Artificial neural network and phasor data‐based islanding detection in smart grid

Auto‐correlation‐based Islanding detection technique verified through hardware‐in‐loop testing

“…Therefore, the overall Islanding detection time from the inception of the Islanding event would be around 60 ms which is equivalent to three cycles. Table 7 shows the comparative assessment of the proposed scheme in terms of the percentage value of NDZ and detection time with the techniques based on ROCOF [11], oscillatory frequency [12], overvoltage/undervoltage (OV/UV), over frequency/under frequency (OF/UF) [13], inverse hyperbolic secant function (applied for acquired voltage signals) [16], time-frequency (TF) transform [17], wavelet transform (WT) [18][19][20], Hilbert-Hung transform (HT) [21], SVM [22,23], RVM [25], artificial neural network (ANN) [26,27], adaptive ensemble classifier (AEC) [28], Data mining [29,30], random forest (RF) [32], and principle component analysis (PCA) [24].…”

“…Furthermore, the hardware implementation of said techniques is also complex [17][18][19][20][21]. Subsequently, support vector machine (SVM), relevance vector machine (RVM), random forest, neural network, adaptive ensemble classifier, data mining, and principle component analysis-based approaches have been discussed in [22][23][24][25][26][27][28][29][30][31][32]. Even though these approaches give good results, the requirement of a vast number of input patterns for training, complexity in training procedure and large errors for unobserved pattern/dataset make the above techniques less popular.…”

Second harmonic impedance drift‐based islanding detection method

“…These methods are effective only when there is a large mismatch between power generation by DG and the local loads. In [12][13][14][15][16][17][18], passive methods with reduced NDZ have been proposed. A passive method with negligible NDZ is proposed in [19], but communication is needed between the utility grid and DG.…”

“…A passive method with negligible NDZ is proposed in [19], but communication is needed between the utility grid and DG. The passive islanding detection methods [6][7][8][9][10][11][12][13][14][15][16][17][18][19], fail to achieve the thresholds required for islanding detection when a minimal mismatch in power generation and the load of the islanded microgrid exists.…”

“…The impedance-based methods [34][35][36][37][38] have NDZ and take a longer time for detection of islanding. The passive method [6][7][8][9][10][11][12][13][14][15][16][17][18][19], the active method [20][21][22][23][24][25][26][27][28][29][30][31][32][33], impedance-based methods [34][35][36][37][38] do not consider DG cut-in event. Hence, a method is needed, which can detect islanding in zero power mismatch condition in an islanded microgrid, and differentiates between DG cut-in event and islanding event.…”