Non-detection Zone Research Articles

Distributed Synchronous generation ride-through enhancement by anti-islanding protection blocking

Fault and other perturbations in the distribution or subtransmission system can change the system voltage and frequency, leading to improper operation of anti-islanding protections. This causes disconnections of distributed generations (DG) and, consequently, financial losses and degradation of Bulk Power System performance. This paper proposes a blocking scheme for an islanding detection function, based on impedance and rate of change of frequency. Several methods have been recently proposed for islanding detection in synchronous generators. However, commercial relays still use functions such as Rate of Change of Frequency. Even though it poses problems that are explored in this paper, it is consolidated and easy to implement. Thus, the proposed method is aimed at improving the performance of DG anti-islanding protection. The method has been tested through simulations using the IEEE 34 node test system. The results show that the proposed method is able to discriminate islanding from other transients, and it has operated properly in all non-islanding events, which include single-phase and three-phase short-circuits, load and capacitor switching, and outages of other DGs. Tolerance to transients allows the use of a small frequency threshold which ensures a small non-detection zone and faster disconnection in case of islanding.

Phaselet-Based Limited-Time $q$-Axis DC Offset Voltage Injection for Detection of Islanding of DG and Fault in a Meshed Microgrid

Rapid grid integration of inverter-interfaced distributed generators (DGs) and low-voltage ride-through capability of the smart inverter, as per IEEE 1547 standard, has made unintentional islanding detection (UID) cumbersome. Also, the feeder reconfiguration capability in meshed microgrids with multiple DGs has made the existing UID techniques ineffective. The methods have limitations in UID for small power mismatch conditions characterizing nondetection zone (NDZ). In hybrid methods for UID, a disturbance injection is continuous or for an extended period, which degrades the power quality (PQ) and creates stability issues. Hence, a decentralized closed-loop hybrid islanding detection method (HIDM) based on the indices extracted from the subcycle phaselet (passive) technique with limited-time (only for two cycles) <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$q$</tex-math></inline-formula> -axis dc offset voltage injection (active) is proposed for UID of DGs. The proposed HIDM mitigates the NDZ due to the closed-loop scheme. Subcycle estimations from the phaselet technique result in quick UID and fault detection and classification process. Furthermore, the PQ issue is reduced due to the limited-time voltage injection (based only on the command from phaselet technique) in the proposed HIDM. Simulation results from the real-time digital simulator on a meshed microgrid and performance comparison with other existing methods prove the efficacy of the proposed HIDM.

A Novel Time-Domain Passive Islanding Detection Technique for Grid-Connected Hybrid Distributed Generation System

In this paper, a time-domain passive islanding detection technique for a grid-connected hybrid distributed generating system has been developed using modified empirical mode decomposition (MOEMD). With the help of the MOEMD, the point of common coupling voltage is decomposed into several oscillatory components called intrinsic mode functions. The islanding will be detected if the magnitude of the islanding detection waveform exceeds the threshold over a predefined delay time. The proposed technique can identify all kinds of islanding cases even for zero power mismatches nearly at 0.3 s of the predefined delay time. The effectiveness of the proposed scheme is tested for different operating conditions that include various non-islanding events. Moreover, the proposed method is faster than the discrete wavelet transform technique, and it has low computational time. The advantages of the proposed method are independent of the system parameters, zero non-detection zone, no classifier requirement, and its performance is independent of the capacity and nature of D.G. connected to the grid.

Voltage-Based Hybrid Algorithm Using Parameter Variations and Stockwell Transform for Islanding Detection in Utility Grids

This paper has introduced an algorithm for the identification of islanding events in the remotely located distribution grid with renewable energy (RE) sources using the voltage signals. Voltage signal is processed using Stockwell transform (ST) to compute the median-based islanding recognition factor (MIRF). The rate of change in the root mean square (RMS) voltage is computed by differentiating the RMS voltage with respect to time to compute the voltage rate of change in islanding recognition factor (VRCIRF). The proposed voltage-based islanding recognition factor (IRFV) is computed by multiplying the MIRF and VRCIRF element to element. The islanding event is discriminated from the faulty and operational events using the simple decision rules using the peak magnitude of IRFV by comparing peak magnitude of IRFV with pre-set threshold values. The proposed islanding detection method (IDM) effectively identified the islanding events in the presence of solar energy, wind energy and simultaneous presence of both wind and solar energy at a fast rate in a time period of less than 0.05 cycles compared to the voltage change rate (ROCOV) and frequency change rate (ROCOF) IDM that detects the islanding event in a time period of 0.25 to 0.5 cycles. This IDM provides a minimum non-detection zone (NDZ). This IDM efficiently discriminated the islanding events from the faulty and switching events. The proposed study is performed on an IEEE-13 bus test system interfaced with renewable energy (RE) generators in a MATLAB/Simulink environment. The performance of the proposed IDM is better compared to methods based on the use of ROCOV, ROCOF and discrete wavelet transform (DWT).

Hybrid Islanding Detection Method of Photovoltaic-Based Microgrid Using Reference Current Disturbance

This paper proposes a new hybrid islanding detection method for grid-connected photovoltaic system (GCPVS)-based microgrid. In the presented technique, the suspicious islanding event is initially recognized whilst the absolute deviation of the point of common coupling (PCC) voltage surpasses a threshold. After an intentional delay, a transient disturbance is injected into the voltage source inverter’s d-axis reference current to decline the active power output. As a result, the PCC voltage reduces in islanding operating mode whilst its variation is negligible in the grid presence. Therefore, the simultaneous drop of PCC voltage and active power output is used as an islanding detection criterion. The effectiveness of the proposed algorithm is investigated for various islanding and non-islanding scenarios for a practical distribution network with three GCPVSs. The simulation results in MATLAB/Simulink show successful islanding detection with a small non-detection zone within 300 ms without false tripping during non-islanding incidents. In addition to the precise and fast islanding classification, the presented scheme is realized inexpensively; its thresholds are determined self-standing, and its output power quality degradation is eminently small. Moreover, the active power output is restored to the nominal set after islanding recognition, enhancing the chance of GCPVS generation at its highest possible level in the autonomous microgrid.

Islanding Detection in Microgrid Compromising Missing Values Using NI Sensors

Islanding detection has become an antiquated topic in microgrid, but during the shabby network condition, the conventional islanding detection methodologies become impractical. This article develops a new islanding detection technique considering interrupted communication during islanding detection. This article has experimented a new predictive model (PM)-based method for islanding detection in the laboratory-based multiple distributed generation (DG) system (system with more than one DG). Microphasor measurement units ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\mu $</tex-math></inline-formula> PMUs) are incorporated for measuring phasors from the real-time system. The measurements are analyzed by the artificial neural network (ANN) for initiating PM, which specifies the occurrence of islanding in terms of probability. The following two subalgorithms: evaluation and decoding are simultaneously working to estimate probability of the islanding during sound network condition. The posterior probability evaluation comes into action when communication is interrupted. The accuracy of the algorithm is tested under UL 1741 loading conditions. The performance of the algorithm is analyzed under the simultaneous manifestation of communication interruption and several islanding or nonislanding condition. Nondetection zone has been evaluated for different scenarios of missing frames. The algorithm has also been compared with existing methodologies.

Islanding Detection Parameters for Integrated Distributed Generation

Background: The growth of renewable energy sources is increasing in the world to meet the energy consumption demand. The major problem after the integration of renewable sources is islanding. The islanding is not safe for equipment and customers. As per Distributed Generation (DG) interconnection standards, it should be detected within 2 seconds. Objective: This paper presents the review of various islanding detection methods for increasing the stability of islanded DG. This will help future researchers for selecting the best islanding detection method with zero NDZ. Methods &amp; Results: The islanding detection methods are classified as local and remote techniques. The local techniques are again classified as active, passive and hybrid methods. Each method is presented with their islanding detection time, power quality issues, Non Detection Zone (NDZ), advantages and disadvantages. Conclusion: The fuzzy based artificial intelligence with Particle Swarm Optimization (PSO) passive methods have been reduced the NDZ to zero and increase the stability of DG without degrading the power quality as active and passive methods.

Small Signal Stability Analysis Oriented Design of Hybrid Anti-Islanding Protection Technique Based on Active Disturbance Injection

The conventional over/under voltage, over/under frequency based anti-islanding protection scheme presents significant nondetection zone (NDZ) under critical loading conditions of distribution networks. To overcome this challenge, a unique hybrid technique has been proposed in this article for the anti-islanding protection of distributed generators (DGs). The algorithm requires the injection of an active oscillatory disturbance signal of very small magnitude through the current control loop along the direct axis of the synchronously rotating reference frame of the converter. Small signal stability analysis of the system is carried out to analyze the effect of such active signal injection having different frequencies. The anti-islanding protection algorithm first involves the superimposition of d-axis voltage. Thereafter, two novel indexes are proposed based on which the trip signal logic is developed for the protection scheme. The methodology has been found to detect an unintentional islanding scenario within 90 ms from the initiation instant. The efficacy of the proposed hybrid anti-islanding protection scheme is tested under various abnormal operating conditions by performing simulations on the CIGRE LV test system. Experimental validation of the proposed methodology has also been carried out in Controller Hardware-in-the-Loop (CHIL) platform using Typhoon HIL 602+ and Speedgoat baseline real-time target machine.

On the Marginal Stability/Instability of Power Island Following Unintentional Islanding: A Modal Analysis Based Approach

This brief presents a theoretical approach to investigate the cause of marginal stability/instability of an islanded system following unintentional islanding event when DGs are enabled with P(f) and Q(V) regulation. Nondetection zone being a traditional cause as per previous investigations, a small-signal model of the standard UL 1741 anti-islanding test system is developed in this brief under islanded condition to illustrate the problem of undamped oscillations. Dynamic model validation has also been performed to verify the correctness of the developed linearized state space model. The eigenvalue analysis of the model successfully illustrates the reason behind sustained oscillations of the system under loss of mains scenario. Finally, time-domain simulations are performed in PSCAD/EMTDC platform to demonstrate the effect of such instability/marginal stability of power island.

Incorporating SLAM and mobile sensing for indoor CO2 monitoring and source position estimation

Indoor Air Quality (IAQ) monitoring is becoming an increasingly important topic since it critically affects occupants’ health, comfort, and safety, etc. Conventionally, monitoring sensors are distributed at stationary positions for measurement acquisitions, which cannot easily become wireless causing a high cost of infrastructure installation and maintenance. Furthermore, stationary sensing often incurs the problems of non-detection zones and low-granularity monitoring, especially in complex indoor scenarios where environmental factors are dynamic and non-convex functions. To address these critical issues, this paper proposes a mobile IAQ sensing using an automated robot equipped with one LIDAR and one CO2 sensor, to enable the prompt detection and positioning of contaminant sources (a CO2 contaminant source). Both stationary sensing (with 9 CO2 sensors) and mobile sensing (a robot with one CO2 sensor) are evaluated in real-world experiments carried out in a typical laboratory room. The spatiotemporal analysis demonstrates that the automated mobile sensing is capable of efficient and agile IAQ survey. The heat maps of the CO2 concentration illustrate that mobile sensing observes better accuracy and granularity of the pollutant detections, as mobile sensing estimates the position of the CO2 source about 1.83 m away from the ground truth position, in contrast with stationary sensing of 3.1 m. The proposed autonomous and mobile IAQ monitoring consumes much less infrastructure (one sensor instead of nine stationary sensors), implementation complexity, and amount of data for communication and processing.

A new passive islanding detection method for hybrid distributed generation under zero power imbalance

To solve the energy consumption demand of the world and environmental problems in the future, the distributed generation is considered an alternative approach. In this paper, a new passive islanding detection technique is proposed for the hybrid distributed generation (HDG) system based on changes in negative sequence voltage (NSV) and currents during an unintentional islanding. Islanding is caused in the distributed generation system due to failures in the power grid. As per distribution energy resources interconnection standards, it should be detected within 2 sec with the equipments connected to it. It is difficult to detect islanding during zero power imbalance condition. Sequence analyser will separate the positive, negative and zero sequence components of voltages and currents from the voltages and currents obtained at the point of common coupling (PCC). During a wide range of power imbalance conditions, the change in negative sequence voltage and currents are examined for islanding detection. The simulation shows that this method is free from non-detection zone, even at zero power imbalances between load and distribution generation. The computer simulations made in MATLAB/Simulink laboratory show the effectiveness of this method.

A new passive islanding detection method for hybrid distributed generation under zero power imbalance

To solve the energy consumption demand of the world and environmental problems in the future, the distributed generation is considered an alternative approach. In this paper, a new passive islanding detection technique is proposed for the hybrid distributed generation (HDG) system based on changes in negative sequence voltage (NSV) and currents during an unintentional islanding. Islanding is caused in the distributed generation system due to failures in the power grid. As per distribution energy resources interconnection standards, it should be detected within 2 sec with the equipments connected to it. It is difficult to detect islanding during zero power imbalance condition. Sequence analyser will separate the positive, negative and zero sequence components of voltages and currents from the voltages and currents obtained at the point of common coupling (PCC). During a wide range of power imbalance conditions, the change in negative sequence voltage and currents are examined for islanding detection. The simulation shows that this method is free from non-detection zone, even at zero power imbalances between load and distribution generation. The computer simulations made in MATLAB/Simulink laboratory show the effectiveness of this method.

Islanding Detection for Inverter-Based Distributed Generation Using Unsupervised Anomaly Detection

Islanding detection with the rising grid supporting inverter-based distributed generation is becoming more critical protection due to its high droop gains and overall decreased system inertia leading to rapid changes in the electrical parameters. Traditional methods for islanding detection in this regard are susceptible to significant problems such as non-detection zone, false-positive detection, and inefficient mode of validation. Therefore, to attenuate these problems, this paper proposes a hybrid islanding detection technique based on unsupervised anomaly detection using autoencoders. This technique uses the rate of change of frequency as primary and phase angles of the voltage and current as secondary detection parameters, demonstrating improved performance, reliability, and robustness due to its shared advantage of both active frequency drift and autoencoder. Furthermore, a dialectic model of offline and online validation schemes is also proposed to ensure the reliability of detection. Extensive simulations and validations have been carried out on multiple networks to generate data sets used to train, test, and validate the technique and compute its statistical significance, thereby confirming its effectiveness. The optimal islanding detection time for the base cases was recorded as 20 milliseconds with an F1-score of 0.991, dependability index of 0.998, security index of 0.995, with total harmonic distortion of 4.56% and zero non-detection zones, which complies with IEC 61000-3-2 and IEEE standard 1547’s requirement of detection within two seconds after islanding.

Sequence Measurement-Based Islanding Detection of DGs in Microgrid With Enhanced Power Quality

Maintaining the power quality (PQ) of supply in a microgrid is a challenge due to the massive integration of inverter interfaced distributed generators (IIDGs). Supply’s PQ and IIDG controller’s transient performance degrade due to continuous, uncontrolled, and nondecaying injections in active methods for islanding detection. Also, active methods have limited application due to increased total harmonic distortion (THD) of current during microgrid’s operation. In this article, a novel sequence measurement-based identification of grid disturbance by sensing voltage and current is proposed to control the disturbance injection cycle in the IIDG controller during islanding detection. The disturbance is a low-frequency decaying current injection in the IIDG controller with controlled input. The proposed method is experimentally verified in controller hardware in loop (CHIL) with real-time digital simulator (RTDS) using the TMSF28335 microcontroller and compared with several previous methods. The impact on PQ due to change in the injection points with controlled and uncontrolled injections is also analyzed. The results indicate that the islanding detection time is low. Also, the proposed closed-loop method is effective and reliable due to two-stage screening. The nondetection zone (NDZ) is eliminated with negligible impact on the PQ of supply.

Identification of Islanding Events in Utility Grid With Renewable Energy Penetration Using Current Based Passive Method

Renewable energy (RE) generation levels are increasing in modern power systems at a fast rate due to their advantages of clean and non-exhaustible nature of energy. However, this type of generation creates technical challenges in terms of operation and control due to uncertain and un-predictable nature of generation. Islanding is an operational scenario where there is a loss of grid and RE generators continue to feed power to the local load. This has harmful effects on the RE generators and operating personal. Hence, it is expected that islanding scenario is identified in minimum time and RE generators are disconnected within 2 s duration after island formation. This paper designed an islanding identification scheme (IDS) by designing a current islanding detection indicator (CIDI) that combines the features computed by processing the current signals, negative sequence current (NSC) and negative sequence voltage (NSV) using the Stockwell transform (ST) and the Hilbert transform (HT). Information contained by the total harmonic distortions of voltage ( THD <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">v</sub> ) and current ( THD <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">i</sub> ) is also used while designing the CIDI. Islanding and non-islanding events of category-I & II are identified and discriminated from each other by comparison of peak magnitude of CIDI with the first threshold value (FTV) and second threshold value (STV). This IDS effectively recognizes the islanding events even in the noisy environment with minimum non-detection zone (NDZ) and minimum time. The efficiency is greater than 98% even with the noise of 20dB SNR (signal to noise ratio). The performance of proposed IDS is better compared to IDS using discrete wavelet transform (DWT), Empirical mode decomposition (EMD), Slantlet transform & Ridgelet probabilistic neural network (RPNN), and artificial neural network (ANN). The effectiveness of IDS is validated on IEEE-13 nodes test system using MATLAB software, practical distribution network and in real time scenario by use of real time digital simulator (RTDS).

Modified Q–f Droop Curve Method for Islanding Detection With Zero Non-Detection Zone

In this paper, a modified Q-f droop curve method for inverter-based distributed generator is proposed. The proposed method has merits such as detecting islanding with zero non-detection zone, negligible effects on power quality and simple implementation. A new parameter is embedded in the reactive power reference to accelerate the frequency deviation at the point of common coupling, until the islanding is detected. Therefore, a passive under/over frequency relay will be simply sufficient to detect islanding within the permissible limit. The proposed method is modelled with computer-aided design SIMULINK/MATLAB environment. The proposed method is analysed for operation with unity and non-unity power factors. The performance is validated for various loading quality factors with a negligible change in detection time. In addition, it is confirmed that the proposed system is stable under unbalanced loading and switching conditions. The proper operation of proposed islanding detection method under multi distributed generators connection is validated. The results of the hardware experimentations are presented to confirm the proposed method analysis and simulations.

An improved islanding detection algorithm based on AFDPF

Unplanned islanding is a harmful phenomenon that will cause a series of adverse effects on the power grid. Therefore, islanding detection is a necessary feature of a microgrid with distributed power generation. Based on the Active Frequency Drift with Positive Feedback (AFDPF) algorithm, this paper proposes an improved frequency offset method.The method uses the frequency difference between two cycles to determine the direction of the disturbance signal. The value of the third power is superimposed on the point of common coupling (PCC)to improve detection speed.And check the Nondetection zone of this method based on the Qf0×Cnom coordinate system. Finally, through MATLAB/simulink simulation, the effectiveness and superiority of the improved frequency shift islanding detection algorithm are verified.

Permutation Entropy Thresholding: A Non-Linear Signal Processing Method for Islanding Detection

ABSTRACT A novel passive method based on Permutation Entropy (PE) is proposed for fast, efficient, and differential detection of islanding from other disturbance events in power system. The extremely remarkable attributes of PE such as efficient and fast detection of change in dynamics as well as computational and conceptual simplicity can be appropriately utilized to devise a thresholding system that can differentiate the change in dynamics of islanding event from the non-islanding ones with negligible Non-Detection Zone (NDZ). As NDZ is the most critical issue of existing passive islanding detection methods, which overshadows its beneficial characteristics, this new approach can prove to be a suitable alternative with an added benefit of faster detection. The method is evaluated with grid connected single as well as multi-DG systems and its robustness against effects of load quality factors, active and reactive power mismatches is investigated. Results show that this method can detect the islanding disturbance and differentiate it from other disturbances within half a cycle. The performance of the proposed method is evaluated with photovoltaic (PV) sources and also validated on IEEE 14 bus model. Results indicate the suitability of the PE method for the common DG source of PV for a wide range of power mismatches including the worst cases and also its robustness against false tripping during DG switching. The results verify the credibility and advantage of the proposed PE thresholding method and its suitability for adopting into existing networks for passive islanding detection.

Improved Active Islanding Detection Technique for Multi-Inverter Power System

Due to the increased penetration of multi-inverter distributed generation (DG) systems, different DG technologies, inverter control methods, and other inverter functions are challenging the capabilities of islanding detection. In addition, multi-inverter networks connecting the distribution system point of common coupling (PCC) create islanding at paralleling inverters, which adds the vulnerability of islanding detection. Furthermore, available islanding detection must overcome more challenges from non-detection zones (NDZs) under reduced power mismatches. Therefore, in this study, a new method called parameter self-adapting active islanding detection was utilized to minimize the dilution effect and reduce NDZs in multi-inverter power systems. The method utilizes an active frequency drift (AFD) method and applies a positive feedback gain of adoption parameters, which significantly minimizes NDZs at parallel inverters. The simulation and experimental outcomes indicate that the proposed method can effectively weaken the dilution effect in multi-inverter networks connecting the distribution system PCC.

Modified Sandia voltage shift anti‐islanding scheme for distributed power generator systems

This study presents an active anti-islanding technique for distributed power generator systems. The proposed scheme is based on the Sandia voltage shift (SVS) technique, which is characterised by a small non-detection zone (NDZ) and by an acceptable solution to the trade-off between the output power quality and the effectiveness of islanding detection. The proposed technique has the advantage to improve the NDZ and to reduce the anti-islanding detection times. This is due to the exponential-product modification made in the positive feedback to inject current, thereby making the response faster than SVS. Additionally, a self-adaptive gain is considered to achieve a low total harmonic distortion at different power levels. Moreover, the proposed scheme has been validated with theoretical and numerical analysis and experimental results. Finally, the behaviour and performance of the proposed technique are compared with other recent techniques.