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Although the state estimator has been a regular application running in many utility control centers for over four decades, detection and identification of bad data (outliers) among the input measurements continues to be a difficult task. The widely adopted Weighted Least Square formulation of the power system static state estimation is known to be vulnerable to presence of bad data and even a single bad data can significantly impact the solution quality. Since the estimate of system state obtained from state estimation serves as starting point for many security and market related downstream applications that run within a control center, the problem of detection and identification of bad data is important. It has been shown that the traditionally used methods of detection and/or identification of bad data in power system static state estimation suffer from drawbacks like failing to detect mild to medium bad data in leverage measurements and excessive false detection rates. The traditional approach to process multiple bad data has been successive elimination (of single bad data) and re-estimation. This approach is highly computationally intensive and time consuming. The problem of computationally intensive multiple bad data processing has an even greater bearing on the Linear State Estimator, which is expected to run every second or potentially at sub-second intervals in the control centers.The work presented here focuses on the problem of multiple bad data processing in power system static state estimation in two ways. Firstly, use of Custom Thresholds is proposed for detection of bad data. The Custom Thresholds are shown to exhibit better false detection performance while being sensitive to mild bad data, even in leverage measurements. Secondly, a new algorithm is proposed to identify the culprit bad measurements. The proposed algorithm utilizes the very nature of bad data in different types of measurements, to accomplish the processing within few cycles of successive elimination and re-estimation. The efficiency and accuracy of the proposed algorithm is validated through thousands of simulations on various standard test systems. The proposed algorithm can be easily integrated in any commercial Weighted Least Square power system static state estimation - linear or iterative.
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.
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.
Power system state estimation (SE) is one of the most fundamental applications at the control center, since it helps the system operator to monitor, control and optimize the performance of the power grid. Motivated by the advancements in synchronized phasor measurement units and the urgent need of a better state estimator to address the corresponding system complexity and computational burden, we focus on improving the resilience and efficiency of SE while incorporating synchrophasor measurements. Different types of cyber attacks are threatening the resilience of power system control and operations, while GPS spoofing attack (GSA) has been proved to be one of the most imminent threats to the recent modernization of the power grid. More specifically, it may greatly jeopardize the benefits brought by the pervasively installed phasor measurement units (PMUs). We consider the case where synchrophasor data from PMUs are compromised due to the presence of single or multiple GSAs, and show that this can be corrected by signal processing techniques. We introduce a statistical model for synchrophasor-based power system SE, then derive the spoofing-matched algorithms for GPS-spoofed synchrophasor data correction. Different testing scenarios based on IEEE 14-, 30-, 57-, 118-bus systems are simulated to show the proposed algorithms' performance on GSA detection as well as state estimation. Numerical results demonstrate that our proposed algorithms can consistently locate and correct the spoofed synchrophasor data with good accuracy. The accuracy of state estimation is significantly improved compared with the traditional weighted least square method and approaches the performance of Genie-aided method. To improve the efficiency of SE, we focus on a potential solution for the state estimation in the control room: decentralized multi-area state estimation (MASE) with synchrophasor measurements. A synchrophasor-assisted hybrid MASE algorithm has been proposed to tackle this problem, where the boundary bus state estimates generated from the tie-line based synchrophasor-only linear SE are transformed into the equality constraints imposed upon the local SE in each area, which makes it truly independent from others. Numerical simulations have been implemented in the IEEE 14-bus and 30-bus systems, and the simulation results show that the proposed algorithm can not only provide system state estimates with good accuracy, but also can speed up the computational process of SE for the entire system.
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.
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.