Power System State Estimation: Detection of Topological Errors

Lugtu,; Hackett,; Liu, Ming; Might,

doi:10.1109/mper.1981.5511219

Cited by 6 publications

(8 citation statements)

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“…One is the topological method and the other is the numerical method. 8,10 Conversant with network reduction concepts and its methods Upstream modeling of the desired network for the implementation of SE is a main challenge of a PAS engineer. In this aim, the student must be able to model upstream network to have the best estimation and best results.…”

Section: Conversant With Observability Concepts and Its Methodsmentioning

confidence: 99%

“…This technique is known as the weighted least squares (WLS) method. [7][8][9][10][11] Supervisory control and data acquisition SCADA aids PAS engineers in controlling the vast amounts of information entering and leaving power plants and electrical substations in order to help facilitate the delivery of electricity. The system tracks values of devices, such as transformers, overhead lines, shunt devices, breakers, and generators, and processes these values as points.…”

Section: State Estimationmentioning

confidence: 99%

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Teaching senior undergraduate students for state estimation module implementation on power applicationsoftware

Beiza

2018

International Journal of Electrical Engineering & Education

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This paper describes an effective method of teaching power application software programming to undergraduate students of power system groups in an electrical engineering department. The paper demonstrates how to implement power application software modules on a power network. The first scope of this method is to develop a power application software state estimation module and grow student practical operational vision of power application software. Some experiments are implemented on a power grid. This grid has 320 buses and that is the biggest sub-transmission area of Iran power grid. Evaluation of this test over several semesters with more than 30 students is very positive. The results show that students’ motivation and confidence in understanding this test has been developed remarkably.

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Section: Conversant With Observability Concepts and Its Methodsmentioning

confidence: 99%

Section: State Estimationmentioning

confidence: 99%

Teaching senior undergraduate students for state estimation module implementation on power applicationsoftware

Beiza

2018

International Journal of Electrical Engineering & Education

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“…State estimation and topology detection have co-evolved since at least the late 1970s [3]; see [4] for an overview of the state of the art as of 2000. These industry-standard methods use low time-resolution SCADA data about power flows and digital status, together with a reference model, to infer system voltages and currents as well as the current topology.…”

Section: B Prior Workmentioning

confidence: 99%

FLiER: Practical Topology Update Detection Using Sparse PMUs

Ponce

Bindel

2017

IEEE Trans. Power Syst.

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Abstract-In this paper, we present a Fingerprint Linear Estimation Routine (FLiER) to identify topology changes in power networks using readings from sparsely-deployed phasor measurement units (PMUs). When a power line, load, or generator trips in a network, or when a substation is reconfigured, the event leaves a unique "voltage fingerprint" of bus voltage changes that we can identify using only the portion of the network directly observed by the PMUs. The naive brute-force approach to identify a failed line from such voltage fingerprints, though simple and accurate, is slow. We derive an approximate algorithm based on a local linearization and a novel filtering approach that is faster and only slightly less accurate. We present experimental results using the IEEE 57-bus, IEEE 118-bus, and Polish 1999-2000 winter peak networks.

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“…Liao In transmission grids, the grid topology is usually available to system operators. The topology error caused by the infrequent reconfiguration can be identified by the topology processor and state estimation [3]- [5]. Unfortunately, in medium voltage (MV) and low voltage (LV) distribution grids, a topology can frequently change and make existing methods with limited performance.…”

Section: Introductionmentioning

confidence: 99%

Urban MV and LV Distribution Grid Topology Estimation via Group Lasso

Liao

Weng

Liu

et al. 2019

IEEE Trans. Power Syst.

117

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The increasing penetration of distributed energy resources poses numerous reliability issues to the urban distribution grid. The topology estimation is a critical step to ensure the robustness of distribution grid operation. However, the bus connectivity and grid topology estimation are usually hard in distribution grids. For example, it is technically challenging and costly to monitor the bus connectivity in urban grids, e.g., underground lines. It is also inappropriate to use the radial topology assumption exclusively because the grids of metropolitan cities and regions with dense loads could be with many mesh structures. To resolve these drawbacks, we propose a datadriven topology estimation method for MV and LV distribution grids by only utilizing the historical smart meter measurements. Particularly, a probabilistic graphical model is utilized to capture the statistical dependencies amongst bus voltages. We prove that the bus connectivity and grid topology estimation problems, in radial and mesh structures, can be formulated as a linear regression with a least absolute shrinkage regularization on grouped variables (group lasso). Simulations show highly accurate results in eight MV and LV distribution networks at different sizes and 22 topology configurations using PG&E residential smart meter data.

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Power System State Estimation: Detection of Topological Errors

Cited by 6 publications

References 0 publications

Teaching senior undergraduate students for state estimation module implementation on power applicationsoftware

Teaching senior undergraduate students for state estimation module implementation on power applicationsoftware

FLiER: Practical Topology Update Detection Using Sparse PMUs

Urban MV and LV Distribution Grid Topology Estimation via Group Lasso

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