A line-current measurement based state estimator

Muñoz, José Manuel Rodríguez; Gómez-Expósito, Antonio

doi:10.1109/59.141753

Cited by 37 publications

(11 citation statements)

References 13 publications

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“…Some of them use the magnitude I directly as measurements in WLS estimation [12], and some others use 2 I instead [13].…”

Section: A Estimation Of Non-gaussian Distributed Analog 1) Approximmentioning

confidence: 99%

“…In fact, on the one hand, there are lots of current magnitude measurements in sub-transmission or distribution networks, and the errors of nonnegative current magnitude measurements normally do not obey Gaussian distributions, hence the first precondition above is not satisfied. There are several WLS estimation methods developed to consider current magnitude measurements so far [12]- [17], but the basic question is not answered that whether and how the precision of WLS SE can be accepted when the errors of current magnitude measurements do not obey Gaussian distributions.…”

Section: Introductionmentioning

confidence: 99%

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Minimum information loss based state estimation for power systems

Sun

Gao²,

Zhang³

2006

2006 IEEE Power Engineering Society General Meeting

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The mathematical base of state estimation (SE) method for power systems is studied based on information theory. A more general SE method based on the minimum information loss (MIL) principle is proposed. The new method is suitable for different probability distributions of measurement errors, it can utilize different types of information including that of analog and digital measurements, and a unified estimation of power flow and network topology can be performed by it. It is proved that weighted least square (WLS) and weighted least absolute value (WLAV) estimation methods are both special cases of the MIL estimation. Based on the MIL method, it is concluded that large magnitude currents are the approximate condition of WLS estimations for current magnitude measurements commonly used in SE's for sub-transmission and distribution networks. A statistical study of a small test case and a numerical experiment in a real power network are carried out.Index Terms-Power systems, information theory, SE, current measurement, topology error.

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“…Some of them use the magnitude I directly as measurements in WLS estimation [12], and some others use 2 I instead [13].…”

Section: A Estimation Of Non-gaussian Distributed Analog 1) Approximmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Minimum information loss based state estimation for power systems

Sun

Gao²,

Zhang³

2006

2006 IEEE Power Engineering Society General Meeting

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“…First, the system power flow equations are reformulated as the second order cone constraints by introducing new variables to represent the relationship of system voltage magnitude and angle in the nodal active and reactive power flow equations [14,15]. The thermal limits of transmission lines are recast as current limits which can be expressed as linear constraints using the new variables in conic constraints [16,17]. In addition, the polyhedral approximation is implemented to transform the conic constraints to a set of linear constraints [18].…”

Section: Introductionmentioning

confidence: 99%

System load margin evaluation using mixed-integer conic optimization

Fang

et al. 2015

2015 North American Power Symposium (NAPS)

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This paper proposes a mixed-integer conic optimization approach for estimating system load margin to evaluate static voltage stability in transmission networks. The proposed problem formulation employs the conic quadratic format of power flow equations, and then utilizes a polyhedral approximation to transform the conic quadratic constraints to linear constraints. Also, the complementary constraint of generators' reactive power limit has been considered. The numerical case studies have been performed on IEEE 14, 30, 39 and 118 bus systems, and validated that the proposed method is an effective tool for system load margin evaluation. Keywords-Static voltage stability, load margin, conic optimization, mixed integer linear programming.

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“…SE is a very useful tool for the economic and secure operation of transmission networks. From early days of Scheweppe [1], developments of SE are done as a notion of robust estimation [2], hierarchical estimation [3], with and without the inclusion of current measurements [4], etc. Distributed SE for very large power system has been taken for study since the very beginning [1] and improvements have been done [5].…”

Section: Introductionmentioning

confidence: 99%

Two stage state estimator with phasor measurements

Jamuna

2009

2009 International Conference on Power Systems

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State estimator is an important tool for online monitoring, analysis and control of power systems. With the increased use of phasor measurement units in a power grid, utilization of synchro phasor measurements in State Estimation (SE) becomes essential. Conventional State Estimation (CSE) has been done from measurements obtained by Supervisory Control And Data Acquisition (SCADA) systems. Linear State Estimation (LSE) is done using phasor measurements alone. The paper presents a hybrid method called Two Stage State Estimation (TSSE), wherein the states of the system are estimated by incorporating both the SCADA measurements and phasor measurements. Simulations are done on IEEE 14 bus, IEEE 30 bus and IEEE 118 bus systems and results are compared.

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A line-current measurement based state estimator

Cited by 37 publications

References 13 publications

Minimum information loss based state estimation for power systems

Minimum information loss based state estimation for power systems

System load margin evaluation using mixed-integer conic optimization

Two stage state estimator with phasor measurements

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