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Intelligent Differential Protection Scheme for Controlled Islanding of Microgrids Based on Decision Tree Technique

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Abstract

This paper presents an intelligent non-model-based differential relay for protecting microgrid systems in the case of islanding scenarios. For this purpose, by using discrete Fourier transform, different types of electrical signals including voltage and current phasors are processed during fault events by which the most observable signals are estimated to identify system abnormal conditions. In order to identify proper protection signals, an intelligent decision tree (IDT) technique is implemented from which the most effective signals for designing differential protection relay are provided. The proposed IDT-based differential scheme is trained comprehensively in off-line environment using different fault scenarios, both operational and topological. Then, it is implemented in online working mode where, by applying candidate protection signals as input to the proposed intelligent relay, the proper differential protection is derived. The proposed protection relay is an online and non-model-based scheme which can be implemented within a wide range of topologies including mesh and radial topologies in terms of the system operating conditions. The proposed strategy is implemented on a modified IEC case with different fault scenarios. Through considering two grid-connected and islanded system operating modes, the performance of the proposed intelligent differential relay is evaluated. Simulation test results indicate the considerable ability of the proposed technique for proper estimation of decision signals in different fault scenarios within real-time environment.

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(Kar and Samantaray 2014)

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Abbreviations

CART:

Classification and regression tree

CB:

Circuit breaker

CT:

Current transformer

CTI:

Coordination Time Interval

DFT:

Discrete Fourier transform

DG:

Distributed generators

GCM:

Grid connected mode

IDT:

Intelligent decision tree

IM:

Islanded mode

LCM:

Linear correlation metric

LSTM:

Long/short term memory

MG:

Microgrid

MMT:

Minimum melting time

NN:

Neural network

OLCM:

Overall linear correlation metric

PMU:

Phasor measurement unit

RBF:

Radial basis function network

RNN:

Recurrent neural network

SLCM:

Stable linear correlation metric

SVM:

Support vector machine

TCT:

Total clearing time

ULCM:

Unstable linear correlation metric

ΔF :

Frequency deviation

ΔV :

Voltage deviation

Δθ :

Voltage phase angle oscillations

ΔφI :

Current phase angle oscillations

ΔP :

Active power deviation

ΔQ :

Reactive power deviation

ΔVn :

Negative sequence of voltage signal

ΔIn :

Negative sequence of current signal

I diff :

Differential current Idiff at each time step

I sum :

Summation of currents at each time step

K :

Constant gain for considering CT saturation in relay zone

I ths :

Threshold current for activating relay commands

α :

Constant index which specifies a safety factor in the differential relay zone

t diff :

Coordination time of differential relay

t fuse :

Coordination time of installed fuses

ΔS :

Sensitivity index

E i :

Entropy index for each feature i

D p :

Positive data set within data classification

D n :

Negative data set within data classification

G (i,e) :

Gini Gi index at each node e with respect to feature i

P (i,e) :

Conditional probability of feature i with respect to node e

π i :

Prior probability of feature i

e :

Decision tree node

N i :

Number of samples in root node

Gain(s,e):

Information gain related to the separated sampling data s in node e

BE(e):

Backed up error at each non-leaf node

Error(e):

Error for each internal node e

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Authors and Affiliations

  1. Department of Electrical Engineering, Islamic Azad University Gorgan Branch, Gorgan, Golestan, Iran

    Iman Sepehrirad, Reza Ebrahimi & Soheil Ranjbar

  2. Department of Electrical Engineering, Islamic Azad University Aliabad Katoul Branch, Aliabad Katoul, Golestan, Iran

    Esmaeil Alibeiki

Authors
  1. Iman Sepehrirad
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  2. Reza Ebrahimi
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  3. Esmaeil Alibeiki
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  4. Soheil Ranjbar
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Correspondence to Reza Ebrahimi.

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Appendix

Appendix

See Tables 9, 10, 11 and 12.

Table 9 Distributed generator parameters
Full size table
Table 10 Distributed load parameters
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Table 11 Transformer parameters
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Table 12 Distributed line parameters
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Sepehrirad, I., Ebrahimi, R., Alibeiki, E. et al. Intelligent Differential Protection Scheme for Controlled Islanding of Microgrids Based on Decision Tree Technique. J Control Autom Electr Syst 31, 1233–1250 (2020). https://doi.org/10.1007/s40313-020-00588-7

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  • DOI: https://doi.org/10.1007/s40313-020-00588-7

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