다중혈관 관상동맥 환자에서 y-문합을 이용하여 양쪽 내흉동맥만을 사용한 우회술의 조기 성적

The purpose of this paper is to provide a comprehensive presentation and interpretation of the Ensemble Kalman Filter (EnKF) and its numerical implementation. The EnKF has a large user group, and numerous publications have discussed applications and theoretical aspects of it. This paper reviews the important results from these studies and also presents new ideas and alternative interpretations which further explain the success of the EnKF. In addition to providing the theoretical framework needed for using the EnKF, there is also a focus on the algorithmic formulation and optimal numerical implementation. A program listing is given for some of the key subroutines. The paper also touches upon specific issues such as the use of nonlinear measurements, in situ profiles of temperature and salinity, and data which are available with high frequency in time. An ensemble based optimal interpolation (EnOI) scheme is presented as a cost-effective approach which may serve as an alternative to the EnKF in some applications. A fairly extensive discussion is devoted to the use of time correlated model errors and the estimation of model bias.

The Ensemble Kalman Filter: Theoretical formulation and practical implementation

The Smart Grid, regarded as the next generation power grid, uses two-way flows of electricity and information to create a widely distributed automated energy delivery network. In this article, we survey the literature till 2011 on the enabling technologies for the Smart Grid. We explore three major systems, namely the smart infrastructure system, the smart management system, and the smart protection system. We also propose possible future directions in each system. colorred{Specifically, for the smart infrastructure system, we explore the smart energy subsystem, the smart information subsystem, and the smart communication subsystem.} For the smart management system, we explore various management objectives, such as improving energy efficiency, profiling demand, maximizing utility, reducing cost, and controlling emission. We also explore various management methods to achieve these objectives. For the smart protection system, we explore various failure protection mechanisms which improve the reliability of the Smart Grid, and explore the security and privacy issues in the Smart Grid.

/pdf/smart-grid-the-new-and-improved-power-grid-a-survey-4jypbbgv3j.pdf

Smart Grid — The New and Improved Power Grid: A Survey

Smart Grid - The New and Improved Power Grid:

A power grid is a complex system connecting electric power generators to consumers through power transmission and distribution networks across a large geographical area. System monitoring is necessary to ensure the reliable operation of power grids, and state estimation is used in system monitoring to best estimate the power grid state through analysis of meter measurements and power system models. Various techniques have been developed to detect and identify bad measurements, including interacting bad measurements introduced by arbitrary, nonrandom causes. At first glance, it seems that these techniques can also defeat malicious measurements injected by attackers.In this article, we expose an unknown vulnerability of existing bad measurement detection algorithms by presenting and analyzing a new class of attacks, called false data injection attacks, against state estimation in electric power grids. Under the assumption that the attacker can access the current power system configuration information and manipulate the measurements of meters at physically protected locations such as substations, such attacks can introduce arbitrary errors into certain state variables without being detected by existing algorithms. Moreover, we look at two scenarios, where the attacker is either constrained to specific meters or limited in the resources required to compromise meters. We show that the attacker can systematically and efficiently construct attack vectors in both scenarios to change the results of state estimation in arbitrary ways. We also extend these attacks to generalized false data injection attacks, which can further increase the impact by exploiting measurement errors typically tolerated in state estimation. We demonstrate the success of these attacks through simulation using IEEE test systems, and also discuss the practicality of these attacks and the real-world constraints that limit their effectiveness.

False data injection attacks against state estimation in electric power grids

Preface INTRODUCTION Operating States of a Power System Power System Security Analysis State Estimation Summary WEIGHTED LEAST SQUARES STATE ESTIMATION Introduction Component Modeling and Assumptions Building the Network Model Maximum Likelihood Estimation Measurement Model and Assumptions WLS State Estimation Algorithm Decoupled Formulation of the WLS State Estimation DC State Estimation Model Problems References ALTERNATIVE FORMULATIONS OF THE WLS STATE ESTIMATION Weaknesses of the Normal Equations Formulation Orthogonal Factorization Hybrid Method Method of Peters and Wilkinson Equality-Constrained WLS State Estimation Augmented Matrix Approach Blocked Formulation Comparison of Techniques Problems References NETWORK OBSERVABILITY ANALYSIS Networks and Graphs NetworkMatrices LoopEquations Methods of Observability Analysis Numerical Method Based on the Branch Variable Formulation Numerical Method Based on the Nodal Variable Formulation Topological Observability Analysis Method Determination of Critical Measurements Measurement Design Summary Problems References BAD DATA DETECTION AND IDENTIFICATION Properties of Measurement Residuals Classification of Measurements Bad Data Detection and IdentiRability Bad Data Detection Properties of Normalized Residuals Bad Data Identification Largest Normalized Residual Test Hypothesis Testing Identification (HTI) Summary Problems References ROBUST STATE ESTIMATION Introduction Robustness and Breakdown Points Outliers and Leverage Points M-Estimators Least Absolute Value (LAV) Estimation Discussion Problems References NETWORK PARAMETER ESTIMATION Introduction Influence of Parameter Errors on State Estimation Results Identification of Suspicious Parameters Classification of Parameter Estimation Methods Parameter Estimation Based on Residua! Sensitivity Analysis Parameter Estimation Based on State Vector Augmentation Parameter Estimation Based on Historical Series of Data Transformer Tap Estimation Observability of Network Parameters Discussion Problems References TOPOLOGY ERROR PROCESSING Introduction Types of Topology Errors Detection of Topology Errors Classification of Methods for Topology Error Analysis Preliminary Topology Validation Branch Status Errors Substation Configuration Errors Substation Graph and Reduced Model Implicit Substation Model: State and Status Estimation Observability Analysis Revisited Problems References STATE ESTIMATION USING AMPERE MEASUREMENTS Introduction Modeling of Ampere Measurements Difficulties in Using Ampere Measurements Inequality-Constrained State Estimation Heuristic Determination of F-# Solution Uniqueness Algorithmic Determination of Solution Uniqueness Identification of Nonuniquely Observable Branches Measurement Classification and Bad Data Identification Problems References Appendix A Review of Basic Statistics Appendix B Review of Sparse Linear Equation Solution References Index

Power System State Estimation : Theory and Implementation

This paper describes the use of wavelet transforms for analyzing power system fault transients in order to determine the fault location. Traveling wave theory is utilized in capturing the travel time of the transients along the monitored lines between the fault point and the relay. Time resolution for the high frequency components of the fault transients, is provided by the wavelet transform. This information is related to the travel time of the signals which are already decomposed into their modal components. The aerial mode is used for all fault types, whereas the ground mode is used to resolve problems associated with certain special cases. The wavelet transform is found to be an excellent discriminant for identifying the traveling wave reflections from the fault, irrespective of the fault type and impedance. EMTP simulations are used to test and validate the proposed fault location approach for typical power system faults.

Fault location using wavelets

This paper is concerned about the analysis of network observability and phasor measurement unit (PMU) placement when using a mixed measurement set. The measurements will include conventional power flows and injections as well as phasor measurements for voltages and line currents provided by phasor measurement units. The observability analysis is followed by an optimal meter placement strategy for the PMUs.

Observability analysis and measurement placement for systems with PMUs

This paper summarizes the technical activities of the Task Force on Power System Dynamic State and Parameter Estimation. This Task Force was established by the IEEE Working Group on State Estimation Algorithms to investigate the added benefits of dynamic state and parameter estimation for the enhancement of the reliability, security, and resilience of electric power systems. The motivations and engineering values of dynamic state estimation (DSE) are discussed in detail. Then, a set of potential applications that will rely on DSE is presented and discussed. Furthermore, a unified framework is proposed to clarify the important concepts related to DSE, forecasting-aided state estimation, tracking state estimation, and static state estimation. An overview of the current progress in DSE and dynamic parameter estimation is provided. The paper also provides future research needs and directions for the power engineering community.

/pdf/power-system-dynamic-state-estimation-motivations-lul365qej6.pdf

Power System Dynamic State Estimation: Motivations, Definitions, Methodologies, and Future Work

As the phasor measurement units (PMUs) start populating the substations, their benefits for different power system application functions are being debated. One of these functions is the bad data processing that is commonly integrated into the state estimation. Bad data detection is closely related to the measurement redundancy in that bad data appearing in critical measurements cannot be detected. Such measurements, however, can be transformed into redundant measurements by adding few PMUs at strategic locations. In this paper, it will be shown that with few extra PMUs, the bad data detection and identification capability of a given system can be drastically improved. Description of the placement algorithm is given, and case studies carried out on different size test systems are presented

Ali Abur

Papers

Power System State Estimation : Theory and Implementation

Fault location using wavelets

Observability analysis and measurement placement for systems with PMUs

Power System Dynamic State Estimation: Motivations, Definitions, Methodologies, and Future Work

Placement of PMUs to Enable Bad Data Detection in State Estimation