The transformation of traditional grid networks towards smart-grid and microgrid concepts raises many critical issues, and quality in the power supply is one of the prominent ones that needs further research. Developing and applying power quality (PQ) recognition methods with efficient and reliable analysis are essential to the fast-growing issues related to modern smart power distribution systems. In this regard, a hybrid algorithm is proposed for PQ events detection and classification using Elasticnet Regression-based Variational Mode Decomposition (ER-VMD) and Salp Swarm Algorithm optimized Probabilistic Neural Network (SSA-PNN). The Elasticnet Regression (ER) process is suggested to modify the conventional VMD approach instead of the Tikhonov Regularization (TR) method to enhance performance and obtain better band-limited intrinsic mode functions. This idea results in robust and effective reconstruction features and helps to obtain accurate classification using the classifier. In the classification stage, a Salp Swarm Algorithm (SSA) based PNN is used for the PQ event, considering the relevant features obtained from ER-VMD. The system parameters often influence PNN performance, and SSA is used to determine the ideal values to improve the PNN's capacity for more accurate classification. The numerical values of the accuracy percentage, percentage of sensitivity, and percentage of specificity in the case of real-time data are found as 98.58, 100, and 98.46, respectively. The acquired comparison findings demonstrate the effectiveness and robustness of the proposed technique in terms of rapid learning speed, smaller computational complexity, robust performance for anti-noise conditions, and accurate identification and categorization.

College of Engineering University of Business and Technology Jeddah 21448 Saudi Arabia

Department of Computer Science and Engineering Siksha' O' Anusandhan University India

Department of Electrical and Electronics Engineering NIST University India

Department of Electrical and Electronics Engineering Siksha' O' Anusandhan University India

Department of Electrical Engineering Graphic Era Dehradun 248002 India

Department of Electrical Engineering Srinix College of Engineering Ranipatna Balasore Odisha India

ENET Centre VSB Technical University of Ostrava 708 00 Ostrava Czech Republic

Hourani Center for Applied Scientific Research Al Ahliyya Amman University Amman Jordan

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