Abstract
Recently, power quality (PQ) issues have drawn considerable attention of the researchers due to the increasing awareness of the customers towards power quality. The PQ issues maintain its pre-eminence because of the significant growth encountered in the smart grid technology, distributed generation, usage of sensitive and power electronic equipments with the integration of renewable energy resources. The IoT and 5G networks technologies have a number of advantages like smart sensor interfacing, remote sensing and monitoring, data transmission at high speed. Due to this, applications of these two are highly adopted in smart grid. The prime focus of the paper is to present an exhaustive survey of detection and classification of power quality disturbances by discussing signal processing techniques and artificial intelligence tools with their respective pros and cons. Further, critical analysis of automatic recognition techniques for the concerned field is posited with the viewpoint of the types of power input signal (synthetic/real/noisy), pre-processing tools, feature selection methods, artificial intelligence techniques and modes of operation (online/offline) as per the reported articles. The present work also elaborates the future scope of the said field for the reader. This paper provides valuable guidelines to the researchers those having interest in the field of PQ analysis and exploring the better methodologies for further improvement. Comprehensive comparisons have been presented with the help of tabular presentations. Although this critical survey cannot be collectively exhaustive, still this survey comprises the most significant works in the concerned paradigm by examining more than 300 research publications.
Highlights
Nowadays, non-linear loads and sensitive power electronic equipments in the industrial, commercial and domestic applications are extensively used
The performance of power quality (PQ) disturbance detection and classification system is significantly improved by selecting the proper optimization technique
The applications based on Iot and the 5G network support brings a revolution in smart grid domain
Summary
Non-linear loads and sensitive power electronic equipments in the industrial, commercial and domestic applications are extensively used. A lot of work on PQD detection and classification has been done by the researchers and a number of signal processing and AI based techniques are proposed. A detailed and extensive review on detection and classification of PQD is presented by Khokar et al with the application of wavelet in data compression and de-noising. A detailed review of PQ detection and classification methods in grid is presented by Chawda et al [29], with hardware/software structure used for the PQ monitoring in the presence of renewable energy sources. Main focus of this manuscript is to present a up-to-date and detailed review on PQ analysis with PQ standards, signal processing techniques for detection, AI based classification methods and optimization techniques. Power quality issues faced in integration of renewable energy and smart grid presented with researches on real time and experimental studies. PQ disturbances due to renewable integration to grid as well as in smart grid environment with some real time applications are discussed with application of IoT and 5G network
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