Modeling and Control of Smart Standalone Microgrids within Cyber Physical System Frameworks

Korukonda, Meher Preetam

doi:10.48550/arxiv.2203.00970

Cited by 1 publication

(1 citation statement)

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“…The second is to use artificial intelligence to improve the classifier's efficiency. After certain training, artificial intelligence can quickly and automatically identify PQD at a high success rate and a fast speed, which is vital to developing intelligent grids [116,117]. Group optimization algorithms such as ABC and PSO are widely used among feature optimization techniques.…”

Section: Feature Optimization and Intelligent Classificationmentioning

confidence: 99%

A Review on Intelligent Detection and Classification of Power Quality Disturbances: Trends, Methodologies, and Prospects

Yan¹,

Chen²,

Geng³

et al. 2023

Computer Modeling in Engineering &Amp; Sciences

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With increasing global concerns about clean energy in smart grids, the detection of power quality disturbances (PQDs) caused by energy instability is becoming more and more prominent. It is well acknowledged that the PQD effects on power grid equipment are destructive and hazardous, which causes irreversible damage to underlying electrical/electronic equipment of the concerned intelligent grids. In order to ensure safe and reliable equipment implementation, appropriate PQD detection technologies must be adopted to avoid such adverse effects. This paper summarizes the newly proposed and traditional PQD detection techniques in order to give a quick start to new researchers in the related field, where specific scenarios and events for which each technique is applicable are also clearly presented. Finally, comments on the future evolution of PQD detection techniques are given. Unlike the published review articles, this paper focuses on the new techniques from the last five years while providing a brief recap on traditional PQD detection techniques so as to supply researchers with a systematic and state-of-the-art review for PQD detection.

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Section: Feature Optimization and Intelligent Classificationmentioning

confidence: 99%