Application of Root Mean Square and Adaptive NeuroFuzzyInference Systemfor Power Quality Events Classification Using Electricaland Electronics Home Appliances as Case Study
Journal Title: IOSR Journals (IOSR Journal of Electrical and Electronics Engineering) - Year 2018, Vol 13, Issue 3
Abstract
The proliferation of sensitive equipment and non-linear loads atbothindustrial and domestic environment is extremely higher nowadays. This invariably contributes immensely topower quality issues on electric power system network and this indeed is a subject of concern among power system researchers since the world is aiming at ensuring clean, stable and quality electric power supply. This paper presents application of root mean square and adaptive neuro-fuzzy inference system for power quality events classification using electrical and electronics home appliances as case study.Three power quality events (voltage dip, voltage swell and voltage interruption) were considered in this paper. PQ events classification results obtained by the proposed approach were compared with the classification with FLUKE 435. Based on the analysis, obtained classification rateforelectric blender, laptop, television and electric fan was found to be 100% while that obtained forrefrigerator, vacuum cleaner and washing machine was found to be 80%. The estimatedoverall performanceaccuracy of RMS-ANFIS was found to be 91.42%. The proposed approach showed greater suitability for detection and classification of PQ events.
Authors and Affiliations
Okelola M. O. , Olabode O. E
Keywords
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- EP ID EP388752
- DOI 10.9790/1676-1303021523.
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