Enhancing State Estimation Accuracy in Distribution Networks: An Optimized Algorithm for Strategic Meter Placement

Articles in Press

Document Type : Research paper

Authors

1 Department of Electrical and Computer Engineering, Qom University of Technology, Qom, Iran.

2 Power Systems Operation and Planning Research Department, Niroo Research Institute (NRI), Shahrak Ghods, Tehran, Iran.

Abstract

Accurate state estimation is crucial for the effective control and management of power grids, as it provides a comprehensive understanding of voltage magnitude and phase angle at network buses. Incorrect estimations may lead to damaging decisions and network collapse. This paper addresses the significance of precise state estimation in distribution networks and proposes an efficient algorithm for optimal measurement device allocation, aiming to minimize estimation errors. The algorithm considers both investment and technical constraints, utilizing an optimal alternative current (AC) power flow model that eliminates the need for exact values of active and reactive load demands. The proposed method identifies optimal locations for installing a specific number of phasor measurement units (PMUs) across the network. The application of the algorithm to 33-bus and 69-bus test systems demonstrates its effectiveness in enhancing state estimation accuracy. Results reveal that optimizing the number and location of measurement devices significantly improves outcomes. A comparative analysis with the conventional weighted least squares (WLS) algorithm underscores the applicability of the proposed model, particularly in distribution networks with limited measurement devices. The proposed method formulates optimal meter placement problems in distribution networks based on an optimal power flow model, which has a superior performance in both accuracy and convergence without needing to exact nodal demands for state estimation. This research contributes to the advancement of state estimation procedures, offering a practical approach to enhance accuracy and reliability in power grid management.

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Main Subjects

References

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Journal of Operation and Automation in Power Engineering

Articles in Press, Corrected Proof
Available Online from 28 July 2025

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History

  • Receive Date: 18 June 2024
  • Revise Date: 21 January 2025
  • Accept Date: 02 February 2025
  • First Publish Date: 28 July 2025

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