Optimal PMU placement in a distribution network considering network reconfiguration

Abdelsalam, Hany A.; Abdelaziz, Almoataz Y.; Mukherjee, V.

doi:10.1109/iccpct.2014.7054997

Cited by 15 publications

(12 citation statements)

References 20 publications

(24 reference statements)

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“…Ref. [41] uses the system reconfiguration approach for OPP in the distribution network to achieve system reconfiguration, and the ant colony algorithm has been applied as an optimization tool to minimize energy losses. In the next phase, a greedy algorithm is utilized to find the PMU placement location by minimizing the number of PMUs with consideration to the maximum observability of the system [41].…”

Section: Greedy Algorithmmentioning

confidence: 99%

Optimal PMU placement in a smart grid: An updated review

Sefid¹,

Rihan²

2018

IJSGCE

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In recent years, the monitoring and control of the power grid has become an essential objective to prevent system failure. The provision of measurements generated from phasor measurement units (PMUs) can play a significant role in achieving this goal. PMUs can offer synchronized measurements and dynamically measure voltages and current phasors. The estimation of the states of each bus via the installation of PMUs at each node of the bus is not necessary and is hindered by the high cost and complexity of the installation and communication methods. Therefore, a method that reduces the total number of PMUs without affecting the maximum observability and reliability of the power grid is needed. Achieving the minimum number of installed PMUs with maximum observability is the main target of optimal PMU placement. Several techniques are available for resolving this issue, and these techniques lie in two main categories: mathematical techniques and metaheuristic approaches. In the last few years, a huge number of publications have reported different techniques that are based on the principle used and the intended application. Some comprehensive reviews have also been reported a few years ago. This area is an intensively pursued field of study, and many new techniques and important results have been reported after the publication of these reviews. Therefore, there is a need for a comprehensive review of recent research on optimal PMU placement. The present work attempts to provide a critical review of recent literature on optimal PMU placement. We expect this review to be beneficial to researchers and industries that are studying the optimal placement of PMUs in their networks.

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Section: Greedy Algorithmmentioning

confidence: 99%

Optimal PMU placement in a smart grid: An updated review

Sefid¹,

Rihan²

2018

IJSGCE

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“…Evaporation of the pheromone trace and action of the daemon are procedures in ant colony optimisation. The use of ant colony optimisation to determine good paths across graphs will decrease computational issues [25].…”

Section: Ant Colony Optimizationmentioning

confidence: 99%

Review of Different Methods for Optimal Placement of Phasor Measurement Unit on the Power System Network

Abdulkareem¹,

Ogbe²,

Somefun³

2020

Adv. sci. technol. eng. syst. j.

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“…Phasor measurement units have not been widely applied at the distribution level due to great challenges in both technical and economic aspects [44]. To overcome these problems, several laboratories such as Power Standards Lab and Lawrence Berkeley National Lab have devoted to developing a novel powerful micro-phasor measurement unit (µPMU) and studied its practical and potential distribution system applications [45,46].…”

Section: Introductionmentioning

confidence: 99%

Optimal Micro-PMU Placement Using Mutual Information Theory in Distribution Networks

et al. 2018

Energies

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Micro-phasor measurement unit (μPMU) is under fast development and becoming more and more important for application in future distribution networks. It is unrealistic and unaffordable to place all buses with μPMUs because of the high costs, leading to the necessity of determining optimal placement with minimal numbers of μPMUs in the distribution system. An optimal μPMU placement (OPP) based on the information entropy evaluation and node selection strategy (IENS) using greedy algorithm is presented in this paper. The uncertainties of distributed generations (DGs) and pseudo measurements are taken into consideration, and the two-point estimation method (2PEM) is utilized for solving stochastic state estimation problems. The set of buses selected by improved IENS, which can minimize the uncertainties of network and obtain system observability is considered as the optimal deployment of μPMUs. The proposed method utilizes the measurements of smart meters and pseudo measurements of load powers in the distribution systems to reduce the number of μPMUs and enhance the observability of the network. The results of the simulations prove the effectiveness of the proposed algorithm with the comparison of traditional topological methods for the OPP problem. The improved IENS method can obtain the optimal complete and incomplete μPMU placement in the distribution systems.

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Optimal PMU placement in a distribution network considering network reconfiguration

Cited by 15 publications

References 20 publications

Optimal PMU placement in a smart grid: An updated review

Optimal PMU placement in a smart grid: An updated review

Review of Different Methods for Optimal Placement of Phasor Measurement Unit on the Power System Network

Optimal Micro-PMU Placement Using Mutual Information Theory in Distribution Networks

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