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Journal ArticleDOI

A Method That Combines Internal State Estimation and External Network Modeling

A. Monticelli, +1 more
- 01 Jan 1985 - 
- Vol. 104, Iss: 1, pp 91-103
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TLDR
The dormant-measurement technique, developed, achieves simultaneously the internal state estimation and the external network modeling without adversely affecting theinternal state estimation.
Abstract
A method that combines internal state estimation and external network modeling is developed. The external system is represented by an unreduced load flow model. One state estimation covering both the internal system and the external system is used. The external system operating data on power injections and bus voltages are entered as pseudo-measurements. At each iteration the set of active pseudo- measurements are selected to conform with the specified variables in a load flow program. Because such a set of non-redundant measurements is used, the internal state estimation is not affected by the external system pseudo-measurements. External generation MVAR and controlled bus voltage limits are enforced. A technique is developed to make a pseudo-measurement dormant. Using the dormant-measurement technique, it is possible to maintain the same external system state estimation formulation while the PV-PQ switching takes place from iteration to iteration. The method can easily be implemented by modifying an existing state estimation program. It has been implemented in a fast model-decoupled estimation program. Because of the dormant measurement technique, the constant gain matrix evaluated at flat voltage is used in every iteration. The method has been tested on the IEEE 14- bus, 30-bus, and Brazilian 66-bus systems. Excellent results are obtained. The number of iterations for the method to converge is usually the same as the regular state estimation runs. Thus the method presented here achieves simultaneously the internal state estimation and the external network modeling without adversely affecting the internal state estimation.

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Citations
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Journal ArticleDOI

A Multilevel State Estimation Paradigm for Smart Grids

TL;DR: A multilevel framework that facilitates seamless integration of existing state estimators that are designed to function at different levels of modeling hierarchy in order to accomplish very large-scale monitoring of interconnected power systems is described.
Journal ArticleDOI

Network Observability: Identification of Observable Islands and Measurement Placement

TL;DR: Two algorithms are presented; one for testing the observability of a network and identifying the observable islands when the network is unobservable, and the other for selecting a minimal set of additional measurements to make the network observable.

A Multilevel State Estimation Paradigm for Smart Grids The authors of this paper describe a multilevel state estimator architecture that can sustain growth in size, complexity of data, and information.

TL;DR: In this paper, the authors describe a multilevel framework that facilitates seamless integration of existing state estimators (SEs) that are designed to function at different levels of modeling hierarchy in order to accomplish very large-scale monitoring of interconnected power systems.
Journal ArticleDOI

Real-time modeling of power networks

TL;DR: The various steps in constructing the model from the real-time measurements are described, including the determination of the network topology, the estimation of thenetwork state, and the approximate modeling of the unobservable (external) network.
Journal ArticleDOI

Multiple Bad Data Identification for State Estimation by Combinatorial Optimization

TL;DR: An efficient branch-and-bound algorithm fully exploiting the knowledge of the problem is developed and it is shown that the method is reliable, efficient, and does not require separate testing of network observability.
References
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Journal ArticleDOI

Fast Decoupled Load Flow

TL;DR: This paper describes a simple, very reliable and extremely fast load-flow solution method that is attractive for accurate or approximate off-and on-line routine and contingency calculations for networks of any size, and can be implemented efficiently on computers with restrictive core-store capacities.
Journal ArticleDOI

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

TL;DR: 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.
Journal ArticleDOI

Bad data analysis for power system state estimation

TL;DR: In this article, the state estimation problem in electric power systems consists of four basic operations: hypothesize structure; estimate; detect; identify, which is addressed with respect to the bad data and structural error problem.
Journal ArticleDOI

Power System Observability: A Practical Algorithm Using Network Topology

TL;DR: In this paper, 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, and the theoretical basis for an algorithm for determining observability is presented.
Journal ArticleDOI

Network Observability: Theory

TL;DR: In this article, a complete theory of network observability is presented, starting from a fundamental notion of the observability of a network, a number of basic facts relating to network observations, including unobservable states, observable branches, observable islands, relevancy of measurements, etc.
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