The static state of an electric power system is defined as the vector of the voltage magnitudes and angles at all network buses The static-state estimator is a data processing algorithm far converting redundant meter readings and other available information into an estimate of the static-state vector Discussions center on the general nature of the problem, mathematical modeling, an interative technique for calculating the state estimate, and concepts underlying the detection and identification of modeling errors Problems of interconnected systems are considered Results of some initial computer simulation tests are discussed

Power System Static-State Estimation, Part I: Exact Model

The state estimation problem in electric power systems consists of four basic operations: hypothesize structure; estimate; detect; identify. This paper addresses the last two problems with respect to the bad data and structural error problem. The paper interrelates various detection and identification methods (sum of squared residuals, weighted and normalized residuals, nonquadratic criteria) and presents new results on bad data analysis (probability of detection, effect of bad data). The theoretical results are illustrated by means of a 25 bus network.

Bad data analysis for power system state estimation

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

A power system is observable if the measurements made on it allow determination of bus voltage magnitude and angle at every bus of the network. This paper outlines the theoretical basis for an algorithm for determining observability. Based on this theory, an algorithm for networks containing both bus injection and line flow measurements is presented.

Power System Observability: A Practical Algorithm Using Network Topology

The problem of real-time estimation of the state of a power system is treated from the point of view of the theory of least-squares estimation (Kalman-Bucy filtering). Since under normal operating conditions, the power system behaves in a quasi- static manner, a simple model for the time behavior of the power system is derived. This model, together with the real-time measurement system, enables the design of a tracking state-estimator algorithm. The proposed algorithm has several advantages over the previously suggested static estimator algorithm in regard to its computational aspects, real-time implementation, and the accuracy of the estimated state.

A Dynamic Estimator for Tracking the State of a Power System

The static state of an electric power system is defined as the vector of the voltage magnitudes and angles at all network buses. The static-state estimator is a data-processing algorithm for converting redundant meter readings and other available information into an estimate of the static-state vector. Discussions center on an approximate mathematical model (related to the dc load-flow model). This model yields noniterative-state estimation equations, simplified prediction of effects of network and generation-load pattern changes on network flow, and simplified detection and identification of modeling errors. Results of some initial computer studies on the real power-voltage angle portion of the approximate model are discussed.

Douglas B. Rom

Papers

Power System Static-State Estimation, Part II: Approximate Model