Comparative Evaluation of PMU Algorithms for Power Quality Monitoring in Distribution

Sefid, Marzieh; Khan, Hannan Ahmad; Rihan, Mohd

doi:10.1109/indicon45594.2018.8987142

Cited by 2 publications

(1 citation statement)

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“…The other intelligent tools that are used to monitor PQ disturbances are expert system (ES), Artificial Neural Networks (ANN), and Fuzzy Logic (FL). The different approaches used to detect power quality disturbances are discussed in papers [28][29][30][31][32]. There are monitoring methods that are used in the HRES.…”

Section: Power Quality Monitring Methodsmentioning

confidence: 99%

Novel Approach to Monitoring and Mitigating Power Quality Disturbances in Hybrid Renewable Energy System

Shah¹,

Hellany²,

Nagrial³

et al. 2024

RE&PQJ

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Renewable energy sources are continually increasing their share in the energy system. The introduction of Hybrid Renewable Energy Sources (H.R.E.S.) in the electrical power system has gained momentum. The increased share of Renewable sources has resulted in an increase in Power Quality (P.Q.) disturbances at the user and consumer levels. This research will engineers dedicate the P.Q. disturbances produced in the electrical system due to Hybrid Renewable energy sources, especially solar and wind. The research will predict what type of P.Q. disturbances are introduced during power production. The study will focus on a stand-alone Hybrid Renewable Energy System (H.R.E.S.). The energy system data will be collected and used to produce a Fuzzy Logic (F.L.) algorithm to improve the mitigating techniques to reduce P.Q. disturbances. The suggested algorithm analyzes the stored and continuous data from different sources. The data will be collected and used to drive the hardware to take appropriate actions at the mitigation level. The hardware used in the system consists of a Multiplexer (MUX) and different types of filters. The output of the multiplexer chooses the filters. The algorithm will improve the system's efficiency and help the designers improve the system's design capabilities. The monitoring system will help predict what type of P.Q. disturbances are produced when different energy sources are used to produce power. The proposed system monitors these P.Q. disturbances and classifies them according to their severity.

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Section: Power Quality Monitring Methodsmentioning

confidence: 99%