A new islanding detection technique based on rate of change of reactive power and radial basis function neural network for distributed generation

Chandio, Asad Ali; Laghari, J. A.; Khokhar, Suhail; Almani, Suhail Ahmed

doi:10.3233/jifs-181849

Cited by 7 publications

(5 citation statements)

References 37 publications

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“…The interval type-2 fuzzy logic system (IT2FLS) consists of two type-1 membership functions, and the distance between these two membership functions indicates uncertainty [ 7 ]. As shown in Fig 2 , a IT2FLS is described similar to a type-1 fuzzy system using a series of if-then rules, except for the type-2 fuzzy sets use a range (this can be a fuzzy set) in their membership functions, instead of employing a number for defining the degree of membership.…”

Section: Type-2 Fuzzy Systemmentioning

confidence: 99%

“…Local detection methods can be categorized into passive, active, hybrid, and intelligent methods, which operate by measuring SG parameters, such as voltage, current, frequency, and harmonic distortion on the microgrid side [ 5 ]. Passive methods include under/overvoltage relays (UVR/OVR), under/over-frequency relays (UFR/OFR) [ 5 ], rate of change of frequency (ROCOF) [ 6 ], methods based on rate of change of active power (ROCOAP) and rate of change of reactive power (ROCORP) [ 7 ], a technique based on two criteria of transient index value (TIV) and positive sequence of current angle at common connection point [ 8 ], detection methods using signal processing techniques [ 9 ], methods based on unbalance voltage (UV) [ 2 ], methods based on total harmonic distortion (THD) [ 10 ], and methods based on differential transient rate of change of frequency (DTROCOF) [ 11 ].…”

Section: Introductionmentioning

confidence: 99%

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Real-time detection of microgrid islanding considering sources of uncertainty using type-2 fuzzy logic and PSO algorithm

Khonakdari

Kamarposhti

2021

PLoS ONE

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In this paper, a new innovative type-2 fuzzy-based for microgrid (MG) islanding detection is proposed in the condition of uncertainties. Load and generation uncertainties are two main sources of uncertainties in microgrids (MGs). Regardless of the uncertainties, the results cannot be confirmed. The proposed controller detects islanding in the fastest time under different conditions, and the uncertainties in the system will not considerably affect the controller’s performance. The proposed method is simulated on the sample system and examined in different scenarios. Then, a comparison is made in different conditions and scenarios between the suggested method and some common methods that have been presented so far to demonstrate the ability of the proposed method for islanding detection.

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Section: Type-2 Fuzzy Systemmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Real-time detection of microgrid islanding considering sources of uncertainty using type-2 fuzzy logic and PSO algorithm

Khonakdari

Kamarposhti

2021

PLoS ONE

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“…It can be said that the most important issue in fuzzy controllers based on tpe-2 fuzzy logic systems is recognizing the sources of uncertainty and correct definition of membership functions [7].…”

Section: Type-2 Fuzzy Logicmentioning

confidence: 99%

“…Local detection methods can be categorized into passive, active, hybrid, and intelligent methods, which operate by measuring SG parameters, such as voltage, current, frequency, and harmonic distortion on the microgrid side [5]. Passive methods include under/overvoltage relays (UVR/OVR), under/over-frequency relays (UFR/OFR) [5], rate of change of frequency (ROCOF) [6], methods based on rate of change of active power (ROCOAP) and rate of change of reactive power (ROCORP) [7], a technique based on two criteria of transient index value (TIV) and positive sequence of current angle at common connection point [8], detection methods using signal processing techniques [9], methods based on unbalance voltage (UV) [2], methods based on total harmonic distortion (THD) [10], and methods based on differential transient rate of change of frequency (DTROCOF) [11].…”

Section: Introductionmentioning

confidence: 99%

Real-time Detection of Microgrid Islanding Considering Sources of Uncertainty Using Type-2 Fuzzy Logic and PSO Algorithm

Khonakdari

Kamarposhti

2021

Preprint

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Background: Nowadays, in microgrids based on renewable energy resources (RESs), the uncertainties of load and power generation of distributed generation (DGs) resources is inevitable, which if not taken into account, will lead to errors in network analysis. Results: In this paper, a new method based on type-2 fuzzy logic isproposed to detect microgrid islanding; in whichthe power system does not misoperateduring complex operations, can correctly discriminate the microgrid islandingand other network events at the proper time, and prevent the undesirable performance of DGs. This controller detects islanding in the fastest time under different conditions, and the uncertainties in the system will not considerablyaffect the controller's performance. Conclusions: The proposed method is simulated on the sample system and examined in different scenarios. Then, a comparison is made in different conditions and scenarios between the suggested method and some common methods that have been presented so far to determine the ability of the proposed method to detect islanding.

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“…The negative effects of this distributed generation will in turn give benefits depending on the placement and power [8]. Power plants with a water source are usually far from the load center and fast detection and power quality degradation [9] issues will be evaluate. In this research, it will evaluate whether there are negative effects on the distribution system.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of 20 kV Distribution Network Losses In Radial Distribution Systems Due to Distributed Generation Penetration

Arnawan

Muzamir

Mohd

et al. 2021

J. Phys.: Conf. Ser.

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The installation of distributed generation with renewable energy becomes a solution when the demand for electricity is increasing and electricity generation with fossil energy is increasingly limited. There has been a change in power flow before and after the installation of distributed generation. However there can be a negative impact on the distribution network losses applicable to reactive power flows. There are cases where the distributed generation capacity is greater than the supplied load, resulting in distributed generation operating as a system voltage regulator and requiring reactive power, so that DG will absorb the reactive power from the system. The increasing demand for reactive power in DG also causes an increase in the current flowing in the network, and causes an increase in losses in the network, especially for the losses in reactive power.

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A new islanding detection technique based on rate of change of reactive power and radial basis function neural network for distributed generation

Cited by 7 publications

References 37 publications

Real-time detection of microgrid islanding considering sources of uncertainty using type-2 fuzzy logic and PSO algorithm

Real-time detection of microgrid islanding considering sources of uncertainty using type-2 fuzzy logic and PSO algorithm

Real-time Detection of Microgrid Islanding Considering Sources of Uncertainty Using Type-2 Fuzzy Logic and PSO Algorithm

Evaluation of 20 kV Distribution Network Losses In Radial Distribution Systems Due to Distributed Generation Penetration

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A new islanding detection technique based on rate of change of reactive power and radial basis function neural network for distributed generation

Cited by 7 publications

References 37 publications

Real-time detection of microgrid islanding considering sources of uncertainty using type-2 fuzzy logic and PSO algorithm

Real-time detection of microgrid islanding considering sources of uncertainty using type-2 fuzzy logic and PSO algorithm

Real-time Detection of Microgrid Islanding Considering Sources of Uncertainty Using Type-2 Fuzzy Logic and PSO&nbsp;Algorithm

Evaluation of 20 kV Distribution Network Losses In Radial Distribution Systems Due to Distributed Generation Penetration

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Real-time Detection of Microgrid Islanding Considering Sources of Uncertainty Using Type-2 Fuzzy Logic and PSO Algorithm