Size Estimation of Bulk Capacitor Removal Using Limited Power Quality Monitors in the Distribution Network

Mingang Tan (), Chaohai Zhang and Bin Chen
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Mingang Tan: Department of Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
Chaohai Zhang: Department of Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
Bin Chen: Department of Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China

Sustainability, 2022, vol. 14, issue 22, 1-14

Abstract: With a large number of distributed generators (DG) and sensitive power loads connected to the distribution network, power quality issues have increasingly become the focus of users’ attention. Accurate and quick estimation of the amount of bulk capacitor removal that causes voltage sag is helpful to maintain power quality management equipment in time. This paper presents a novel size estimation of bulk capacitor removal using a limited power quality monitor (PQM) in the distribution network, including PQM deployment optimization, feeder localization, and capacitor removal amount calculation. The PQM placement is optimized by taking the estimated capacitance removal sizes of all buses as a constraint. The change of reactive power consumption before and after removing the capacitor at each power line is adopted to determine the feeder where the disturbance is located. Based on the impedance characteristics of the power grid components, the steady estimation method (SEM) is deduced using the fundamental voltage and current. Applying the sampling points of instantaneous voltage and current waveform, the transient estimation method (TEM) is constructed by data fitting. Case studies and index analysis for the IEEE 13 bus test work are presented to verify the reasonableness and accuracy of the proposed method for disturbed bus, capacitor size, load symmetry, disturbance duration, and DGs. SEM shows more stability and accuracy, while TEM performs faster and is more robust. The new methods provide a reliable and acceptable disturbance size estimation with several limited PQMs.

Keywords: power quality monitoring; optimal configuration; voltage sag location; decision tree; covering problem; weighted metrics (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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