Power Systems State Estimation Accuracy Enhancement Through the Use of PMU Measurements

Rice, Carla; Heydt,

doi:10.1109/tdc.2006.1668476

Cited by 29 publications

(16 citation statements)

References 24 publications

(14 reference statements)

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“…Apparently, observability alone does not necessarily lead to an acceptable state estimate or an informative PMU configuration. In fact, PMU configurations, which use the same number of PMUs to make the grid completely observable, can result in quite different state estimation accuracies [18]. On the other hand, ignoring the state observability requirements in PMU placement optimization as in [15] and [16] can potentially force to accept the estimate for an unobserved state component as its unconditional mean, which is its trivial estimate.…”

Section: B Research Gap and Contributionmentioning

confidence: 99%

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PMU Placement Optimization for Efficient State Estimation in Smart Grid

Shi

Tuan

Poor

et al. 2020

IEEE J. Select. Areas Commun.

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This paper investigates phasor measurement unit (PMU) placement for informative state estimation in smart grid by incorporating various constraints for observability. Observability constitutes an important information-theoretic characteristic for PMU placement to reply the depth of the buses' reachability by the placed PMUs, but addresing it solely by binary linear programming in many works still does not guarantee a good estimate for the grid state. Some existing works considered optimization problems of some estimation indexes by ignoring the observability requirements for computational ease and thus potentially lead to trivial results such as acceptance of the estimate for an unobserved state component as its unconditional mean. In this work, the PMU placement optimization problem is considered by minimizing the mean squared error or maximizing the mutual information between the measurement output and grid state subject to observability constraints, which incorporate operating conditions such as presence of zero injection buses, contigency of measurement loss, and limitation of communication channels per PMU. The proposed design is thus free from the fundamental shortcomings in the existing PMU placement designs. The problems are posed as large scale binary nonlinear optimization problems involving thousands binary variables, for which this paper develops efficient algorithms for computational solutions. Their performance is analyzed in detail through numerical examples on large scale IEEE power networks. The solution method is also shown to be extended to AC power flow models, which are formulated by nonlinear equations.

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Section: B Research Gap and Contributionmentioning

confidence: 99%

“…For m ∈ Z, the constraints (18) mean that all its incident buses are observable except one, which is then observable by applying the Kirchhoff's current law (KCL) at m. For m / ∈ Z, the constraints (18) mean that all its incident buses are observable so m is observable by applying KCL at m.…”

Section: ) Zero Injection Buses (Zibs)mentioning

confidence: 99%

PMU Placement Optimization for Efficient State Estimation in Smart Grid

Shi

Tuan

Poor

et al. 2020

IEEE J. Select. Areas Commun.

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“…In this paper, we advocate an information-theoretic criterion to assess the 'information gain' that can be obtained from the PMU measurements. Specifically, we model the uncertainties in the system states as the Shannon entropy [15]: (6) where is the probability mass function (pmf) of . In this paper, we assume that the entropies of all variables are calculated after quantization with a sufficiently small step size .…”

Section: Optimal Pmu Placement: Theoretical Formulationmentioning

confidence: 99%

“…Currently, there is a significant performance gap between the existing research and the desired 'informative' PMU configuration [6], [7]. One particular reason is that most researches center around the topological observability criterion, which essentially specifies that power system states should be uniquely estimated using minimum number of PMU measurements [8].…”

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confidence: 99%

An Information-Theoretic Approach to PMU Placement in Electric Power Systems

Cui

Weng

et al. 2013

IEEE Trans. Smart Grid

124

102

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Abstract-This paper presents an information-theoretic approach to address the phasor measurement unit (PMU) placement problem in electric power systems. Different from the conventional 'topological observability' based approaches, this paper advocates a much more refined, information-theoretic criterion, namely the mutual information (MI) between PMU measurements and power system states. The proposed MI criterion not only includes observability as a special case, but also rigorously models the uncertainty reduction on power system states from PMU measurements. Thus, it can generate highly informative PMU configurations. The MI criterion can also facilitate robust PMU placement by explicitly modeling probabilistic PMU outages. We propose a greedy PMU placement algorithm, and show that it achieves an approximation ratio of for any PMU placement budget. We further show that the performance is the best that one can achieve, in the sense that it is NP-hard to achieve any approximation ratio beyond . Such performance guarantee makes the greedy algorithm very attractive in the practical scenario of multi-stage installations for utilities with limited budgets. Finally, simulation results demonstrate near-optimal performance of the proposed PMU placement algorithm.Index Terms-Electric power systems, greedy algorithm, mutual information, phasor measurement unit, submodular functions.

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“…One way to measure the state estimation accuracy is to use the metric based on the calculated normalized state errors given by [15]:…”

Section: State Estimator Tuning For Pmu Measurementsmentioning

confidence: 99%

State estimator tuning for PMU measurements

Zhang

Abur

2011

2011 North American Power Symposium

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Tuning of measurement weights in state estimation refers to the choice of elements for the measurement error covariance matrix. While these values are typically set by the users of state estimators based on some preliminary knowledge on the accuracies of conventional measurements, there are no commonly accepted methods for specifying these weights for new types of measurements. One class of such new measurements is the synchronized phasors. This paper provides a simple method to tune weights for phasor measurements and illustrates the suggested method by using IEEE 14bus system as an example. Keywords-Phasor measurement units (PMUs), measurement error covariance matrix, estimator tuning. . His research interests are in computational methods for the solution of power system monitoring, operation and control problems.

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Power Systems State Estimation Accuracy Enhancement Through the Use of PMU Measurements

Cited by 29 publications

References 24 publications

PMU Placement Optimization for Efficient State Estimation in Smart Grid

PMU Placement Optimization for Efficient State Estimation in Smart Grid

An Information-Theoretic Approach to PMU Placement in Electric Power Systems

State estimator tuning for PMU measurements

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