The cheap and reliable primal energy source for battery energy storage system (BESS) refueling necessitates a special attention for combining renewable energy resources with plug-in hybrid electric vehicle (PHEV) charging stations in microgrids. Rapid charging is an operation mode of PHEV for drivers which demands fast recharging of BESSs of the electric cars. This charging mode manifests as low impedance short circuit at dc side, making power transient on power grid side. This paper presents a new anti-islanding protection scheme for low-voltage-sourced converter-based microgrids by exploiting support vector machines (SVMs). The proposed anti-islanding protection method exploits powerful classification capability of SVMs. The sensor monitors seven inputs measured at the point of common coupling (PCC), namely, root-mean-square (RMS) value of voltage and current ( $RMS_{V}$ , $RMS_{I}$ ), total harmonic distortion (THD) of voltage and current ( $THD_{V}$ , $THD_{I}$ ), frequency ( $f$ ), and also active and reactive powers ( $P$ , $Q$ ). This approach is based on passive monitoring and therefore, it does not affect the power quality (PQ). In order to cover as many situations as possible, minimize false tripping and remain selective, training, and detection procedures are simply introduced. Based on the presented sampling method and input model, the proposed method is tested under different conditions such as PHEV rapid charging, additional load change and multiple distributed generations at the same PCC. Simulations based on the model and parameters of a real-life practical photovoltaic power plant are performed in MATLAB/Simulink environment, and several tests are executed based on different scenarios and compared with previously reported techniques, this analysis proved the effectiveness, authenticity, selectivity, accuracy, and precision of the proposed method with allowable impact on PQ according to UL1741 standard, and its superiority over other methods.

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Anti-Islanding Protection of PV-Based Microgrids Consisting of PHEVs Using SVMs

In this paper, transient response of the microgrid caused due to unintended switching events and faults have been investigated in distributed generation (DG) system. The proposed technique is based on two new criteria transient index value (TIV) and positive sequence superimposed current angle at point of common coupling. The proposed method utilizes three phase voltage signals at DG end to compute the TIV. The performance of the proposed integrated approach has been evaluated on a sample test system and a practical distribution network consisting of combined heat and power plant, wind turbine generators, and photovoltaic system. The simulation results demonstrate that the proposed technique exhibits high reliability and leads to faster detection of islanding condition as compared to the existing passive islanding detection methods not only for zero active and reactive power mismatch conditions, but also for transient events caused due to nonlinear loads.

A Transient Component Based Approach for Islanding Detection in Distributed Generation

Islanding in power systems is a challenge that results in various uncertainties in the system parameters, degrades power quality, and may endanger the maintenance workers. This study presents a new passive islanding detection approach for grid-connected distributed generation (DG) units. The proposed method employs a Kalman filter (KF) to extract and filter the harmonic contents of the voltage signal measured at DG terminals. A three-phase voltage signal is measured at the point of common coupling and taken as a test signal for islanding detection. First, a residual signal is generated using the KF to detect different changes in the power system. In the second step, multiple harmonic contents are estimated by the KF to calculate a criterion named selected harmonic distortion (SHD). The variation of SHD classifies between islanding and normal conditions. The IEEE 13-bus test system simulated in Matlab/Simulink is used as a testbed to assess the performance of the proposed approach. The proposed method is extensively analysed under various islanding and non-islanding scenarios. The results demonstrate that the proposed method can successfully differentiate between islanding and non-islanding events. Moreover, it provides high reliability by eliminating the non-detection zone and stands robust against the false operation.

https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/iet-rpg.2018.5381

Harmonic-signature-based islanding detection in grid-connected distributed generation systems using Kalman filter

A passive islanding detection scheme using variational mode decomposition-based mode singular entropy for integrated microgrids

This article proposes a fast and reliable two-level islanding detection method (IDM) for grid-connected photovoltaic system (GCPVS)-based microgrid. In the first level of the proposed IDM, the magnitude of the rate of change of output voltage (ROCOV) is computed. If this variable exceeds a predefined threshold, a disturbance is injected into the duty cycle of DC/DC converter after a given time delay to deviate the system operating point away of its maximum power point (MPP) condition. This leads to a substantial active power output and voltage reduction in an islanded mode. Therefore, the ROCOV and the rate of change of active power output (ROCOP) indices, measured in the second stage, pose great negative sets at the same time in islanding states. However, the variation of at least one of these variables is near-zero in non-islanding switching events. The assessment of the presented algorithm has been conducted under extensive islanding and non-islanding scenarios for a case study system with two PV power plants using hardware-in-the-loop (HiL) simulation tests. The provided results remark precise islanding classification with an eminently small non-detection zone (NDZ) within 510 ms. The presented IDM has the advantages of self-standing thresholds determination, no improper effect on the output power quality, and simple and inexpensive structure. Moreover, the fast MPP restoration of the proposed scheme after islanding identification boosts the chance of seamless reconnection and DG autonomous operation in microgrid.

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Two-Level Islanding Detection Method for Grid-Connected Photovoltaic System-Based Microgrid With Small Non-Detection Zone

An implementation of a new islanding detection technique based on modal components of the voltage signals is presented in this paper. It is based on derivation of islanding detection factor which is derived from the modal transformation of the input voltage signals. Authenticity of the presented technique has been verified by developing a laboratory prototype of the distribution network along with distributed generator. From the developed laboratory prototype, various islanding cases with varying positive/negative active and reactive power mismatches and different non-islanding events have been generated. The experimental results show that the presented algorithm is able to differentiate between islanding situation and non-islanding events efficiently. Moreover, it is able to sense islanding situation rapidly as it operates within three and half cycles after the inception of event. Furthermore, the proposed scheme is able to identify islanding situation even in case of perfect power balance condition. In addition, the presented scheme provides better stability against various non-islanding events and hence, avoids nuisance tripping. At the end, comparative evaluation of the proposed scheme with the existing schemes clearly indicates its superiority in distinguishing islanding situation with non-islanding events.

Experimental Performance of an Islanding Detection Scheme Based on Modal Components

This study presents a new islanding detection technique based on islanding discrimination factor which is derived from the superimposed components of voltages These voltages are calculated by utilising the acquired voltage signals from the terminal of distributed generators Various islanding and non-islanding events with varying power mismatches have been simulated on two different widely used networks namely (i) IEEE 34 bus network and (ii) IEC61850-7-420 Micro-Grid model in real time digital simulator (RTDS/RSCAD) environment The authenticity of the presented scheme has been verified on diversified islanding and non-islanding cases, generated from the above two models The results indicate that the proposed scheme is able to distinguish islanding situation with non-islanding events accurately Moreover, it senses islanding condition quickly (within one and half cycle) even with perfect power balance situation and hence, eliminates non-detection zone In addition, it also provides better stability against nuisance tripping which is initiated due to various types of non-islanding events including reconfiguration of the network In the end, comparative assessment of the presented scheme with the scheme just published in the literature shows its domination in distinguishing islanding condition with non-islanding events

Islanding detection technique based on superimposed components of voltage

This study describes a novel Islanding detection technique based on a discrimination factor (DF) which is derived from an auto-correlation factor (ACF) of the voltage signals acquired from the terminal of the distributed generator. The value of DF is calculated from the most affected lags of the ACF during various Islanding and non-Islanding conditions. Further, the validation of the presented scheme has been carried out by developing a hardware-in-loop laboratory setup. In this setup, a power distribution network has been modelled on a real-time digital simulator (RTDS/RSCAD) which is physically connected to the digital signal processor controller. Various non-Islanding and Islanding test scenarios have been generated. The proposed ACF-based technique is able to differentiate Islanding state with non-Islanding states even for perfect power equilibrium situation. The proposed approach can determine the Islanding state in a period of three cycles from the inception of Islanding. Finally, a relative assessment of the above algorithm with other existing methods shows its supremacy in terms of better stability during critical non-Islanding situations and lower non-detection zone in case of Islanding states.

https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/iet-gtd.2018.6370

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

A new technique for power transformer protection, that depends on the calculation of fault detection ratio (FDR) based on quartile of superimposed differential currents is presented. Internal faults are detected by comparing FDR with the predetermined threshold derived through analytical analysis and verified based on simulation results. The performance of the presented scheme is tested by modeling an existing Indian power transmission network using PSCAD/EMTDC software. Various types of abnormal conditions such as magnetizing inrush (including sympathetic and recovery) and over-excitation along with several types of internal (winding, inter-winding and turn-to-turn) faults have been investigated. Its validity has also been checked on the data of magnetizing inrush and simultaneous inrush with the internal fault in the transformer, which was obtained from the real network. The results reveal the effectiveness of the suggested technique in differentiating internal faults from other abnormal conditions. Further, it remains stable during heavy through fault with current transformer saturation. It is equally applicable for different ratings and winding connections of power transformers. Finally, comparative evaluation of the proposed scheme with the conventional and several existing techniques shows its superiority in terms of higher sensitivity during internal faults and improved stability in case of non-internal faults.

Quartile Based Differential Protection of Power Transformer

This study present a new islanding detection technique based on relevance vector machine (RVM) containing various types of distributed generations (DGs). The proposed scheme is based on utilising negative sequence component of current (I 2), acquired at the terminal of the target DG. Various islanding and non-islanding events with variable real and reactive power, change in network topology and diverse X/R ratio have been generated by modelling IEEE 34 bus system in real time digital simulator (RTDS®/RSCAD) environment. The samples of I 2 for one cycle duration from the inception of islanding/non-islanding events are given as input to the proposed RVM classifier. The proposed classifier is able to discriminate between islanding and non-islanding events with an accuracy of 98.62% by utilising only 40% of the total dataset in training. Moreover, it is capable to classify islanding condition rapidly and correctly even with perfect power balance situation. Furthermore, it remains immune to change in network configuration/entirely different network and X/R ratio of various types of DGs. Comparative analysis of the proposed scheme in terms of accuracy, testing time and number of relevance vectors (RVs) with the existing schemes shows its superiority in discriminating islanding situation with non-islanding events.

https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/iet-rpg.2016.0184

Yogesh M. Makwana

Papers

Experimental Performance of an Islanding Detection Scheme Based on Modal Components

Islanding detection technique based on superimposed components of voltage

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

Quartile Based Differential Protection of Power Transformer

Islanding detection technique based on relevance vector machine