IEEE Access (Jan 2021)

An Improved Dynamic Thermal Current Rating Model for PMU-Based Wide Area Measurement Framework for Reliability Analysis Utilizing Sensor Cloud System

  • Mohammad Kamrul Hasan,
  • Musse Mohamud Ahmed,
  • Sherfriz Sherry Musa,
  • Shayla Islam,
  • Siti Norul Huda Sheikh Abdullah,
  • Eklas Hossain,
  • Nazmus Shaker Nafi,
  • Nguyen Vo

DOI
https://doi.org/10.1109/ACCESS.2021.3052368
Journal volume & issue
Vol. 9
pp. 14446 – 14458

Abstract

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Information technology expressively improves remote electricity measurement and monitoring. Integrating Dynamic Thermal Current Rating (DTCR) software packs with the exclusive phasor measurement-based Wide Area Measurement (WAM) framework, the remote Transmission Lines (TLs) current rating can be measured. WAM is used for data acquisition from different sensors, and also allows data transmissions and processing for which sensor cloud system (SCS) plays a vital role. DTCR with phasor-measurement based WAM framework is mainly used to analyze and determine the current ratings of overhead TLs using weather condition estimation or prediction methods. However, the recent study suggests that the accuracy of the DTCR has become an issue in the smart grid of Sarawak Energy Berhad (SEB). Hence, this article studies and discusses the relevant models and systems, and then proposes an improved thermal pi (π) model for the transmission line thermal model of DTCR software in WAM Framework. The performance of the improved π model will be distinguished from the existing thermal model. The weather factors that bring a substantial impact on the current rating is also considered, where the relevant data is monitored via different weather sensors. Besides, this study also focuses on calibrating the DTCR through phasor measurement in the WAM system, as well as the field measured data. All the data is collected from relevant sensors, and a detailed comparative analysis is provided based on the proposed model for the sake of improving the reliability of the system. The performance analysis of the thermal models is evaluated using Matlab software-based numerical analysis.

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