includes new contents like Distribution System State Estimation, Data Attacks, Defense strategies, with an introduction to large scale systems based on cloud computing, and an MATLAB training package for graduate students
The system operator faced high level of uncertainties due to the evolving complexity of the electric power systems. Therefore, efficient solutions for power system prediction, monitoring and state estimation can be found in new methods. These methods improve the secure operations of the network. This thesis covers three different state estimations incorporating static, tracking, and dynamic state estimation in order to estimate all possible operating conditions of power systems. This research also introduces new meta heuristic methods such as stochastic and fractal search technique. The SFS technique is implemented in real time nonlinear power system applications under various scenarios. New methodology of multilayer neural networks exhibited in composite typologies are proposed in this thesis to improve the estimation performance. Optimized Neural Network by Stochastic Fractal Search technique is used and applied to both tracking and dynamic state estimation. The proposed methods are validated utilizing diverse benchmark optimization methods. The combination of conventional and synchronized measurement is also studied in this thesis. This is used to increase the reliability of electric power systems in realtime. Additionally, the research is extended to evaluate the benefits of multiarea state estimators and how it uses to reduce the computational time. Finally, all formulations proposed in this work were validated in different IEEE test systems.