PMU Installation to Increase The Accuracy of State Estimation

Wakti, Muhamad Hazrirrahman; Hadi, Sasongko Pramono; Putranto, Lesnanto Multa

doi:10.1109/iciteed.2019.8929976

Cited by 1 publication

(1 citation statement)

References 14 publications

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“…One of the original drivers behind the efforts that eventually lead to the development of the PMU was the need to enhance static state estimators. This is showcased in [7], where PMUs are used to validate static estimators. Eventually, as PMUs continue to be installed across the grid, dynamic state estimation (DSE) will likely become the standard for grid monitoring.…”

Section: Power System Monitoringmentioning

confidence: 99%

Research Trends and Applications of PMUs

2022

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This work is a survey of current trends in applications of PMUs. PMUs have the potential to solve major problems in the areas of power system estimation, protection, and stability. A variety of methods are being used for these purposes, including statistical techniques, mathematical transformations, probability, and AI. The results produced by the techniques reviewed in this work are promising, but there is work to be performed in the context of implementation and standardization. As the smart grid initiative continues to advance, the number of intelligent devices monitoring the power grid continues to increase. PMUs are at the center of this initiative, and as a result, each year more PMUs are deployed across the grid. Since their introduction, myriad solutions based on PMU-technology have been suggested. The high sampling rates and synchronized measurements provided by PMUs are expected to drive significant advancements across multiple fields, such as the protection, estimation, and control of the power grid. This work offers a review of contemporary research trends and applications of PMU technology. Most solutions presented in this work were published in the last five years, and techniques showing potential for significant impact are highlighted in greater detail. Being a relatively new technology, there are several issues that must be addressed before PMU-based solutions can be successfully implemented. This survey found that key areas where improvements are needed include the establishment of PMU-observability, data processing algorithms, the handling of heterogeneous sampling rates, and the minimization of the investment in infrastructure for PMU communication. Solutions based on Bayesian estimation, as well as those having a distributed architectures, show great promise. The material presented in this document is tailored to both new researchers entering this field and experienced researchers wishing to become acquainted with emerging trends.

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Section: Power System Monitoringmentioning

confidence: 99%