Power Quality Disturbance Detection and Monitoring of Solar Integrated Micro-Grid-Reference-Cited by-同舟云学术

Power Quality Disturbance Detection and Monitoring of Solar Integrated Micro-Grid

Published:2022-10-06 Issue: Volume:17 Page:306-315
ISSN:2224-350X
Container-title:WSEAS TRANSACTIONS ON POWER SYSTEMS
language:en
Short-container-title:

Author:

Pattanaik Debasish¹,Swain Sarat Chandra¹,Samanta Indu Sekhar²,Dash Ritesh³,Swain Kunjabihari⁴

Affiliation:

1. School of Electrical Engineering, KIIT Deemed to be University, Bhubaneswar, INDIA

2. Department of Electrical and Electronics Engineering, Siksha ‘O’ Anusandhan University, INDIA

3. School of Electrical & Electronics Engineering, REVA University, Bangalore, INDIA

4. Department of Electrical and Electronics Engineering, NIST Institue of Science and Technology, Berhampur, INDIA

Abstract

Due to the popularity of microgrids and power quality disturbances (PQD) induced by renewable energies, monitoring in microgrids has risen in popularity in recent years. For monitoring the PQD, many strategies based on artificial intelligence have been proposed. However, when the electrical parameters change, the need to retrain the Artificial neural network (ANN) becomes a significant issue. This paper presents a new approach to the power quality disturbance detection and monitoring of integrated solar microgrids. The power quality event detection is accomplished by analyzing the frequency signal with Wavelet transformation (WT). The classification of power quality disturbance is achieved based on the features. For the classification of PQDs, the retrieved features are fed into a Convolutional neural network (CNN) classifier.

Publisher

World Scientific and Engineering Academy and Society (WSEAS)

Subject

Electrical and Electronic Engineering,Energy (miscellaneous)

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