Combination of neural network and wavelet transform for islanding detection of distributed generation in a small-scale network. Issue 3 (3rd April 2019)

• Record Type: Journal Article
• Authors: Shahryari, Elnaz; Nooshyar, Mehdi; Sobhani, Behrooz
• Is Part Of: International journal of ambient energy. Volume 40:Issue 3(2019)
• Page Start: 263
• Page End: 273
• Publication Date: 2019-04-03
• Subjects: Islanding detection -- distributed generation -- wavelet analysis -- neural network -- non detection zone reduction -- mean square error; Power resources -- Periodicals; Renewable energy sources -- Periodicals; 621.04205
• DOI: 10.1080/01430750.2017.1392348
• Languages: English
• ISSNs: 0143-0750

Abstract

ABSTRACT: In this paper, an optimum and intelligent method is proposed for islanding detection using wavelet transform. The suggested relay is based on neural network (NN) in which different heuristic algorithms are used for training the NN. In the proposed method, the appropriate signals for detection procedure as well as mother wavelet are selected optimally, based on the mean square error (MSE) concept. Lately, the desired relay is trained by the optimally selected signals using four different algorithms and the optimum condition of the fault detector is identified. Simulation results approved that non detection zone (NDZ) has a significant reduction utilising the proposed intelligent technique. The contributions of the proposed method include presenting an appropriate signal selection method based on MSE, selecting optimum number of relay input signals using the proposed technique, fast training of intelligent relay by using least information, solving threshold selection problem and reduction of NDZ approximately to zero.