# Integrated Microgrid Islanding Detection with Phase Angle Difference for Reduced Nondetection Zone

Authors: Bangar Raju Lingampalli; Subba Rao Kotamraju; M. Kiran Kumar; Ch. Rami Reddy; Mukesh Pushkarna; Mohit Bajaj; Hossam Kotb; Sadam Alphonse
Journal: International Journal of Energy Research
 (2023)

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## Abstract

Microgrids with distributed generation (DG) are rapidly coming into distribution networks to supply load demand in order to preserve ecological balance and reduce greenhouse gas emissions. Power electronic advancements are making renewables dispatchable to loads while turning passive networks to active with bidirectional power flow. The IEEE-1547-2018 regulations enforced certain standards on microgrids, including the ability to detect unintended failures, island the microgrid in less than 2 seconds, and feed connected loads while maintaining voltage, frequency, and power quality. There are numerous islanding techniques accessible, including passive, active, hybrid, and communication techniques. The active techniques degrade power quality due to injection of deviations, passive type leaves larger nondetection zone (NDZ), and communication type are costly. The hybrid type combines both passive and active methods. To get away from all these issues, a passive technique is formulated in this paper, which measures the differential phase angle of voltage and current at DG output, to detect islanding. This approach reliably identifies islanding in 20 ms at nearly zero NDZ. This approach is also stable during transient conditions such as load switching and throwing off. There is also no power quality issue because there are no injections during testing. This method is tested in MATLAB/Simulink and evaluated using the differential frequency technique to get performance indices in accordance with UL-1741 testing standards.


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## Body

## 1. Introduction

Microgrids are made up of loads and distributed energy resources that can interact within clear electrical boundaries to form a single controllable entity that can be connected or disconnected from the main grid. Islanding is a phenomenon that occurs when the microgrid is disconnected from the main distribution system owing to system problems. The IEEE-1547-2018 establishes a number of standards for microgrids that are either connected to or separated from the main grid and are capable of supplying loads on their own. Every microgrid needs to have an islanding detection technique that detects the islanding, effortlessly transitions the microgrid to islanding mode in under 2 seconds, and ensures reliable power to linked loads. Blackout-causing nuisance tripping and auto-reclosing should also be handled by this islanding detection. To obviate all this, a passive islanding technique is suggested, which is dependent on the phase angle difference to detect islanding scenario. It is mandatory to consider the safety of the persons and the equipment involved. For this, the IEEE-1547-2018 specifies certain standards to be maintained regarding the performance indices like, NDZ, detection time, and error detection ratio [1].


### 1.1. Performance Evaluation Indices

(i)
NDZ. Nondetection zone is the zone wherein islanding condition cannot be sensed due to the inefficiency of the detection technique. Based on the type of the detection method, testing for NDZ is again classified into two types [2](a)
Power Mismatch Space. The NDZ measurement is done on power mismatch space for passive methods, which are dependent on the variation of voltage, frequency, power, and phase angle(b)
Load Parameter Space. The NDZ measurement is done on load parameter space for active detection techniques which are dependent on creation of certain perturbancesPower mismatch space: variation in amplitudes of frequency and voltage are not sufficient enough to cross the thresholds, when demand and supply matches, i.e., ΔQ and ΔP are equal to zero. Hence, the detection of the islanding method fails. The real and reactive mismatch powers are given by the following equations
(1)VVmax2−1≤ΔPPDG≤VVmin2−1,(2)Qf1−ffmin2≤ΔQPDG≤Qf1−ffmax2.The UL-1741 testing standards prescribe certain methods depending on the type of detection technique.The performance indices for passive methods for different standards are given in Table1.Table 1
% power mismatch space (%PMS) for different international standards.
Islanding standardDetection time (secs)vmax%vmin%fmax (Hz)fmin (Hz)QfQuality factor% power mismatch space (%PMS)ΔPPDGminΔPPDGmaxΔQPDGminΔQPDGmaxIEEE-1547-201821108861.258.81-1714-44IEEE-929-200021108860.559.32.5-1714-55Korean Std.0.51108860.559.31-1714-55VDE V 0126-1-10.21108850.547.52-1714-204UL-174121108860.559.32.5-1714-55Load parameter space: the NDZ measurement technique based on load parameter space is utilized to find the performance of active type of detection method, which depends on disturbance injection. The NDZ load parameter space is given by the following equation
(3)F1cf,K,Q<ΔCnorm<F2cf,K,Q.In whichK is accelerating gain, cf is chopping fraction, Q is load quality factor, and ΔCnorm is resonance capacitance resonance, for the limit of NDZ.
(ii)
Time of detectionTime of detection is the time between disconnecting the microgrid till the end of islanding by the detection method. The detection timeΔT is given by [3]
(4)ΔT=TIDM−TTrip.In which ΔT is the time between starting and the disconnection of microgrid for the islanding detection technique.
(iii)
Error detection ratioThis is defined as the wrong sensing of transient operation of microgrid as an islanding operation. These are normally caused during capacitor banks switching on and loads connecting and throwing off, which are system transient states. These are nuisance tripping, causing instability to the grid-connected system. The error detection ratio is the ratio between wrong detection time to total detection time of the detection method [4].
(iv)
Power qualityPower quality measurement is done by comparison of % total harmonic distortion (THD) during normal operation and islanding operation. During grid mode, the value of % THD will be within the limits which is <5% but in islanded mode, and the value exceeds the limit due to inverter harmonics. The power quality deteriorates during the initiation of perturbances for test purposes, in active techniques [5].


### 1.2. Islanding Detection Techniques

The islanding detection techniques have been divided into local and remote. The local types are again divided into passive, active, and hybrid, which depend on local measurement [6]. The remote methods depend on media and are suitable for microgrids, which are away from distribution network. The passive methods measure the variations in measurements during normal working and islanding [7]. The active methods depend on certain perturbations and detect islanding due to variations during islanding conditions [8]. The hybrid techniques are compound effect of passive and active techniques [9]. The performance indices of some methods are shown in Table 2.Table 2
Islanding detection methods existing.
MethodTechniqueNDZTime of detection (ms)Error ratioQuality of powerPassive:1. Voltage unbalanceLarge53 msLowNo effect2. Harmonic distortionLarge45 msHighNo effect3. Over/under voltage/frequencyLarge2 ms–2 sHighNo effect4. Differential of powerSmall24–26 msHighNo effect5. Differential of frequencySmall24 msHighNo effect6. Rate of change of frequency over powerSmall100 msLowNo effect7. Phase jump detectionLarge10–20 msLowNo effectActive:1. Impedance measurementSmall770–950 msLowDegrades2. Active frequency driftLarge<2 sHighDegrades3. Frequency jumpSmall75 msLowDegrades4. Sandia frequency shiftSmall0.5 sLowSlightly degrades5. Sandia voltage shiftSmall0.5 sLowSlightly degrades6. Slip mode frequency shiftSmall0.4 sLowSlightly deteriorates7. Variation ofP and QSmall0.3 to 0.7 sHighSlightly deteriorates8. Injection of negative-sequence currentNegligible60 msLowDeteriorates9. Injection of high frequency signalSmallA few msLowSlightly deteriorates10. Virtual capacitorSmall20–51 msLowSlightly deteriorates11. Virtual inductorSmall13–59 msLowSlightly deteriorates12. Phase PLL disturbanceSmall120 msLowNegligibleHybrid:1. Positive feedback and voltage imbalanceSmall>1 sLowSlightly degrades2. Voltage and reactive power shiftSmall<1 sLowDegrades3. SFS and Q-f based schemeSmall>1 sLowDegrades4. SFS and ROCOFSmall<1 sLowDegradesRemote:1. Power line carrier communicationSmall<1 sLowNo effect2. Supervisory control and data acquisitionSmall<1 sLowNo effect3. Impedance insertion schemeSmall>1 sLowNo effect4. Micro-PMU schemesSmall<1 sLowNo effect5. Angle difference methodSmall<1 sLowNo effect6. Transfer trip schemesSmall>1 sLowNo effect


#### 1.2.1. Passive Islanding Detection Techniques

The passive techniques depend on the variation of measurements at PCC between normal operation and islanding, to detect islanding condition.Voltage imbalance method: the technique depends on the principle of amplitude variation of voltage during islanding and normal operation. This technique is good with less detection time, i.e., 53 ms, but is not sensitive to loads switching on and throwing off. The NDZ is also large. It is not having power quality issue as there are no injections [10].Harmonic distortion method: this method is dependent on variation of total harmonic distortion (THD) at PCC during islanding. The NDZ is large with detection less time 45 ms. The error ratio is high, with no power quality degradation [2].Over/under voltage/frequency method: this is common type used in all protection systems. The NDZ is large with high error ratio and detection time, but with no power quality degradation [11].Differential of power method: the method is dependent on the amplitude of rate of change of power during islanding. The NDZ is small with high error ratio but with less detection time and with no power quality issue [12].Differential of frequency method: this method depends on the variations in rate of change of frequency during islanding. The grid code limit for ROCOF is 1 Hz/sec with detection time 100 ms. The NDZ is large with high error ratio but with less detection time and with no power quality issue [13].Differential of frequency over power method: the method is dependent on variations in rate of change of frequency over power during islanding. The NDZ is small with low error ratio but with less detection time and with no power quality degradation [14].Phase jump method: the NDZ is large with low error ratio but with less detecting time and with no power quality issue [15].


#### 1.2.2. Active Islanding Detection Methods

The active techniques depend on the variation of measurements between normal operation and during injection of pertubations in islanding mode, to detect islanding condition. Some of this type of methods are discussed below.Impedance measurement method: the variation in voltage and current and thereby impedance is substantial enough to detect islanding condition. The NDZ is small with low error ratio but with higher detection time and with power quality degradation [16].Active frequency drift method: this technique depends on voltage frequency, drifting forcibly up or down and there by detecting the islanding. The NDZ is large with high error ratio but with higher detection time and with power quality degradation [17].Frequency jump method: this method creates a dead zone for every three cycles, and during islanding, the voltage frequency is substantial and thereby islanding is detected. The NDZ is small with low error ratio but with higher detection time and with power quality degradation [18].Sandia frequency shift method: this technique takes care of the positive feedback of inverter voltage and thereby detecting the islanding. The NDZ is small with low error ratio but with less detection time and has no quality degradation [19].Sandia voltage shift method: this technique uses the injection of inverter current, monitoring the voltage variation and thereby detecting the islanding. The NDZ is small with low error ratio but with lower detection time and with small power quality degradation [20].Slip mode frequency shift method: this technique uses the injection of inverter current, monitoring the voltage and frequency variation and thereby detecting the islanding. It is a good anti-islanding method. The NDZ is small with low error ratio but with lower detection time and with small power quality degradation [21].Variation ofPandQmethod: by varying the active and reactive powers, the variations in voltage and frequency are monitored and thereby detecting the islanding condition. In this method, the NDZ is small with low error ratio but with lower detection time and with small power quality degradation [22].Negative-sequence current injection method: this technique uses the injection of negative sequence current and monitoring the amplitude of negative sequence voltage variation for detecting the islanding. It is a good anti-islanding detection method. The NDZ is very small with low error ratio, with lower detection time and with small power quality degradation [23].High frequency signal injection method: this method is dependent on high frequency voltage signal injection and analyzing the current response, to detect islanding. The NDZ is very small with low error ratio, with lower detection time and with small power quality degradation [24].Virtual capacitor method: during islanding, when the frequency of grid interfaced inverter is higher due to the inverter inductance, this is used to detect islanding. The NDZ is small with low error ratio and detection time [25].Virtual inductor method: during islanding, when the frequency of grid interfaced inverter is lower due to the inverter inductance, this is used to detect islanding. The NDZ is small with low error ratio and detection time [26].Phase PLL disturbance: during islanding, the injected reference output voltage or current phase angle changes, and this is used to detect islanding. The NDZ is small with low error ratio and detection time with negligible power quality effect [27].


#### 1.2.3. Hybrid Islanding Detection Techniques

The hybrid techniques combine passive and active methods for reliable operation of detection method. First, the passive method is used to detect the islanding, failing which the active injection is used to detect the islanding. Some of these types are discussed below.Positive feedback and voltage imbalance: it is a mixture of active method feedback and passive voltage imbalance method. To confirm the passive voltage imbalance, after one second, the frequency set point is changed from 60 to 50 Hz and islanding is confirmed. The NDZ is very small, error ratio is low, and detection time is more with small power quality degradation [28].Voltage and reactive power shift: this technique is a mixture of passive voltage frequency variation and reactive power shift confirmation, for detection of islanding scenario. The NDZ is small with lower error ratio and with higher detection time and power degradation [29].SFS and Q-f based scheme: this method is a mixture of active Sandia frequency shift and passive reverse droop method, to detect islanding. The NDZ is small with lower error ratio and with higher detection time and power degradation [30].SFS and ROCOF: this method is a mixture of active Sandia frequency shift and passive differential of frequency method, to detect islanding. The NDZ is small with lower error ratio but with higher detection time. The power quality degrades due to frequency shift [31].


#### 1.2.4. Remote Detection Methods

These type of methods are well suitable for remote operations, where the microgrid is far off from distribution network. But they take the support of network media, for the detection of islanding. These are efficient effective, reliable but are costly for implementation.Power line carrier communication: this method is simple. The transmitters are placed on remote distribution side and the receivers in microgrid. During islanding, there is no signal received from grid side and hence islanding is confirmed. The NDZ is very small with low error ratio and higher detection time having no power quality degradation [32].Supervisory control and data acquisition: this method depends on the observation of circuit breaker contacts. During islanding, many auxiliary contacts of the breaker are utilized for alarm purposes. Some of these contacts can be used to isolate DG. This method is effective but requires more sensors. The NDZ is very small with low error ratio and higher detection time having no power quality degradation [33].Impedance insertion scheme: the impedance insertion at PCC has normal variations in voltage and current during normal operation, but during islanding, the variations are sufficient to sense islanding. This method leaves behind smaller NDZ with very less detection time and error ratio. It has low power quality degradation [34].Micro-PMU schemes: the micro-PMU method works through communication network and is very effective with small NDZ, less detection time, and low detection time. But there is no power quality effect with this method. But it is prone to cyber-attacks. To get away this problem, the micro-MPU is installed on the DG bus, and the attackers cannot interfere with the device [35].Angle difference method: this method depends on difference between the microgrid and distribution side synchrophasor angle values and is compared against an angle threshold, to sense islanding. This method has lower NDZ, low error ratio, low detection time, and no power degradation [8].Transfer trip schemes: a server system monitors the circuit breaker status of utility side and sends command to stop the DGs supplying load. This technique has small NDZ, low error ratio, low detection time, and no power degradation [36, 37].


#### 1.2.5. Signal Processing-Based Islanding Detection Techniques

Signal processing (SP) techniques are used for detection of islanding to reduce NDZ for passive techniques. SP techniques are based on utilizing the inside features of any signal, which is more advantageous than other passive techniques [38, 39].


#### 1.2.6. Computational Intelligence-Based Islanding Detection Techniques

In spite of the SP technique’s added efficiency in islanding sensing, they cannot reduce the NDZ due to DG system complex nature. In these situations, addition of intelligence to the detection technique enhances the effectiveness. The intelligent computational techniques can monitor multiple measurements continuously at a time and hence are utilized for detection purposes for higher efficiency [40, 41].


## 1.1. Performance Evaluation Indices

(i)
NDZ. Nondetection zone is the zone wherein islanding condition cannot be sensed due to the inefficiency of the detection technique. Based on the type of the detection method, testing for NDZ is again classified into two types [2](a)
Power Mismatch Space. The NDZ measurement is done on power mismatch space for passive methods, which are dependent on the variation of voltage, frequency, power, and phase angle(b)
Load Parameter Space. The NDZ measurement is done on load parameter space for active detection techniques which are dependent on creation of certain perturbancesPower mismatch space: variation in amplitudes of frequency and voltage are not sufficient enough to cross the thresholds, when demand and supply matches, i.e., ΔQ and ΔP are equal to zero. Hence, the detection of the islanding method fails. The real and reactive mismatch powers are given by the following equations
(1)VVmax2−1≤ΔPPDG≤VVmin2−1,(2)Qf1−ffmin2≤ΔQPDG≤Qf1−ffmax2.The UL-1741 testing standards prescribe certain methods depending on the type of detection technique.The performance indices for passive methods for different standards are given in Table1.Table 1
% power mismatch space (%PMS) for different international standards.
Islanding standardDetection time (secs)vmax%vmin%fmax (Hz)fmin (Hz)QfQuality factor% power mismatch space (%PMS)ΔPPDGminΔPPDGmaxΔQPDGminΔQPDGmaxIEEE-1547-201821108861.258.81-1714-44IEEE-929-200021108860.559.32.5-1714-55Korean Std.0.51108860.559.31-1714-55VDE V 0126-1-10.21108850.547.52-1714-204UL-174121108860.559.32.5-1714-55Load parameter space: the NDZ measurement technique based on load parameter space is utilized to find the performance of active type of detection method, which depends on disturbance injection. The NDZ load parameter space is given by the following equation
(3)F1cf,K,Q<ΔCnorm<F2cf,K,Q.In whichK is accelerating gain, cf is chopping fraction, Q is load quality factor, and ΔCnorm is resonance capacitance resonance, for the limit of NDZ.
(ii)
Time of detectionTime of detection is the time between disconnecting the microgrid till the end of islanding by the detection method. The detection timeΔT is given by [3]
(4)ΔT=TIDM−TTrip.In which ΔT is the time between starting and the disconnection of microgrid for the islanding detection technique.
(iii)
Error detection ratioThis is defined as the wrong sensing of transient operation of microgrid as an islanding operation. These are normally caused during capacitor banks switching on and loads connecting and throwing off, which are system transient states. These are nuisance tripping, causing instability to the grid-connected system. The error detection ratio is the ratio between wrong detection time to total detection time of the detection method [4].
(iv)
Power qualityPower quality measurement is done by comparison of % total harmonic distortion (THD) during normal operation and islanding operation. During grid mode, the value of % THD will be within the limits which is <5% but in islanded mode, and the value exceeds the limit due to inverter harmonics. The power quality deteriorates during the initiation of perturbances for test purposes, in active techniques [5].


## 1.2. Islanding Detection Techniques

The islanding detection techniques have been divided into local and remote. The local types are again divided into passive, active, and hybrid, which depend on local measurement [6]. The remote methods depend on media and are suitable for microgrids, which are away from distribution network. The passive methods measure the variations in measurements during normal working and islanding [7]. The active methods depend on certain perturbations and detect islanding due to variations during islanding conditions [8]. The hybrid techniques are compound effect of passive and active techniques [9]. The performance indices of some methods are shown in Table 2.Table 2
Islanding detection methods existing.
MethodTechniqueNDZTime of detection (ms)Error ratioQuality of powerPassive:1. Voltage unbalanceLarge53 msLowNo effect2. Harmonic distortionLarge45 msHighNo effect3. Over/under voltage/frequencyLarge2 ms–2 sHighNo effect4. Differential of powerSmall24–26 msHighNo effect5. Differential of frequencySmall24 msHighNo effect6. Rate of change of frequency over powerSmall100 msLowNo effect7. Phase jump detectionLarge10–20 msLowNo effectActive:1. Impedance measurementSmall770–950 msLowDegrades2. Active frequency driftLarge<2 sHighDegrades3. Frequency jumpSmall75 msLowDegrades4. Sandia frequency shiftSmall0.5 sLowSlightly degrades5. Sandia voltage shiftSmall0.5 sLowSlightly degrades6. Slip mode frequency shiftSmall0.4 sLowSlightly deteriorates7. Variation ofP and QSmall0.3 to 0.7 sHighSlightly deteriorates8. Injection of negative-sequence currentNegligible60 msLowDeteriorates9. Injection of high frequency signalSmallA few msLowSlightly deteriorates10. Virtual capacitorSmall20–51 msLowSlightly deteriorates11. Virtual inductorSmall13–59 msLowSlightly deteriorates12. Phase PLL disturbanceSmall120 msLowNegligibleHybrid:1. Positive feedback and voltage imbalanceSmall>1 sLowSlightly degrades2. Voltage and reactive power shiftSmall<1 sLowDegrades3. SFS and Q-f based schemeSmall>1 sLowDegrades4. SFS and ROCOFSmall<1 sLowDegradesRemote:1. Power line carrier communicationSmall<1 sLowNo effect2. Supervisory control and data acquisitionSmall<1 sLowNo effect3. Impedance insertion schemeSmall>1 sLowNo effect4. Micro-PMU schemesSmall<1 sLowNo effect5. Angle difference methodSmall<1 sLowNo effect6. Transfer trip schemesSmall>1 sLowNo effect


### 1.2.1. Passive Islanding Detection Techniques

The passive techniques depend on the variation of measurements at PCC between normal operation and islanding, to detect islanding condition.Voltage imbalance method: the technique depends on the principle of amplitude variation of voltage during islanding and normal operation. This technique is good with less detection time, i.e., 53 ms, but is not sensitive to loads switching on and throwing off. The NDZ is also large. It is not having power quality issue as there are no injections [10].Harmonic distortion method: this method is dependent on variation of total harmonic distortion (THD) at PCC during islanding. The NDZ is large with detection less time 45 ms. The error ratio is high, with no power quality degradation [2].Over/under voltage/frequency method: this is common type used in all protection systems. The NDZ is large with high error ratio and detection time, but with no power quality degradation [11].Differential of power method: the method is dependent on the amplitude of rate of change of power during islanding. The NDZ is small with high error ratio but with less detection time and with no power quality issue [12].Differential of frequency method: this method depends on the variations in rate of change of frequency during islanding. The grid code limit for ROCOF is 1 Hz/sec with detection time 100 ms. The NDZ is large with high error ratio but with less detection time and with no power quality issue [13].Differential of frequency over power method: the method is dependent on variations in rate of change of frequency over power during islanding. The NDZ is small with low error ratio but with less detection time and with no power quality degradation [14].Phase jump method: the NDZ is large with low error ratio but with less detecting time and with no power quality issue [15].


### 1.2.2. Active Islanding Detection Methods

The active techniques depend on the variation of measurements between normal operation and during injection of pertubations in islanding mode, to detect islanding condition. Some of this type of methods are discussed below.Impedance measurement method: the variation in voltage and current and thereby impedance is substantial enough to detect islanding condition. The NDZ is small with low error ratio but with higher detection time and with power quality degradation [16].Active frequency drift method: this technique depends on voltage frequency, drifting forcibly up or down and there by detecting the islanding. The NDZ is large with high error ratio but with higher detection time and with power quality degradation [17].Frequency jump method: this method creates a dead zone for every three cycles, and during islanding, the voltage frequency is substantial and thereby islanding is detected. The NDZ is small with low error ratio but with higher detection time and with power quality degradation [18].Sandia frequency shift method: this technique takes care of the positive feedback of inverter voltage and thereby detecting the islanding. The NDZ is small with low error ratio but with less detection time and has no quality degradation [19].Sandia voltage shift method: this technique uses the injection of inverter current, monitoring the voltage variation and thereby detecting the islanding. The NDZ is small with low error ratio but with lower detection time and with small power quality degradation [20].Slip mode frequency shift method: this technique uses the injection of inverter current, monitoring the voltage and frequency variation and thereby detecting the islanding. It is a good anti-islanding method. The NDZ is small with low error ratio but with lower detection time and with small power quality degradation [21].Variation ofPandQmethod: by varying the active and reactive powers, the variations in voltage and frequency are monitored and thereby detecting the islanding condition. In this method, the NDZ is small with low error ratio but with lower detection time and with small power quality degradation [22].Negative-sequence current injection method: this technique uses the injection of negative sequence current and monitoring the amplitude of negative sequence voltage variation for detecting the islanding. It is a good anti-islanding detection method. The NDZ is very small with low error ratio, with lower detection time and with small power quality degradation [23].High frequency signal injection method: this method is dependent on high frequency voltage signal injection and analyzing the current response, to detect islanding. The NDZ is very small with low error ratio, with lower detection time and with small power quality degradation [24].Virtual capacitor method: during islanding, when the frequency of grid interfaced inverter is higher due to the inverter inductance, this is used to detect islanding. The NDZ is small with low error ratio and detection time [25].Virtual inductor method: during islanding, when the frequency of grid interfaced inverter is lower due to the inverter inductance, this is used to detect islanding. The NDZ is small with low error ratio and detection time [26].Phase PLL disturbance: during islanding, the injected reference output voltage or current phase angle changes, and this is used to detect islanding. The NDZ is small with low error ratio and detection time with negligible power quality effect [27].


### 1.2.3. Hybrid Islanding Detection Techniques

The hybrid techniques combine passive and active methods for reliable operation of detection method. First, the passive method is used to detect the islanding, failing which the active injection is used to detect the islanding. Some of these types are discussed below.Positive feedback and voltage imbalance: it is a mixture of active method feedback and passive voltage imbalance method. To confirm the passive voltage imbalance, after one second, the frequency set point is changed from 60 to 50 Hz and islanding is confirmed. The NDZ is very small, error ratio is low, and detection time is more with small power quality degradation [28].Voltage and reactive power shift: this technique is a mixture of passive voltage frequency variation and reactive power shift confirmation, for detection of islanding scenario. The NDZ is small with lower error ratio and with higher detection time and power degradation [29].SFS and Q-f based scheme: this method is a mixture of active Sandia frequency shift and passive reverse droop method, to detect islanding. The NDZ is small with lower error ratio and with higher detection time and power degradation [30].SFS and ROCOF: this method is a mixture of active Sandia frequency shift and passive differential of frequency method, to detect islanding. The NDZ is small with lower error ratio but with higher detection time. The power quality degrades due to frequency shift [31].


### 1.2.4. Remote Detection Methods

These type of methods are well suitable for remote operations, where the microgrid is far off from distribution network. But they take the support of network media, for the detection of islanding. These are efficient effective, reliable but are costly for implementation.Power line carrier communication: this method is simple. The transmitters are placed on remote distribution side and the receivers in microgrid. During islanding, there is no signal received from grid side and hence islanding is confirmed. The NDZ is very small with low error ratio and higher detection time having no power quality degradation [32].Supervisory control and data acquisition: this method depends on the observation of circuit breaker contacts. During islanding, many auxiliary contacts of the breaker are utilized for alarm purposes. Some of these contacts can be used to isolate DG. This method is effective but requires more sensors. The NDZ is very small with low error ratio and higher detection time having no power quality degradation [33].Impedance insertion scheme: the impedance insertion at PCC has normal variations in voltage and current during normal operation, but during islanding, the variations are sufficient to sense islanding. This method leaves behind smaller NDZ with very less detection time and error ratio. It has low power quality degradation [34].Micro-PMU schemes: the micro-PMU method works through communication network and is very effective with small NDZ, less detection time, and low detection time. But there is no power quality effect with this method. But it is prone to cyber-attacks. To get away this problem, the micro-MPU is installed on the DG bus, and the attackers cannot interfere with the device [35].Angle difference method: this method depends on difference between the microgrid and distribution side synchrophasor angle values and is compared against an angle threshold, to sense islanding. This method has lower NDZ, low error ratio, low detection time, and no power degradation [8].Transfer trip schemes: a server system monitors the circuit breaker status of utility side and sends command to stop the DGs supplying load. This technique has small NDZ, low error ratio, low detection time, and no power degradation [36, 37].


### 1.2.5. Signal Processing-Based Islanding Detection Techniques

Signal processing (SP) techniques are used for detection of islanding to reduce NDZ for passive techniques. SP techniques are based on utilizing the inside features of any signal, which is more advantageous than other passive techniques [38, 39].


### 1.2.6. Computational Intelligence-Based Islanding Detection Techniques

In spite of the SP technique’s added efficiency in islanding sensing, they cannot reduce the NDZ due to DG system complex nature. In these situations, addition of intelligence to the detection technique enhances the effectiveness. The intelligent computational techniques can monitor multiple measurements continuously at a time and hence are utilized for detection purposes for higher efficiency [40, 41].


## 1.2.1. Passive Islanding Detection Techniques

The passive techniques depend on the variation of measurements at PCC between normal operation and islanding, to detect islanding condition.Voltage imbalance method: the technique depends on the principle of amplitude variation of voltage during islanding and normal operation. This technique is good with less detection time, i.e., 53 ms, but is not sensitive to loads switching on and throwing off. The NDZ is also large. It is not having power quality issue as there are no injections [10].Harmonic distortion method: this method is dependent on variation of total harmonic distortion (THD) at PCC during islanding. The NDZ is large with detection less time 45 ms. The error ratio is high, with no power quality degradation [2].Over/under voltage/frequency method: this is common type used in all protection systems. The NDZ is large with high error ratio and detection time, but with no power quality degradation [11].Differential of power method: the method is dependent on the amplitude of rate of change of power during islanding. The NDZ is small with high error ratio but with less detection time and with no power quality issue [12].Differential of frequency method: this method depends on the variations in rate of change of frequency during islanding. The grid code limit for ROCOF is 1 Hz/sec with detection time 100 ms. The NDZ is large with high error ratio but with less detection time and with no power quality issue [13].Differential of frequency over power method: the method is dependent on variations in rate of change of frequency over power during islanding. The NDZ is small with low error ratio but with less detection time and with no power quality degradation [14].Phase jump method: the NDZ is large with low error ratio but with less detecting time and with no power quality issue [15].


## 1.2.2. Active Islanding Detection Methods

The active techniques depend on the variation of measurements between normal operation and during injection of pertubations in islanding mode, to detect islanding condition. Some of this type of methods are discussed below.Impedance measurement method: the variation in voltage and current and thereby impedance is substantial enough to detect islanding condition. The NDZ is small with low error ratio but with higher detection time and with power quality degradation [16].Active frequency drift method: this technique depends on voltage frequency, drifting forcibly up or down and there by detecting the islanding. The NDZ is large with high error ratio but with higher detection time and with power quality degradation [17].Frequency jump method: this method creates a dead zone for every three cycles, and during islanding, the voltage frequency is substantial and thereby islanding is detected. The NDZ is small with low error ratio but with higher detection time and with power quality degradation [18].Sandia frequency shift method: this technique takes care of the positive feedback of inverter voltage and thereby detecting the islanding. The NDZ is small with low error ratio but with less detection time and has no quality degradation [19].Sandia voltage shift method: this technique uses the injection of inverter current, monitoring the voltage variation and thereby detecting the islanding. The NDZ is small with low error ratio but with lower detection time and with small power quality degradation [20].Slip mode frequency shift method: this technique uses the injection of inverter current, monitoring the voltage and frequency variation and thereby detecting the islanding. It is a good anti-islanding method. The NDZ is small with low error ratio but with lower detection time and with small power quality degradation [21].Variation ofPandQmethod: by varying the active and reactive powers, the variations in voltage and frequency are monitored and thereby detecting the islanding condition. In this method, the NDZ is small with low error ratio but with lower detection time and with small power quality degradation [22].Negative-sequence current injection method: this technique uses the injection of negative sequence current and monitoring the amplitude of negative sequence voltage variation for detecting the islanding. It is a good anti-islanding detection method. The NDZ is very small with low error ratio, with lower detection time and with small power quality degradation [23].High frequency signal injection method: this method is dependent on high frequency voltage signal injection and analyzing the current response, to detect islanding. The NDZ is very small with low error ratio, with lower detection time and with small power quality degradation [24].Virtual capacitor method: during islanding, when the frequency of grid interfaced inverter is higher due to the inverter inductance, this is used to detect islanding. The NDZ is small with low error ratio and detection time [25].Virtual inductor method: during islanding, when the frequency of grid interfaced inverter is lower due to the inverter inductance, this is used to detect islanding. The NDZ is small with low error ratio and detection time [26].Phase PLL disturbance: during islanding, the injected reference output voltage or current phase angle changes, and this is used to detect islanding. The NDZ is small with low error ratio and detection time with negligible power quality effect [27].


## 1.2.3. Hybrid Islanding Detection Techniques

The hybrid techniques combine passive and active methods for reliable operation of detection method. First, the passive method is used to detect the islanding, failing which the active injection is used to detect the islanding. Some of these types are discussed below.Positive feedback and voltage imbalance: it is a mixture of active method feedback and passive voltage imbalance method. To confirm the passive voltage imbalance, after one second, the frequency set point is changed from 60 to 50 Hz and islanding is confirmed. The NDZ is very small, error ratio is low, and detection time is more with small power quality degradation [28].Voltage and reactive power shift: this technique is a mixture of passive voltage frequency variation and reactive power shift confirmation, for detection of islanding scenario. The NDZ is small with lower error ratio and with higher detection time and power degradation [29].SFS and Q-f based scheme: this method is a mixture of active Sandia frequency shift and passive reverse droop method, to detect islanding. The NDZ is small with lower error ratio and with higher detection time and power degradation [30].SFS and ROCOF: this method is a mixture of active Sandia frequency shift and passive differential of frequency method, to detect islanding. The NDZ is small with lower error ratio but with higher detection time. The power quality degrades due to frequency shift [31].


## 1.2.4. Remote Detection Methods

These type of methods are well suitable for remote operations, where the microgrid is far off from distribution network. But they take the support of network media, for the detection of islanding. These are efficient effective, reliable but are costly for implementation.Power line carrier communication: this method is simple. The transmitters are placed on remote distribution side and the receivers in microgrid. During islanding, there is no signal received from grid side and hence islanding is confirmed. The NDZ is very small with low error ratio and higher detection time having no power quality degradation [32].Supervisory control and data acquisition: this method depends on the observation of circuit breaker contacts. During islanding, many auxiliary contacts of the breaker are utilized for alarm purposes. Some of these contacts can be used to isolate DG. This method is effective but requires more sensors. The NDZ is very small with low error ratio and higher detection time having no power quality degradation [33].Impedance insertion scheme: the impedance insertion at PCC has normal variations in voltage and current during normal operation, but during islanding, the variations are sufficient to sense islanding. This method leaves behind smaller NDZ with very less detection time and error ratio. It has low power quality degradation [34].Micro-PMU schemes: the micro-PMU method works through communication network and is very effective with small NDZ, less detection time, and low detection time. But there is no power quality effect with this method. But it is prone to cyber-attacks. To get away this problem, the micro-MPU is installed on the DG bus, and the attackers cannot interfere with the device [35].Angle difference method: this method depends on difference between the microgrid and distribution side synchrophasor angle values and is compared against an angle threshold, to sense islanding. This method has lower NDZ, low error ratio, low detection time, and no power degradation [8].Transfer trip schemes: a server system monitors the circuit breaker status of utility side and sends command to stop the DGs supplying load. This technique has small NDZ, low error ratio, low detection time, and no power degradation [36, 37].


## 1.2.5. Signal Processing-Based Islanding Detection Techniques

Signal processing (SP) techniques are used for detection of islanding to reduce NDZ for passive techniques. SP techniques are based on utilizing the inside features of any signal, which is more advantageous than other passive techniques [38, 39].


## 1.2.6. Computational Intelligence-Based Islanding Detection Techniques

In spite of the SP technique’s added efficiency in islanding sensing, they cannot reduce the NDZ due to DG system complex nature. In these situations, addition of intelligence to the detection technique enhances the effectiveness. The intelligent computational techniques can monitor multiple measurements continuously at a time and hence are utilized for detection purposes for higher efficiency [40, 41].


## 2. Mathematical and Network Model

In the proposed method, the absolute phase angle difference of voltage and current is retrieved at the DG output and differentiated to detect the islanding, when an unintentional symmetrical fault is initiated on the grid side. The method is evaluated against ROCOF method, for the performance indices as per UL-1741 testing standards in MATLAB/Simulink.The waveform signal equation is given by(5)Xt=∑k=1∞Aksin2πkft+δk.In whichAk and δk are kth waveform amplitude and angle, and f is the system frequency. By converting rotating to synchronous wave form of 3 phase abc quantities to 2 phase rotating direct and quadrature axis, dq0 components
(6)XdXq=Sinω0t−Cosω0t−Cosω0t−Sinω0t×1−12−12032−32×XaXbXc.In whichω0=2πf0 and f0 are frequency of the normal system. In this case, it is 50 Hz. Now inserting the value of equation (5) in (6) for the sample time of mth order, which is t=mTs, where m=0,1,2,⋯⋯,Ts is sampling interval. Equation (6) is rewritten as below
(7)XdmXqm=32∑k=1∞Akcos2πKf−f0mTs+δk−∑k=1∞Akcos2πKf−f0mTs+δk.In whichk=1, the fundamental quantities are given by
(8)Xd1m=1.5A1cos2πf−f0mTs+δ1,(9)Xq1m=−1.5A1cos2πf−f0mTs+δ1.The park transformationsd and q give out amplitude A1, phase δ1, and frequency f and are given as
(10)A1=23X2d1+X2q1,(11)δ1=arctan−Xq10Xd10,(12)f=δ1m−δ1m−p2πpTs+f0.In whichp=0,1,2,⋯⋯⋯.Equations (11) and (12) give out the values of phase and frequency with which ROCPAD and ROCOF are given by
(13)Differentialofphaseangledifference=△δv−δi△t,(14)ROCOF=△f△t.The schematic diagram for testing the proposed phase angle difference method of islanding detection is depicted in Figure1. The proposed method is tested on 3 kW DG with interfacing inverter of constant current control mode. A 3 phase parallel RLC load with quality factor of 1.8 is connected at PCC for MATLAB simulations, for testing purposes.Figure 1
Schematic diagram for testing the of phase angle difference method of detection technique.


### 2.1. Nondetection Zone (NDZ)

NDZ is the area in which detection method fails to detect islanding condition. It is one of the performance evaluation indices of detection method. The NDZ testing can be done by two methods, one is power mismatch space and the other is load parameter space. The power mismatch space method is used for all passive methods, and the load parameter space is used for active type method. The power mismatch consists of both real and reactive power mismatches. As per IEEE-1547-2018, the real and reactive power mismatch limits are <15% and <2%, respectively, and the detection time is <2 secs. The NDZ mapping of real and reactive power mismatch is shown in Figure2.Figure 2
NDZ for phase angle difference islanding detection method.The calculated power mismatch limits for rated inverter of2.5kW+0.5kVAr are +0.3 kW and −0.25 kW for active power mismatch and +0.0015kVAr and −0.002 kVAr for reactive power.During testing, to have more deviations in frequency in islanded mode, a load with quality factor (Qf) 1.8 is selected for testing the performance indices and is given by
(15)Qf=ω0RC=Rω0L=RCL.In which(16)ω0=2πf0=1LC.The equation of (16) decides quality factor, which decides islanding detection criterion. The load reactive power is given by
(17)QLoad=Vrms21ωL−ωc=ΔQ.Equation (17) gives the load reactive power. The real power mismatch is given by
(18)ΔP==3V×I–3V+ΔV×I=−3V×ΔV×I.The voltage and frequency limits, as per IEEE-1547-2018, are1.1≤V≤0.8p.u. and for frequency is 58.8≤f≤61.2Hz/sec. Hence, the mismatch of reactive power is
(19)ΔQ=3V2ωnL1−ω2LC=3V2ωnL1−ωn2ωr2,whereωn is system frequency, and ωr is resonance frequency. In islanding, reactive power changes as per load frequency, which is
(20)ωr=1LC.Hence, the mismatch of reactive power is(21)ΔQ=3V2ωnL1−fn2fn±Δf2.The limits of frequency as per IEEE-1547-2018 is 49 to 51 Hz (for 50 Hz system frequency), and theΔf range is ±1 Hz.


## 2.1. Nondetection Zone (NDZ)

NDZ is the area in which detection method fails to detect islanding condition. It is one of the performance evaluation indices of detection method. The NDZ testing can be done by two methods, one is power mismatch space and the other is load parameter space. The power mismatch space method is used for all passive methods, and the load parameter space is used for active type method. The power mismatch consists of both real and reactive power mismatches. As per IEEE-1547-2018, the real and reactive power mismatch limits are <15% and <2%, respectively, and the detection time is <2 secs. The NDZ mapping of real and reactive power mismatch is shown in Figure2.Figure 2
NDZ for phase angle difference islanding detection method.The calculated power mismatch limits for rated inverter of2.5kW+0.5kVAr are +0.3 kW and −0.25 kW for active power mismatch and +0.0015kVAr and −0.002 kVAr for reactive power.During testing, to have more deviations in frequency in islanded mode, a load with quality factor (Qf) 1.8 is selected for testing the performance indices and is given by
(15)Qf=ω0RC=Rω0L=RCL.In which(16)ω0=2πf0=1LC.The equation of (16) decides quality factor, which decides islanding detection criterion. The load reactive power is given by
(17)QLoad=Vrms21ωL−ωc=ΔQ.Equation (17) gives the load reactive power. The real power mismatch is given by
(18)ΔP==3V×I–3V+ΔV×I=−3V×ΔV×I.The voltage and frequency limits, as per IEEE-1547-2018, are1.1≤V≤0.8p.u. and for frequency is 58.8≤f≤61.2Hz/sec. Hence, the mismatch of reactive power is
(19)ΔQ=3V2ωnL1−ω2LC=3V2ωnL1−ωn2ωr2,whereωn is system frequency, and ωr is resonance frequency. In islanding, reactive power changes as per load frequency, which is
(20)ωr=1LC.Hence, the mismatch of reactive power is(21)ΔQ=3V2ωnL1−fn2fn±Δf2.The limits of frequency as per IEEE-1547-2018 is 49 to 51 Hz (for 50 Hz system frequency), and theΔf range is ±1 Hz.


## 3. MATLAB Model, Flowchart, and System Parameters for Phase Angle Difference Islanding Detection

### 3.1. MATLAB Model

The MATLAB model for the proposed detection technique is depicted in Figure3. The voltage and current are retrieved at the DG output first. Then, the phase angle between them is obtained through phasor measurement unit (PMU). It is then differentiated to get the proposed technique, to detect islanding condition. For ROCOF, the differential of voltage frequency is monitored at the output of PMU and differentiated to detect islanding. Both these methods are compared for performance indices as per UL-1741 testing in MATLAB/Simulink and found better with zero NDZ, lower detection time, and error detection ratio. There is no degradation in power quality as there are no injections.Figure 3
Phasor estimation scheme in MATLAB.


### 3.2. Flowchart for ROCPAD

The flowchart of phase angle difference method is shown in Figure4. The voltage and current oft DG output are extracted and differentiated to detect islanding. If the threshold value crosses, meaning end and the signal is utilized to isolate the microgrid from grid. If the variations are within threshold, it is nonislanding scenario, and the process is given to starting point.Figure 4
Flowchart of proposed phase angle difference method of islanding detection.


### 3.3. Flowchart for ROCOF

The process diagram for ROCOF is explained in Figure5. The voltage is retrieved at the output of DG and is given to PMU for obtaining the frequency. Then, the frequency is differentiated to get ROCOF to detect the islanding condition. If the variation exceeds the threshold value, command is utilized to island the microgrid from grid. Otherwise, it is nonislanding operation and the process starts from beginning. The process diagram of this method is depicted in Figure 6.Figure 5
ROCPAD islanding detection for 3 phase fault at 0% power mismatch.Figure 6
Process diagram for ROCOF.


### 3.4. System Parameters for Phase Angle Difference and ROCOF Methods

The schematic diagram for testing the phase angle difference method and ROCOF is depicted in Figure1, and the system parameters are given in Table 3. A 3 kW DG with interfacing inverter is connected to PCC. A 3 phase parallel RLC load is connected at PCC. The inverter input is 400VDC. The inverter output voltage is 415 VAC. The line resistance is 1.2 mΩ, and inductance is 1.5 mH. The normal grid frequency is 50 Hz. The inverter switching frequency is set to 8 kHz. The load parameters with a quality factor of 1.8 are RL=1.8mΩ, LL=3.1mH, and CL=3.1μF. The load resonant frequency is 50 Hz. Current controller gains are Kp=0.4 and Ki=400. The controller is of constant current mode to regulate active and reactive power at PCC. The synchronizing of DG to grid is done through phase locked loop (PLL). The PWM gets the feedback from PCC to regulate voltage, frequency, and power. This is a passive islanding detection method, which monitors local measurements only. The voltage and frequency are controlled by the grid and the power by inverter controller in grid mode. The European grid code limit for phase angle method is 175 deg/sec at 40 ms detection time, and the proposed method is well within this limit.Table 3
System parameters.
ComponentValue and unitsDG power3 kWSwitching frequency8 kHzDC input inverter600Line voltage415 VACFilter capacitanceCf2.2μFFilter inductanceLf5.5 mHDamping resistanceRf10 ohmsNominal frequency50 HzLoad resistanceRL1.8 m ΩLoad inductanceLL3.1 mHLoad capacitanceCL3.1μ FLoad quality factor (Q=RC/L)1.8Load resonant frequency (fr=1/2πLC)50 HzCurrent controller proportional gain,kp0.5Current controller integral gain,ki400


## 3.1. MATLAB Model

The MATLAB model for the proposed detection technique is depicted in Figure3. The voltage and current are retrieved at the DG output first. Then, the phase angle between them is obtained through phasor measurement unit (PMU). It is then differentiated to get the proposed technique, to detect islanding condition. For ROCOF, the differential of voltage frequency is monitored at the output of PMU and differentiated to detect islanding. Both these methods are compared for performance indices as per UL-1741 testing in MATLAB/Simulink and found better with zero NDZ, lower detection time, and error detection ratio. There is no degradation in power quality as there are no injections.Figure 3
Phasor estimation scheme in MATLAB.


## 3.2. Flowchart for ROCPAD

The flowchart of phase angle difference method is shown in Figure4. The voltage and current oft DG output are extracted and differentiated to detect islanding. If the threshold value crosses, meaning end and the signal is utilized to isolate the microgrid from grid. If the variations are within threshold, it is nonislanding scenario, and the process is given to starting point.Figure 4
Flowchart of proposed phase angle difference method of islanding detection.


## 3.3. Flowchart for ROCOF

The process diagram for ROCOF is explained in Figure5. The voltage is retrieved at the output of DG and is given to PMU for obtaining the frequency. Then, the frequency is differentiated to get ROCOF to detect the islanding condition. If the variation exceeds the threshold value, command is utilized to island the microgrid from grid. Otherwise, it is nonislanding operation and the process starts from beginning. The process diagram of this method is depicted in Figure 6.Figure 5
ROCPAD islanding detection for 3 phase fault at 0% power mismatch.Figure 6
Process diagram for ROCOF.


## 3.4. System Parameters for Phase Angle Difference and ROCOF Methods

The schematic diagram for testing the phase angle difference method and ROCOF is depicted in Figure1, and the system parameters are given in Table 3. A 3 kW DG with interfacing inverter is connected to PCC. A 3 phase parallel RLC load is connected at PCC. The inverter input is 400VDC. The inverter output voltage is 415 VAC. The line resistance is 1.2 mΩ, and inductance is 1.5 mH. The normal grid frequency is 50 Hz. The inverter switching frequency is set to 8 kHz. The load parameters with a quality factor of 1.8 are RL=1.8mΩ, LL=3.1mH, and CL=3.1μF. The load resonant frequency is 50 Hz. Current controller gains are Kp=0.4 and Ki=400. The controller is of constant current mode to regulate active and reactive power at PCC. The synchronizing of DG to grid is done through phase locked loop (PLL). The PWM gets the feedback from PCC to regulate voltage, frequency, and power. This is a passive islanding detection method, which monitors local measurements only. The voltage and frequency are controlled by the grid and the power by inverter controller in grid mode. The European grid code limit for phase angle method is 175 deg/sec at 40 ms detection time, and the proposed method is well within this limit.Table 3
System parameters.
ComponentValue and unitsDG power3 kWSwitching frequency8 kHzDC input inverter600Line voltage415 VACFilter capacitanceCf2.2μFFilter inductanceLf5.5 mHDamping resistanceRf10 ohmsNominal frequency50 HzLoad resistanceRL1.8 m ΩLoad inductanceLL3.1 mHLoad capacitanceCL3.1μ FLoad quality factor (Q=RC/L)1.8Load resonant frequency (fr=1/2πLC)50 HzCurrent controller proportional gain,kp0.5Current controller integral gain,ki400


## 4. Result Analysis and Discussion

### 4.1. Islanding Detection

In this paper, islanding detection of phase angle difference method proposed is tested by simulating unintentional symmetrical faults with fault resistanceRf=1Ω and ground resistance of Rg=0.1Ω in MATLAB. The simulation results are shown and discussed in Section 4.1.1. The proposed passive method is evaluated with widely used frequency method with performance indices in MATLAB.


#### 4.1.1. Islanding Detection of L-L-L Fault (3 Phase Fault)

This proposed passive method depends on the variation of rate of change of phase angle difference between voltage and current during islanding. A 3 phase fault (L-L-L) is initiated at 0.6 secs at 0% active power mismatch on a sampling time of 1 secs in MATLAB during grid connected mode. The proposed phase angle difference method detected islanding, in 20 milliseconds within a threshold of 150 deg/sec, which is shown in Figure5. The real time islanding detection time is 0.02relaytime+0.1breakertime, which is 0.12 secs.This passive islanding detection method ROCOF, which is to compare with the proposed one, depends on the differential of frequency. A 3 phase fault (L-L-L) is initiated at 0.6 secs on a sampling time of 1 secs at 0% active power mismatch in MATLAB, on the integrated microgrid during grid mode. This islanding detection method detected islanding within 80 milliseconds in a threshold value of 0.02 Hz/sec, which is depicted in Figure7.Figure 7
ROCOF islanding detection for 3 phase fault at 0% power mismatch.


#### 4.1.2. Islanding Detection of L-L-L-G Fault (3 Phase to Ground Fault)

This passive method depends on the variation of differential of phase angle between voltage and current during islanding. A 3 phase fault (L-L-L-G) is initiated at 0.6 secs at 0% power mismatch on a sampling time of 1 secs, in MATLAB, on integrated microgrid during grid mode. This sensed the islanding in 20 milliseconds with threshold of 150 deg/sec, which is shown in Figure8.Figure 8
ROCPAD islanding detection for 3 phase to ground fault at 0% power mismatch.ROCOF method depends on the variation of rate of change of frequency. A 3 phase to ground fault (L-L-L-G) is initiated at 0.6 secs on a sampling time of 1 secs at 0% power mismatch in MATLAB, on integrated microgrid during grid mode. The method detected islanding in 80 milliseconds with threshold value of 0.02 Hz/sec, which is depicted in Figure9.Figure 9
ROCOF islanding detection for 3 phase to ground fault 0% power mismatch.


### 4.2. Nonislanding Operation

In this section, the nonislanding condition of transient operation of the proposed method and rate of change of frequency method are tested for stability indices of error detection ratio for loads switching on and throwing off. The loads used for testing are linear, nonlinear, and capacitive type, in MATLAB as per testing standards of UL-1741.


#### 4.2.1. Transient Operation with Linear Load

The nonislanding operation of phase angle difference technique is tested by switching on and throwing off, a linear load equal to 3 kW at 0.4 secs and 0.8 secs, respectively, on a sampling time of 1 secs, in MATLAB, on the system at PCC during grid mode. The phase angle difference method is stable for transient operation without crossing threshold of 150 deg/sec. The simulation result is shown in Figure10.Figure 10
ROCPAD nonislanding operation for linear load switching on and throwing off.The nonislanding operation of differential frequency method is tested by switching on and throwing off, a linear load equal to 3 kW at 0.4 secs and 0.8 secs, respectively, on a sampling time of 1 secs, in MATLAB, on the integrated microgrid during grid mode. The differential frequency technique is stable without nuisance tripping, as the limit is set at 0.02 Hz/sec. The simulation result is shown in Figure11.Figure 11
ROCOF nonislanding operation for transient operation of linear load.


#### 4.2.2. Transient Operation with Nonlinear Load

The nonislanding operation of phase angle difference technique is tested by switching on and throwing off, a nonlinear load equal to 1 kW, 2 kVAr (inductive) at 0.4 secs and 0.8 secs, respectively, on a sampling time of 1 secs, in MATLAB, on the integrated microgrid during grid mode. The technique is stable during transient operation, as the threshold is set at 150 deg/sec. The simulation result is shown in Figure12.Figure 12
ROCPAD nonislanding operation for transient operation.The nonislanding operation of ROCOF method is tested by switching on and throwing off, a nonlinear load equal to 1 kW, 2 kVAr (inductive) at 0.4 secs and 0.8 secs, respectively, on a sampling time of 1 secs, in MATLAB, on the system in grid connected mode. This technique is stable for transient operation, as the limit is set at 0.02 Hz/sec. The simulation result is shown in Figure13.Figure 13
ROCOF transient operation for nonlinear load.


#### 4.2.3. Transient Operation with Capacitive Load

The nonislanding operation of phase angle difference technique is tested by switching on and throwing off, a capacitive load equal to 1 kW, 2 kVAr (capacitive) at 0.4 secs and 0.8 secs, respectively, on a sampling time of 1 secs, in MATLAB, on the system in grid connected mode. This technique is stable for the transient operation as the threshold is set at 150 deg/sec. The simulation result is shown in Figure14.Figure 14
ROCPAD transient operation for capacitive load.The nonislanding operation of rate of change frequency method is tested by switching on and throwing off, a linear load equal to 1 kW, 2 kVAr (capacitive) at 0.4 secs and 0.8 secs, respectively, on a sampling time of 1 secs, in MATLAB, on the system in grid connected mode. This technique is stable for transient operation as the limit is set to 0.02 Hz/sec. The simulation result is shown in Figure15.Figure 15
ROCOF transient operation for capacitive load.


### 4.3. Performance Evaluation of Islanding Detection Methods at Different Power Mismatch Space

The evaluation of the phase angle technique and differential frequency technique is done for active and reactive power mismatch in MATLAB by initiating a L-L-L-G fault at 0.6 secs on a sample time of 1 secs. The simulations are done for both the methods at 10%, 15%, and 20% active power mismatches as 0% power mismatch is already done in Section4.1. The results are discussed in the following sections.


#### 4.3.1. Fault Detection Performance at Different % Active Power Mismatches

The islanding performance of ROCPAD and ROCOF is tested for detection time at 10%, 15%, and 20% active power mismatches, in this section.(1) Islanding Detection of ROCPAD at 10% Active Power Mismatch. A L-L-L-G fault is initiated on 0.6 secs at 10% active power mismatch in MATLAB on a sampling time of 1 secs and phase angle difference method detected islanding in 20 ms within a threshold value of 150 deg/sec. But, the detection time is same as of at 0% power mismatch. The simulation result is depicted in Figure 16.Figure 16
ROCPAD islanding detection for 3 phase to ground fault at 10% real power mismatch.(2) Islanding Detection of ROCOF at 10% Active Power Mismatch. A 3 phase to ground fault is initiated on 0.6 secs at 10% active power mismatch in MATLAB on a sampling time of 1 secs and rate of change of frequency method detected islanding in 75 ms within a threshold value of 0.02 Hz/sec. But, the detection time is reduced as against 0% active power mismatch, which is 80 ms. The simulation result is depicted in Figure 17.Figure 17
ROCOF islanding detection for 3 phase to ground fault at 10% real power mismatch.(3) Islanding Detection of ROCPAD at 15% Active Power Mismatch. A 3 phase to ground fault is initiated on 0.6 secs at 15% active power mismatch in MATLAB on a sampling time of 1 secs and phase angle difference method detected islanding in 20 ms within a threshold value of 150 deg/sec. But, the detection time is same as of at 0% real power mismatch. The simulation result is shown in Figure 18.Figure 18
ROCPAD islanding detection for 3 phase to ground fault at 15% real power mismatch.(4) Islanding Detection of ROCOF at 15% Active Power Mismatch. A 3 phase to ground fault is initiated on 0.6 secs at 15% active power mismatch in MATLAB on a sampling time of 1 secs and rate of change of frequency method detected islanding in 70 ms within a threshold value of 0.02 Hz/sec. But, the detection time is reduced to 70 ms as against 10% active power mismatch, which is 75 ms. The simulation result is depicted in Figure 19.Figure 19
ROCOF islanding detection for 3 phase to ground fault at 15% real power mismatch.(5) Islanding Detection of ROCPAD at 20% Active Power Mismatch. A 3 phase to ground fault is initiated on 0.6 secs at 20% active power mismatch in MATLAB on a sampling time of 1 secs and phase angle difference method detected islanding in 20 ms within a threshold value of 150 deg/sec. But, the detection time is same as of at 0% real power mismatch. The simulation result is shown Figure 20.Figure 20
ROCPAD islanding detection for 3 phase to ground fault at 20% real power mismatch.(6) Islanding Detection of ROCOF at 20% Active Power Mismatch. A 3 phase to ground fault is initiated on 0.6 secs at 20% active power mismatch in MATLAB on a sampling time of 1 secs and the rate of change of frequency method detected islanding in 650 ms within a threshold value of 0.02 Hz/sec. But, the detection time is reduced to 65 ms as against 15% active power mismatch, which is 70 ms. The simulation result is depicted in Figure 21.Figure 21
ROCOF islanding detection for 3 phase to ground fault at 20% real power mismatch.(7) Tabulations for Real Power Mismatch. The tabulations of simulation results of % real power mismatch vs. phase difference and ROCOF methods are shown in Table 4.Table 4
Real power mismatch vs. detection time for ROCPAD and ROCOF.
% mismatch real powerTime ROCPAD (ms)Time ROCOF (ms)0%208010%207515%207020%2065(8) Graph for % Real Power Mismatch vs. Detection Time. The graph of Figure 22 clearly indicates that the detection time of ROCPAD is same at all % active power mismatches. But the detection time of ROCOF is being reduced as % active power mismatch is increasing. This concludes that ROCPAD is efficient at all power mismatches but ROCOF is more efficient at higher power mismatches.Figure 22
Graph of % active power mismatch vs. detection time.


#### 4.3.2. Islanding Performance at Different Reactive Power Mismatches

The islanding performance of ROCPAD and ROCOF is tested for detection time at 10%, 15%, and 20% active power mismatches, in this section.(1) Islanding Detection of ROCPAD at 10% Reactive Power Mismatch. A L-L-L-G fault is initiated on 0.6 secs at 10% reactive power mismatch in MATLAB on a sampling time of 1 secs and phase angle difference method detected islanding in 20 ms within a threshold value of 150 deg/sec. But, the detection time is same as of at 0% real power mismatch. The simulation result is depicted in Figure 23.Figure 23
ROCPAD islanding detection for 3 phase to ground fault at 10% reactive power mismatch.(2) Islanding Detection of ROCOF at 10% Reactive Power Mismatch. A 3 phase to ground fault is initiated on 0.6 secs at 10% reactive power mismatch in MATLAB on a sampling time of 1 secs and rate of change of frequency method detected islanding in 75 ms within a threshold value of 0.02 Hz/sec. But, the detection time is reduced as against 0%power mismatch, which is 80 ms. The simulation result is depicted in Figure 24.Figure 24
ROCOF islanding detection for 3 phase to ground fault at 10% reactive power mismatch.(3) Islanding Detection of ROCPAD at 15% Reactive Power Mismatch. A L-L-L-G fault is initiated on 0.6 secs at 15% reactive power mismatch in MATLAB on a sampling time of 1 secs and phase angle difference method detected islanding in 20 ms within a threshold value of 150 deg/sec. But, the detection time is same as of at 0% reactive power mismatch. The MATAB simulations are depicted in Figure 25.Figure 25
ROCPAD islanding detection for 3 phase to ground fault at 15% reactive power mismatch.(4) Islanding Detection of ROCOF at 15% Reactive Power Mismatch. A 3 phase to ground fault is initiated on 0.6 secs at 15% active power mismatch in MATLAB on a sampling time of 1 secs and rate of change of frequency method detected islanding in 70 ms within a threshold value of 0.02 Hz/sec. But, the detection time is reduced to 70 ms as against 10% reactive power mismatch, which is 75 ms. The MATLAB result is depicted in Figure 26.Figure 26
ROCOF islanding detection for 3 phase to ground fault at 15% reactive power mismatch.(5) Islanding Detection of ROCPAD at 20% Reactive Power Mismatch. A 3 phase to ground fault is initiated on 0.6 secs at 20% reactive power mismatch in MATLAB on a sampling time of 1 secs and phase angle difference method detected islanding in 20 ms within a threshold value of 150 deg/sec. But, the detection time is same as of at 0% reactive power mismatch. The MATLAB simulation is shown in Figure 27.Figure 27
ROCPAD islanding detection for 3 phase to ground fault at 20% reactive power mismatch.(6) Islanding Detection of ROCOF at 20% Reactive Power Mismatch. A 3 phase to ground fault is initiated on 0.6 secs at 20% imaginary power mismatch in MATLAB on a sampling time of 1 secs and rate of change of frequency method detected islanding in 70 ms within a threshold value of 0.02 Hz/sec. But, ROCOF detected in 65 ms as against in case of 20% reactive power mismatch, which is 70 ms. The simulation result is depicted in Figure 28.Figure 28
ROCOF islanding detection for 3 phase to ground fault at 20% reactive power mismatch.(7) Tabulations for Reactive Power Mismatch. The tabulations of simulation results of % reactive power mismatch vs. phase angle difference and ROCOF methods are shown in Table 5. The reactive power vs. detection time graph is shown in Figure 29.Table 5
Reactive power mismatch vs. detection time for ROCPAD and ROCOF.
% mismatch reactive powerTime ROCPAD (ms)Time ROCOF (ms)0%208010%207515%207020%2065Figure 29
Graph of % reactive power mismatch vs. detection time.(8) Graph for % Real Power Mismatch vs. Detection Time. The graph of Figure 29 clearly indicates that the detection time of ROCPAD is same at all % reactive power mismatches. But the detection time of ROCOF is being reduced as % reactive power mismatch is increasing. This concludes that ROCPAD is efficient at all power mismatches but ROCOF is more efficient at higher power mismatches only.


#### 4.3.3. Summary of Total Work

The summary of the total work is depicted in Table6, which consists of performance indices, like NDZ, detection time, and error detection ratio.Table 6
Simulation results of ROCPAD and ROCOF islanding detection methods.
(a)MethodFault typeThreshold valueDetection time in millisecondsDetection time in millisecondsAt 0% active power mismatchAt 10% active power mismatchAt 15% active power mismatchAt 20% active power mismatchAt 0% reactive power mismatchAt 10% reactive power mismatchAt 15% reactive power mismatchAt 20% reactive power mismatchIslanding detection:ROCPADL-L-L and L-L-L-G150 deg/sec2020202020202020ROCOFL-L-L and L-L-L-G0.02 Hz/sec8075706580757065(b)MethodLoad typeSwitch on at (secs)Throw off at (secs)StatusNonislanding operation:ROCPADLinear, nonlinear, and capacitive0.40.8Stable without nuisance trippingROCOFLinear, nonlinear, and capacitive0.40.8Stable without nuisance tripping


## 4.1. Islanding Detection

In this paper, islanding detection of phase angle difference method proposed is tested by simulating unintentional symmetrical faults with fault resistanceRf=1Ω and ground resistance of Rg=0.1Ω in MATLAB. The simulation results are shown and discussed in Section 4.1.1. The proposed passive method is evaluated with widely used frequency method with performance indices in MATLAB.


### 4.1.1. Islanding Detection of L-L-L Fault (3 Phase Fault)

This proposed passive method depends on the variation of rate of change of phase angle difference between voltage and current during islanding. A 3 phase fault (L-L-L) is initiated at 0.6 secs at 0% active power mismatch on a sampling time of 1 secs in MATLAB during grid connected mode. The proposed phase angle difference method detected islanding, in 20 milliseconds within a threshold of 150 deg/sec, which is shown in Figure5. The real time islanding detection time is 0.02relaytime+0.1breakertime, which is 0.12 secs.This passive islanding detection method ROCOF, which is to compare with the proposed one, depends on the differential of frequency. A 3 phase fault (L-L-L) is initiated at 0.6 secs on a sampling time of 1 secs at 0% active power mismatch in MATLAB, on the integrated microgrid during grid mode. This islanding detection method detected islanding within 80 milliseconds in a threshold value of 0.02 Hz/sec, which is depicted in Figure7.Figure 7
ROCOF islanding detection for 3 phase fault at 0% power mismatch.


### 4.1.2. Islanding Detection of L-L-L-G Fault (3 Phase to Ground Fault)

This passive method depends on the variation of differential of phase angle between voltage and current during islanding. A 3 phase fault (L-L-L-G) is initiated at 0.6 secs at 0% power mismatch on a sampling time of 1 secs, in MATLAB, on integrated microgrid during grid mode. This sensed the islanding in 20 milliseconds with threshold of 150 deg/sec, which is shown in Figure8.Figure 8
ROCPAD islanding detection for 3 phase to ground fault at 0% power mismatch.ROCOF method depends on the variation of rate of change of frequency. A 3 phase to ground fault (L-L-L-G) is initiated at 0.6 secs on a sampling time of 1 secs at 0% power mismatch in MATLAB, on integrated microgrid during grid mode. The method detected islanding in 80 milliseconds with threshold value of 0.02 Hz/sec, which is depicted in Figure9.Figure 9
ROCOF islanding detection for 3 phase to ground fault 0% power mismatch.


## 4.1.1. Islanding Detection of L-L-L Fault (3 Phase Fault)

This proposed passive method depends on the variation of rate of change of phase angle difference between voltage and current during islanding. A 3 phase fault (L-L-L) is initiated at 0.6 secs at 0% active power mismatch on a sampling time of 1 secs in MATLAB during grid connected mode. The proposed phase angle difference method detected islanding, in 20 milliseconds within a threshold of 150 deg/sec, which is shown in Figure5. The real time islanding detection time is 0.02relaytime+0.1breakertime, which is 0.12 secs.This passive islanding detection method ROCOF, which is to compare with the proposed one, depends on the differential of frequency. A 3 phase fault (L-L-L) is initiated at 0.6 secs on a sampling time of 1 secs at 0% active power mismatch in MATLAB, on the integrated microgrid during grid mode. This islanding detection method detected islanding within 80 milliseconds in a threshold value of 0.02 Hz/sec, which is depicted in Figure7.Figure 7
ROCOF islanding detection for 3 phase fault at 0% power mismatch.


## 4.1.2. Islanding Detection of L-L-L-G Fault (3 Phase to Ground Fault)

This passive method depends on the variation of differential of phase angle between voltage and current during islanding. A 3 phase fault (L-L-L-G) is initiated at 0.6 secs at 0% power mismatch on a sampling time of 1 secs, in MATLAB, on integrated microgrid during grid mode. This sensed the islanding in 20 milliseconds with threshold of 150 deg/sec, which is shown in Figure8.Figure 8
ROCPAD islanding detection for 3 phase to ground fault at 0% power mismatch.ROCOF method depends on the variation of rate of change of frequency. A 3 phase to ground fault (L-L-L-G) is initiated at 0.6 secs on a sampling time of 1 secs at 0% power mismatch in MATLAB, on integrated microgrid during grid mode. The method detected islanding in 80 milliseconds with threshold value of 0.02 Hz/sec, which is depicted in Figure9.Figure 9
ROCOF islanding detection for 3 phase to ground fault 0% power mismatch.


## 4.2. Nonislanding Operation

In this section, the nonislanding condition of transient operation of the proposed method and rate of change of frequency method are tested for stability indices of error detection ratio for loads switching on and throwing off. The loads used for testing are linear, nonlinear, and capacitive type, in MATLAB as per testing standards of UL-1741.


### 4.2.1. Transient Operation with Linear Load

The nonislanding operation of phase angle difference technique is tested by switching on and throwing off, a linear load equal to 3 kW at 0.4 secs and 0.8 secs, respectively, on a sampling time of 1 secs, in MATLAB, on the system at PCC during grid mode. The phase angle difference method is stable for transient operation without crossing threshold of 150 deg/sec. The simulation result is shown in Figure10.Figure 10
ROCPAD nonislanding operation for linear load switching on and throwing off.The nonislanding operation of differential frequency method is tested by switching on and throwing off, a linear load equal to 3 kW at 0.4 secs and 0.8 secs, respectively, on a sampling time of 1 secs, in MATLAB, on the integrated microgrid during grid mode. The differential frequency technique is stable without nuisance tripping, as the limit is set at 0.02 Hz/sec. The simulation result is shown in Figure11.Figure 11
ROCOF nonislanding operation for transient operation of linear load.


### 4.2.2. Transient Operation with Nonlinear Load

The nonislanding operation of phase angle difference technique is tested by switching on and throwing off, a nonlinear load equal to 1 kW, 2 kVAr (inductive) at 0.4 secs and 0.8 secs, respectively, on a sampling time of 1 secs, in MATLAB, on the integrated microgrid during grid mode. The technique is stable during transient operation, as the threshold is set at 150 deg/sec. The simulation result is shown in Figure12.Figure 12
ROCPAD nonislanding operation for transient operation.The nonislanding operation of ROCOF method is tested by switching on and throwing off, a nonlinear load equal to 1 kW, 2 kVAr (inductive) at 0.4 secs and 0.8 secs, respectively, on a sampling time of 1 secs, in MATLAB, on the system in grid connected mode. This technique is stable for transient operation, as the limit is set at 0.02 Hz/sec. The simulation result is shown in Figure13.Figure 13
ROCOF transient operation for nonlinear load.


### 4.2.3. Transient Operation with Capacitive Load

The nonislanding operation of phase angle difference technique is tested by switching on and throwing off, a capacitive load equal to 1 kW, 2 kVAr (capacitive) at 0.4 secs and 0.8 secs, respectively, on a sampling time of 1 secs, in MATLAB, on the system in grid connected mode. This technique is stable for the transient operation as the threshold is set at 150 deg/sec. The simulation result is shown in Figure14.Figure 14
ROCPAD transient operation for capacitive load.The nonislanding operation of rate of change frequency method is tested by switching on and throwing off, a linear load equal to 1 kW, 2 kVAr (capacitive) at 0.4 secs and 0.8 secs, respectively, on a sampling time of 1 secs, in MATLAB, on the system in grid connected mode. This technique is stable for transient operation as the limit is set to 0.02 Hz/sec. The simulation result is shown in Figure15.Figure 15
ROCOF transient operation for capacitive load.


## 4.2.1. Transient Operation with Linear Load

The nonislanding operation of phase angle difference technique is tested by switching on and throwing off, a linear load equal to 3 kW at 0.4 secs and 0.8 secs, respectively, on a sampling time of 1 secs, in MATLAB, on the system at PCC during grid mode. The phase angle difference method is stable for transient operation without crossing threshold of 150 deg/sec. The simulation result is shown in Figure10.Figure 10
ROCPAD nonislanding operation for linear load switching on and throwing off.The nonislanding operation of differential frequency method is tested by switching on and throwing off, a linear load equal to 3 kW at 0.4 secs and 0.8 secs, respectively, on a sampling time of 1 secs, in MATLAB, on the integrated microgrid during grid mode. The differential frequency technique is stable without nuisance tripping, as the limit is set at 0.02 Hz/sec. The simulation result is shown in Figure11.Figure 11
ROCOF nonislanding operation for transient operation of linear load.


## 4.2.2. Transient Operation with Nonlinear Load

The nonislanding operation of phase angle difference technique is tested by switching on and throwing off, a nonlinear load equal to 1 kW, 2 kVAr (inductive) at 0.4 secs and 0.8 secs, respectively, on a sampling time of 1 secs, in MATLAB, on the integrated microgrid during grid mode. The technique is stable during transient operation, as the threshold is set at 150 deg/sec. The simulation result is shown in Figure12.Figure 12
ROCPAD nonislanding operation for transient operation.The nonislanding operation of ROCOF method is tested by switching on and throwing off, a nonlinear load equal to 1 kW, 2 kVAr (inductive) at 0.4 secs and 0.8 secs, respectively, on a sampling time of 1 secs, in MATLAB, on the system in grid connected mode. This technique is stable for transient operation, as the limit is set at 0.02 Hz/sec. The simulation result is shown in Figure13.Figure 13
ROCOF transient operation for nonlinear load.


## 4.2.3. Transient Operation with Capacitive Load

The nonislanding operation of phase angle difference technique is tested by switching on and throwing off, a capacitive load equal to 1 kW, 2 kVAr (capacitive) at 0.4 secs and 0.8 secs, respectively, on a sampling time of 1 secs, in MATLAB, on the system in grid connected mode. This technique is stable for the transient operation as the threshold is set at 150 deg/sec. The simulation result is shown in Figure14.Figure 14
ROCPAD transient operation for capacitive load.The nonislanding operation of rate of change frequency method is tested by switching on and throwing off, a linear load equal to 1 kW, 2 kVAr (capacitive) at 0.4 secs and 0.8 secs, respectively, on a sampling time of 1 secs, in MATLAB, on the system in grid connected mode. This technique is stable for transient operation as the limit is set to 0.02 Hz/sec. The simulation result is shown in Figure15.Figure 15
ROCOF transient operation for capacitive load.


## 4.3. Performance Evaluation of Islanding Detection Methods at Different Power Mismatch Space

The evaluation of the phase angle technique and differential frequency technique is done for active and reactive power mismatch in MATLAB by initiating a L-L-L-G fault at 0.6 secs on a sample time of 1 secs. The simulations are done for both the methods at 10%, 15%, and 20% active power mismatches as 0% power mismatch is already done in Section4.1. The results are discussed in the following sections.


### 4.3.1. Fault Detection Performance at Different % Active Power Mismatches

The islanding performance of ROCPAD and ROCOF is tested for detection time at 10%, 15%, and 20% active power mismatches, in this section.(1) Islanding Detection of ROCPAD at 10% Active Power Mismatch. A L-L-L-G fault is initiated on 0.6 secs at 10% active power mismatch in MATLAB on a sampling time of 1 secs and phase angle difference method detected islanding in 20 ms within a threshold value of 150 deg/sec. But, the detection time is same as of at 0% power mismatch. The simulation result is depicted in Figure 16.Figure 16
ROCPAD islanding detection for 3 phase to ground fault at 10% real power mismatch.(2) Islanding Detection of ROCOF at 10% Active Power Mismatch. A 3 phase to ground fault is initiated on 0.6 secs at 10% active power mismatch in MATLAB on a sampling time of 1 secs and rate of change of frequency method detected islanding in 75 ms within a threshold value of 0.02 Hz/sec. But, the detection time is reduced as against 0% active power mismatch, which is 80 ms. The simulation result is depicted in Figure 17.Figure 17
ROCOF islanding detection for 3 phase to ground fault at 10% real power mismatch.(3) Islanding Detection of ROCPAD at 15% Active Power Mismatch. A 3 phase to ground fault is initiated on 0.6 secs at 15% active power mismatch in MATLAB on a sampling time of 1 secs and phase angle difference method detected islanding in 20 ms within a threshold value of 150 deg/sec. But, the detection time is same as of at 0% real power mismatch. The simulation result is shown in Figure 18.Figure 18
ROCPAD islanding detection for 3 phase to ground fault at 15% real power mismatch.(4) Islanding Detection of ROCOF at 15% Active Power Mismatch. A 3 phase to ground fault is initiated on 0.6 secs at 15% active power mismatch in MATLAB on a sampling time of 1 secs and rate of change of frequency method detected islanding in 70 ms within a threshold value of 0.02 Hz/sec. But, the detection time is reduced to 70 ms as against 10% active power mismatch, which is 75 ms. The simulation result is depicted in Figure 19.Figure 19
ROCOF islanding detection for 3 phase to ground fault at 15% real power mismatch.(5) Islanding Detection of ROCPAD at 20% Active Power Mismatch. A 3 phase to ground fault is initiated on 0.6 secs at 20% active power mismatch in MATLAB on a sampling time of 1 secs and phase angle difference method detected islanding in 20 ms within a threshold value of 150 deg/sec. But, the detection time is same as of at 0% real power mismatch. The simulation result is shown Figure 20.Figure 20
ROCPAD islanding detection for 3 phase to ground fault at 20% real power mismatch.(6) Islanding Detection of ROCOF at 20% Active Power Mismatch. A 3 phase to ground fault is initiated on 0.6 secs at 20% active power mismatch in MATLAB on a sampling time of 1 secs and the rate of change of frequency method detected islanding in 650 ms within a threshold value of 0.02 Hz/sec. But, the detection time is reduced to 65 ms as against 15% active power mismatch, which is 70 ms. The simulation result is depicted in Figure 21.Figure 21
ROCOF islanding detection for 3 phase to ground fault at 20% real power mismatch.(7) Tabulations for Real Power Mismatch. The tabulations of simulation results of % real power mismatch vs. phase difference and ROCOF methods are shown in Table 4.Table 4
Real power mismatch vs. detection time for ROCPAD and ROCOF.
% mismatch real powerTime ROCPAD (ms)Time ROCOF (ms)0%208010%207515%207020%2065(8) Graph for % Real Power Mismatch vs. Detection Time. The graph of Figure 22 clearly indicates that the detection time of ROCPAD is same at all % active power mismatches. But the detection time of ROCOF is being reduced as % active power mismatch is increasing. This concludes that ROCPAD is efficient at all power mismatches but ROCOF is more efficient at higher power mismatches.Figure 22
Graph of % active power mismatch vs. detection time.


### 4.3.2. Islanding Performance at Different Reactive Power Mismatches

The islanding performance of ROCPAD and ROCOF is tested for detection time at 10%, 15%, and 20% active power mismatches, in this section.(1) Islanding Detection of ROCPAD at 10% Reactive Power Mismatch. A L-L-L-G fault is initiated on 0.6 secs at 10% reactive power mismatch in MATLAB on a sampling time of 1 secs and phase angle difference method detected islanding in 20 ms within a threshold value of 150 deg/sec. But, the detection time is same as of at 0% real power mismatch. The simulation result is depicted in Figure 23.Figure 23
ROCPAD islanding detection for 3 phase to ground fault at 10% reactive power mismatch.(2) Islanding Detection of ROCOF at 10% Reactive Power Mismatch. A 3 phase to ground fault is initiated on 0.6 secs at 10% reactive power mismatch in MATLAB on a sampling time of 1 secs and rate of change of frequency method detected islanding in 75 ms within a threshold value of 0.02 Hz/sec. But, the detection time is reduced as against 0%power mismatch, which is 80 ms. The simulation result is depicted in Figure 24.Figure 24
ROCOF islanding detection for 3 phase to ground fault at 10% reactive power mismatch.(3) Islanding Detection of ROCPAD at 15% Reactive Power Mismatch. A L-L-L-G fault is initiated on 0.6 secs at 15% reactive power mismatch in MATLAB on a sampling time of 1 secs and phase angle difference method detected islanding in 20 ms within a threshold value of 150 deg/sec. But, the detection time is same as of at 0% reactive power mismatch. The MATAB simulations are depicted in Figure 25.Figure 25
ROCPAD islanding detection for 3 phase to ground fault at 15% reactive power mismatch.(4) Islanding Detection of ROCOF at 15% Reactive Power Mismatch. A 3 phase to ground fault is initiated on 0.6 secs at 15% active power mismatch in MATLAB on a sampling time of 1 secs and rate of change of frequency method detected islanding in 70 ms within a threshold value of 0.02 Hz/sec. But, the detection time is reduced to 70 ms as against 10% reactive power mismatch, which is 75 ms. The MATLAB result is depicted in Figure 26.Figure 26
ROCOF islanding detection for 3 phase to ground fault at 15% reactive power mismatch.(5) Islanding Detection of ROCPAD at 20% Reactive Power Mismatch. A 3 phase to ground fault is initiated on 0.6 secs at 20% reactive power mismatch in MATLAB on a sampling time of 1 secs and phase angle difference method detected islanding in 20 ms within a threshold value of 150 deg/sec. But, the detection time is same as of at 0% reactive power mismatch. The MATLAB simulation is shown in Figure 27.Figure 27
ROCPAD islanding detection for 3 phase to ground fault at 20% reactive power mismatch.(6) Islanding Detection of ROCOF at 20% Reactive Power Mismatch. A 3 phase to ground fault is initiated on 0.6 secs at 20% imaginary power mismatch in MATLAB on a sampling time of 1 secs and rate of change of frequency method detected islanding in 70 ms within a threshold value of 0.02 Hz/sec. But, ROCOF detected in 65 ms as against in case of 20% reactive power mismatch, which is 70 ms. The simulation result is depicted in Figure 28.Figure 28
ROCOF islanding detection for 3 phase to ground fault at 20% reactive power mismatch.(7) Tabulations for Reactive Power Mismatch. The tabulations of simulation results of % reactive power mismatch vs. phase angle difference and ROCOF methods are shown in Table 5. The reactive power vs. detection time graph is shown in Figure 29.Table 5
Reactive power mismatch vs. detection time for ROCPAD and ROCOF.
% mismatch reactive powerTime ROCPAD (ms)Time ROCOF (ms)0%208010%207515%207020%2065Figure 29
Graph of % reactive power mismatch vs. detection time.(8) Graph for % Real Power Mismatch vs. Detection Time. The graph of Figure 29 clearly indicates that the detection time of ROCPAD is same at all % reactive power mismatches. But the detection time of ROCOF is being reduced as % reactive power mismatch is increasing. This concludes that ROCPAD is efficient at all power mismatches but ROCOF is more efficient at higher power mismatches only.


### 4.3.3. Summary of Total Work

The summary of the total work is depicted in Table6, which consists of performance indices, like NDZ, detection time, and error detection ratio.Table 6
Simulation results of ROCPAD and ROCOF islanding detection methods.
(a)MethodFault typeThreshold valueDetection time in millisecondsDetection time in millisecondsAt 0% active power mismatchAt 10% active power mismatchAt 15% active power mismatchAt 20% active power mismatchAt 0% reactive power mismatchAt 10% reactive power mismatchAt 15% reactive power mismatchAt 20% reactive power mismatchIslanding detection:ROCPADL-L-L and L-L-L-G150 deg/sec2020202020202020ROCOFL-L-L and L-L-L-G0.02 Hz/sec8075706580757065(b)MethodLoad typeSwitch on at (secs)Throw off at (secs)StatusNonislanding operation:ROCPADLinear, nonlinear, and capacitive0.40.8Stable without nuisance trippingROCOFLinear, nonlinear, and capacitive0.40.8Stable without nuisance tripping


## 4.3.1. Fault Detection Performance at Different % Active Power Mismatches

The islanding performance of ROCPAD and ROCOF is tested for detection time at 10%, 15%, and 20% active power mismatches, in this section.(1) Islanding Detection of ROCPAD at 10% Active Power Mismatch. A L-L-L-G fault is initiated on 0.6 secs at 10% active power mismatch in MATLAB on a sampling time of 1 secs and phase angle difference method detected islanding in 20 ms within a threshold value of 150 deg/sec. But, the detection time is same as of at 0% power mismatch. The simulation result is depicted in Figure 16.Figure 16
ROCPAD islanding detection for 3 phase to ground fault at 10% real power mismatch.(2) Islanding Detection of ROCOF at 10% Active Power Mismatch. A 3 phase to ground fault is initiated on 0.6 secs at 10% active power mismatch in MATLAB on a sampling time of 1 secs and rate of change of frequency method detected islanding in 75 ms within a threshold value of 0.02 Hz/sec. But, the detection time is reduced as against 0% active power mismatch, which is 80 ms. The simulation result is depicted in Figure 17.Figure 17
ROCOF islanding detection for 3 phase to ground fault at 10% real power mismatch.(3) Islanding Detection of ROCPAD at 15% Active Power Mismatch. A 3 phase to ground fault is initiated on 0.6 secs at 15% active power mismatch in MATLAB on a sampling time of 1 secs and phase angle difference method detected islanding in 20 ms within a threshold value of 150 deg/sec. But, the detection time is same as of at 0% real power mismatch. The simulation result is shown in Figure 18.Figure 18
ROCPAD islanding detection for 3 phase to ground fault at 15% real power mismatch.(4) Islanding Detection of ROCOF at 15% Active Power Mismatch. A 3 phase to ground fault is initiated on 0.6 secs at 15% active power mismatch in MATLAB on a sampling time of 1 secs and rate of change of frequency method detected islanding in 70 ms within a threshold value of 0.02 Hz/sec. But, the detection time is reduced to 70 ms as against 10% active power mismatch, which is 75 ms. The simulation result is depicted in Figure 19.Figure 19
ROCOF islanding detection for 3 phase to ground fault at 15% real power mismatch.(5) Islanding Detection of ROCPAD at 20% Active Power Mismatch. A 3 phase to ground fault is initiated on 0.6 secs at 20% active power mismatch in MATLAB on a sampling time of 1 secs and phase angle difference method detected islanding in 20 ms within a threshold value of 150 deg/sec. But, the detection time is same as of at 0% real power mismatch. The simulation result is shown Figure 20.Figure 20
ROCPAD islanding detection for 3 phase to ground fault at 20% real power mismatch.(6) Islanding Detection of ROCOF at 20% Active Power Mismatch. A 3 phase to ground fault is initiated on 0.6 secs at 20% active power mismatch in MATLAB on a sampling time of 1 secs and the rate of change of frequency method detected islanding in 650 ms within a threshold value of 0.02 Hz/sec. But, the detection time is reduced to 65 ms as against 15% active power mismatch, which is 70 ms. The simulation result is depicted in Figure 21.Figure 21
ROCOF islanding detection for 3 phase to ground fault at 20% real power mismatch.(7) Tabulations for Real Power Mismatch. The tabulations of simulation results of % real power mismatch vs. phase difference and ROCOF methods are shown in Table 4.Table 4
Real power mismatch vs. detection time for ROCPAD and ROCOF.
% mismatch real powerTime ROCPAD (ms)Time ROCOF (ms)0%208010%207515%207020%2065(8) Graph for % Real Power Mismatch vs. Detection Time. The graph of Figure 22 clearly indicates that the detection time of ROCPAD is same at all % active power mismatches. But the detection time of ROCOF is being reduced as % active power mismatch is increasing. This concludes that ROCPAD is efficient at all power mismatches but ROCOF is more efficient at higher power mismatches.Figure 22
Graph of % active power mismatch vs. detection time.


## 4.3.2. Islanding Performance at Different Reactive Power Mismatches

The islanding performance of ROCPAD and ROCOF is tested for detection time at 10%, 15%, and 20% active power mismatches, in this section.(1) Islanding Detection of ROCPAD at 10% Reactive Power Mismatch. A L-L-L-G fault is initiated on 0.6 secs at 10% reactive power mismatch in MATLAB on a sampling time of 1 secs and phase angle difference method detected islanding in 20 ms within a threshold value of 150 deg/sec. But, the detection time is same as of at 0% real power mismatch. The simulation result is depicted in Figure 23.Figure 23
ROCPAD islanding detection for 3 phase to ground fault at 10% reactive power mismatch.(2) Islanding Detection of ROCOF at 10% Reactive Power Mismatch. A 3 phase to ground fault is initiated on 0.6 secs at 10% reactive power mismatch in MATLAB on a sampling time of 1 secs and rate of change of frequency method detected islanding in 75 ms within a threshold value of 0.02 Hz/sec. But, the detection time is reduced as against 0%power mismatch, which is 80 ms. The simulation result is depicted in Figure 24.Figure 24
ROCOF islanding detection for 3 phase to ground fault at 10% reactive power mismatch.(3) Islanding Detection of ROCPAD at 15% Reactive Power Mismatch. A L-L-L-G fault is initiated on 0.6 secs at 15% reactive power mismatch in MATLAB on a sampling time of 1 secs and phase angle difference method detected islanding in 20 ms within a threshold value of 150 deg/sec. But, the detection time is same as of at 0% reactive power mismatch. The MATAB simulations are depicted in Figure 25.Figure 25
ROCPAD islanding detection for 3 phase to ground fault at 15% reactive power mismatch.(4) Islanding Detection of ROCOF at 15% Reactive Power Mismatch. A 3 phase to ground fault is initiated on 0.6 secs at 15% active power mismatch in MATLAB on a sampling time of 1 secs and rate of change of frequency method detected islanding in 70 ms within a threshold value of 0.02 Hz/sec. But, the detection time is reduced to 70 ms as against 10% reactive power mismatch, which is 75 ms. The MATLAB result is depicted in Figure 26.Figure 26
ROCOF islanding detection for 3 phase to ground fault at 15% reactive power mismatch.(5) Islanding Detection of ROCPAD at 20% Reactive Power Mismatch. A 3 phase to ground fault is initiated on 0.6 secs at 20% reactive power mismatch in MATLAB on a sampling time of 1 secs and phase angle difference method detected islanding in 20 ms within a threshold value of 150 deg/sec. But, the detection time is same as of at 0% reactive power mismatch. The MATLAB simulation is shown in Figure 27.Figure 27
ROCPAD islanding detection for 3 phase to ground fault at 20% reactive power mismatch.(6) Islanding Detection of ROCOF at 20% Reactive Power Mismatch. A 3 phase to ground fault is initiated on 0.6 secs at 20% imaginary power mismatch in MATLAB on a sampling time of 1 secs and rate of change of frequency method detected islanding in 70 ms within a threshold value of 0.02 Hz/sec. But, ROCOF detected in 65 ms as against in case of 20% reactive power mismatch, which is 70 ms. The simulation result is depicted in Figure 28.Figure 28
ROCOF islanding detection for 3 phase to ground fault at 20% reactive power mismatch.(7) Tabulations for Reactive Power Mismatch. The tabulations of simulation results of % reactive power mismatch vs. phase angle difference and ROCOF methods are shown in Table 5. The reactive power vs. detection time graph is shown in Figure 29.Table 5
Reactive power mismatch vs. detection time for ROCPAD and ROCOF.
% mismatch reactive powerTime ROCPAD (ms)Time ROCOF (ms)0%208010%207515%207020%2065Figure 29
Graph of % reactive power mismatch vs. detection time.(8) Graph for % Real Power Mismatch vs. Detection Time. The graph of Figure 29 clearly indicates that the detection time of ROCPAD is same at all % reactive power mismatches. But the detection time of ROCOF is being reduced as % reactive power mismatch is increasing. This concludes that ROCPAD is efficient at all power mismatches but ROCOF is more efficient at higher power mismatches only.


## 4.3.3. Summary of Total Work

The summary of the total work is depicted in Table6, which consists of performance indices, like NDZ, detection time, and error detection ratio.Table 6
Simulation results of ROCPAD and ROCOF islanding detection methods.
(a)MethodFault typeThreshold valueDetection time in millisecondsDetection time in millisecondsAt 0% active power mismatchAt 10% active power mismatchAt 15% active power mismatchAt 20% active power mismatchAt 0% reactive power mismatchAt 10% reactive power mismatchAt 15% reactive power mismatchAt 20% reactive power mismatchIslanding detection:ROCPADL-L-L and L-L-L-G150 deg/sec2020202020202020ROCOFL-L-L and L-L-L-G0.02 Hz/sec8075706580757065(b)MethodLoad typeSwitch on at (secs)Throw off at (secs)StatusNonislanding operation:ROCPADLinear, nonlinear, and capacitive0.40.8Stable without nuisance trippingROCOFLinear, nonlinear, and capacitive0.40.8Stable without nuisance tripping


## 5. Conclusion

Islanding detection is an important operational activity. It is mandatory as per IEEE-1547-2018 standards; the microgrid has to be isolated from main grid seamlessly within 2 secs for any unintentional fault on the system. In this process, the islanding detection techniques attained very high significance. The islanding methods classified as of now, are passive, active, hybrid, and remote techniques. The various detection techniques have been discussed elaborately. The proposed phase angle difference method is compared with ROCOF method and has been tested for various fault conditions and transient cases as per UL-1741 in MATLAB. It is proved that the proposed technique works effectively at almost zero NDZ. The response time of ROCPAD is very less, which is 20 ms, showing fastness of the proposed algorithm in comparison with ROCOF method. The proposed method ROCPAD is efficient at all power mismatches, unlike ROCOF method, which is efficient at higher power mismatches only. The implementation is easy, and there is no power quality issue because of no external injections in the system. It is also safe, faster, and secure for integrated microgrid operations. The detection time is very less, and it also avoids nuisance tripping. The ROCPAD method is evaluated as per standards of UL-1741 testing. The methodology has been evaluated for performance indices in MATLAB/Simulink platform and found to be operating successfully for the designed environment. The future research work is proposed to use this method for testing the islanding with multiple DGs and with adoptive controller to feed the loads in islanded mode. The method also can be tested in other platforms like, OPAL-RT, Digi-silent, and C-HIL.



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*Source: 2275191-2023-03-03.xml*