Topology processing in distribution systems by Branch Current based state estimation

Zamani, Vahraz; Baran, Mesut

doi:10.1109/naps.2015.7335171

Cited by 9 publications

(5 citation statements)

References 9 publications

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“…The method enables decoupled Jacobian Matrix on a phase basis and is computationally efficient for radial and weakly meshed networks. After this novel method, successive efforts either dedicate to refine the original methodology or use it for other applications, e.g., topology processing [12] [13].…”

Section: State-of-the-artmentioning

confidence: 99%

Hybrid Measurements-Based Fast State Estimation for Power Distribution System

Chang

et al. 2021

IEEE Access

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The distribution grid is undergoing profound changes nowadays, and state estimator has become an essential part in the control room to enable future smart grid. The newly deployed micro phase measurement units (μPMU) and advanced metering infrastructure (AMI) devices make the real-time state estimation possible for distribution system. Therefore, this paper studies the incorporation and process of the multi-source measurements and proposes a fast three-phase state estimation based on the hybrid measurements scheme. By the process of μPMU measurements, pseudo voltage measurements are added, which significantly increases the estimation redundancy. For AMI measurements, the harmonic components model is used to overcome the asynchronicity problem. An improved sequential state estimation based on the changed measurements is proposed to enable a fast estimation. IEEE 13-node and 390-node systems are simulated to verify the efficacy and efficiency of the proposed method.INDEX TERMS Advanced metering infrastructure (AMI), micro phase measurement units (μPMU), sequential state estimation, hybrid measurements scheme.

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Section: State-of-the-artmentioning

confidence: 99%

Hybrid Measurements-Based Fast State Estimation for Power Distribution System

Chang

et al. 2021

IEEE Access

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“…• Switch-flow Constraints: If a switch δ ij is open, then power flow, S φ ij , through the switch must be equal to zero. Otherwise the flow will be unconstrained as defined in (19).…”

Section: Constraint Formulationmentioning

confidence: 99%

“…The worst-case scenario requires evaluation of all possible spanning trees and hence poses computational challenges for large systems. In [19], the distribution system topology is estimated using the residual of branch current distribution state estimation. The algorithm, however, also requires an exhaustive search of all possible topologies posing computational challenges for large systems.…”

Section: Introductionmentioning

confidence: 99%

Joint Estimation of Operational Topology and Outages for Unbalanced Power Distribution Systems

Gandluru

Poudel

Dubey

2020

IEEE Trans. Power Syst.

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“…Furthermore, a procedure was introduced to tackle the problem of lack of measurement by generating pseudo measurements throughout the distribution grid, resulting in a full‐observable network. In Reference 18 a multi‐microgrid state estimator based on WLS was proposed, considering the concept of the limited number of real‐time measurements in DNs 19 . Presented one algorithm for topology identification by analysis of the residuals of the branch current‐based SE using the limited real‐time measurements.…”

Section: Introductionmentioning

confidence: 99%

Multi‐area state estimation in a distribution network using Takagi‐Sugeno model estimated by Kalman filter

Ghadikolaee

Kazemi

Shayanfar

2020

Int Trans Electr Energ Syst

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Summary This study addressed the problem of multi‐area state estimation in a clustered distribution system. Distribution networks are inherently expansive and comprise a multitude of nodes. This issue increases the state estimation computation time and makes it inapplicable for control of sophisticated distribution networks. Multi‐area state estimation is a technique to reduce computation time while concerning computation accuracy. Many efforts are required to reach a perfect algorithm, followed by the optimization of different parameters of the proposed algorithms. This paper performed a precise mathematical analysis of the impact made by the common (shared) node exchanged information between the areas in the multi‐area state estimation algorithm. Furthermore, a new iterative multi‐area state estimation algorithm equipped with machine learning tools was designed based on analytical detections for enhancing the convergence speed and accuracy of the estimation results. The improvement was evaluated in two clustered networks with 356 and 711 nodes. The results indicated the benefits provided by the proposed modification in terms of convergence speed and accuracy with minimum data exchanges in an iterative multi‐area distribution network.

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Topology processing in distribution systems by Branch Current based state estimation

Cited by 9 publications

References 9 publications

Hybrid Measurements-Based Fast State Estimation for Power Distribution System

Hybrid Measurements-Based Fast State Estimation for Power Distribution System

Joint Estimation of Operational Topology and Outages for Unbalanced Power Distribution Systems

Multi‐area state estimation in a distribution network using Takagi‐Sugeno model estimated by Kalman filter

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