Apparent Power-Based Anti-Islanding Protection for Distributed Cogeneration Systems

In this paper, a new passive islanding detection method for grid-connected photovoltaic inverters is proposed. The proposed method is based on extracting signatures from the high frequency components of voltage at the point of common coupling (PCC), which occur after an islanding condition. These high frequency components contain signature information capable of identifying the islanding condition. The PCC voltage is measured and its high frequency sub-band contents are extracted using wavelet packet transform (WPT). This characterization helps to provide enough information to efficiently detect and discriminate the effect of load switching disturbances and grid voltage distortions from islanding conditions. The effectiveness of the proposed method is tested in simulation of a grid-connected inverter system. The simulation results, carried out by Matlab/Simulink are used to validate the performance of the proposed method. The results demonstrate that the proposed method can detected within one cycle (20 ms), even with small non-detection zone and can discriminate between islanding and other events in the system, as load switching disturbances and grid voltage distortions.

Islanding is a major problem that is related to a grid connected distribution generator. During islanding the distribution generator gets disconnected from the grid while still being energized. It should be detected as fast as possible in order to prevent the distribution generator from getting damaged or to ensure the safety of the personnel working. The islanding detection makes use of system parameter to detect islanding at the time of occurrence. In this paper a passive islanding detection method based on ripple content of voltage at the point of common coupling is being used to differentiate between islanding and non-islanding conditions. A threshold level is set upon the ripple content of voltage at the point of common coupling and islanding is detected whenever the threshold level is exceeded for some certain period of time. This method effectively distinguishes the islanding condition from other non-islanding condition and detects the islanding condition efficiently. The working of this method is being ensured by simulating a variety of islanding and non-islanding condition. No non-detection zone was shown by this method and islanding conditions were detected within 150ms of the allowed delay time. Theoretical analysis and simulation results are presented to validate the proposed method.

Distributed generators (DGs) require detection of islanding condition due to personnel safety hazards and equipment damages. Anti-islanding methods are divided into passive and active methods. The passive methods are based on measurement of the natural effects of islanding. The active methods use the effects by intentional transients or harmonics. When the power generated by the DG matches power consumption by load, passive methods fail due to small natural effect of islanding. Therefore, the passive methods have a non-detection zone (NDZ). The active methods can reduce the NDZ size. But these methods reduce the power quality of the grid. In this paper, a novel anti-islanding method (AIM) is proposed. The single phase DG using the proposed AIM injects output current included a little harmonic current into the grid and monitors the harmonic component of voltage at the point of common coupling (PCC) by using Goertzel algorithm. The Goertzel algorithm is a kind of discrete Fourier transform (DFT). It extracts magnitude and phase of the desired frequency from the input signal, with minimum computation. The proposed islanding detection algorithm does not only have NDZ but also bad effect on the power quality of the grid due to injecting harmonic components qualified the interconnection standard. The proposed islanding detection method (IDM) is verified by the PSIM simulations and the experimental results.

The quick detection of islanding in active distribution networks is the main challenge for power engineers. The late detection of islanding may have hazardous impacts on the power systems. Due to the advancement in photovoltaic (PV) technology and their eco-friendly nature, these systems are widely in demand. The islanding methods in the power system are classified into active, passive, remote, and hybrid. The passive methods depend on the measurement of electrical parameters such as voltage, frequency, and phase angle at the point of common coupling (PCC) during islanding condition. The purpose of this paper is to analyze the performance of different passive methods in 100 kW grid-connected PV array. This research paper compares over/under frequency, over/under voltage and rate of change of frequency (ROCOF)-based islanding detection methods (IDMs). The performance of these methods has been analyzed at different conditions. Computer simulations are performed using MATLAB/Simulink.

This paper presents the analysis and development of a new digital differential protection for three phase (3φ ) power transformers. The proposed digital protection is based on extracting high frequency sub-band contents present in the <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">d</i> - <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">q</i> axis components of the differential currents in order to identify internal faults. The desired high frequency sub-band contents are extracted using a single-stage wavelet packet transform (WPT), which offers parameterizing the energy in the high frequency sub-band contents using a finite number of coefficients. The WPT coefficients contain information that offer accurate, fast, and reliable detection and classification of transient disturbances, including magnetizing inrush and internal fault currents that may be experienced by 3φ power transformers. The <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">d</i> - <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">q</i> WPT-based digital differential protection is implemented for off-line performance evaluation using differential currents collected from a 5 kVA, 3φ, laboratory power transformer. Off-line test results demonstrate accurate, fast, and reliable detection, classification, and response to different types of fault and non-fault currents. These encouraging performances of the <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">d</i> - <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">q</i> WPT-based digital differential protection are obtained with simple implementation, reduced computational burdens, and small memory requirements.

Islanding phenomenon is often undesirable for microgrids because it may interrupt power services, and cause damage to the equipment. At times, islanding is also required to isolate any potential problem. Anti-islanding methods can detect the islanding, causing the distributed generators (DGs) to stop providing power to the loads in microgrids, the passive islanding techniques are easy implementation, but the non-detection zone (NDZ) of them is too large. This paper presents a method to reduce the NDZ of passive islanding techniques by controlling the output power of the inverters. A structure of hybrid AC/DC microgrid is under operating with the anti-islanding method. The over/under voltage (OUV) and over/under frequency (OUF) methods are used to detect the islanding phenomenon at the point of common coupling (PCC) to ensure all power generated by DGs can be fully utilized. The proposed system is developed in MATLAB/SIMULINK environment and tested for the results.

This paper presents the improvement of the voltage sags for the semiconductor fabrication facility by the installation of cogeneration systems. The critical equipment is evaluated against the SEMI F47 and ITIC power quality documents. The cogeneration system is installed to mitigate the voltage sags due to external system faults. Also, the under voltage relays to disconnect the cogeneration system from the utility are designed by considering the critical clearing times at the point of common coupling and voltage sags ride-through curves. The dynamic responses of different fault conditions are executed by using the transient stability analysis to calculate and define the voltage sags ride-through curves with and without considering the disconnection of the cogeneration system. It is concluded that the voltage sags ride-through capability can be improved greatly if the cogeneration systems are performed to trip accurately according to the under voltage relays design proposed by the paper.

This paper offers a pattern identification-based scheme for discovering the islanding conditions in synchronous generator-based distributed generation (DG) systems. The chief purpose of the suggested scheme in this investigation is measuring the Changes of Magnetomotive Force (MF) in the airgap of DG (ΔMF) within 412 ms after events, Which is less than 2 seconds by IEEE std.1547. First, The MF signal sampled at the DG was inspected by Mathematical Morphology Filter (MMF) for noise reduction. Then, a k-Nearest Neighbor (k-NN) classifier was taught by ΔMF of DG to recognize the islanding conditions from the other typical operation conditions. The consequences of the inspections on the different islanding conditions incorporating system loading and network operation conditions of a typical system were showen to inquiry the capacity of the suggested scheme for islanding discovery. The consequences exhibit that the suggested algorithm firmly discovers and classifies the islanding and non-islanding conditions within 467 ms. The precision quantity of discovering the islanding and non-islanding conditions is 100% for clean and noisy (30 and 20 dB, respectively) test data under the mismatches ΔP=-5% and ΔQ=- 0.5 % for the typical system.

A grid-connected inverter should stop supplying energy to the local load when the grid is disconnected. It is called anti-islanding. To detect the islanding operation of inverter, many islanding detection methods were generally employed. Anti-islanding methods are divided into two groups: active methods and passive methods. Active methods generate the perturbation to change grid parameters such as magnitude of grid voltage and frequency in the allowable range. Most active methods using frequency variation generate the reactive power in accordance with the grid frequency. In this paper, a new islanding detection method is proposed. The proposed method uses the feed-forward voltage of the current control loop to make positive feedback on frequency. The phase angle of feed-forward voltage shifts according to the grid frequency variation. Thus, in the islanding condition, phase shifted feed-forward voltage makes inverter output voltage leading or lagging. Through the principle, the proposed method generates reactive current and drifts grid frequency out of the allowable range in the case of islanding operation. The feasibility of the proposed method was verified by computer simulations and experiments based on 600W inverter system.

This study presents a new method for detecting an islanding event in a microgrid with embedded converter‐based distributed generation (DG). Unlike other schemes, the proposed scheme injects negligible perturbations into the microgrid after the generation of an alert signal. The proposed scheme then uses another index called superimposed impedance, ΔZ. The ΔZ is characterised by a low steady‐state magnitude during the grid‐connected mode and a high magnitude during the islanded mode. Furthermore, for a fault at the point of common coupling (PCC), the magnitudes of ΔZ and PCC voltage are both very low – except during the initial transient period, where |ΔZ | momentarily crosses the threshold. Therefore, an islanding event can be detected if the magnitude of ΔZ is high for some specified time. Moreover, a fault event will not be misdirected as an islanding event because the steady‐state magnitudes of both the ΔZ and PCC voltage are very low in the case of a fault. The robustness of the proposed detection scheme is evaluated against different islanding conditions and also, for a fault at the PCC, first by using MATLAB‐based simulations and later by using a laboratory‐based experimental setup. A comparison with a recently published detection scheme shows the superiority of the proposed schemes.

This paper proposes a new method for fast detection of the point of common coupling (PCC) voltage variations for a grid connected PV inverter. The main feature of this method is the rapidity of the algorithm in such a way that the detection can be carried out even when protection devices are not yet activated. The method uses only voltage sensors at the PCC and the algorithm is based on temporal redundancies obtained with previous stored measurements. The method consists in obtaining a residual, which is generated using simplifications introduced by the real-time constraints. The operation principle is as follows: in healthy mode, the residual is lower than a certain threshold. However, if there is PCC voltage variation, the residual value will increase, allowing a fast detection of this change. The theoretical analysis is performed in order to establish threshold analytic expressions in both cases, with and without PCC voltage variations, and to explain the residual waveform during faults. The proposed method is easy to implement, fast and does not require system parameters knowledge. Simulations and experimental results are presented to demonstrate the effectiveness of the proposed method.

The Low Voltage ride Through (LVRT) capability of Wind Turbines (WTs) determines the connectivity of WT to the grid based on both voltage sag magnitude and duration locally measured at Point of Common Coupling (PCC), in order to protect the WT against overloading out of its tolerable apparent power. If the WT is still inside its safe and secure operating condition and there is still some standby capacity available in it to support the grid, the WT should remain connected to the power system regardless of voltage sag magnitude and duration until the WT apparent power exceeds its nominal value. In case of islanding, which often is accompanied with a low voltage drop, the WT may be improperly disconnected while operates with less than half of its nominal apparent power. This situation necessitates investigation or perhaps a revision of LVRT grid code to be efficient for all possible incidents, not only Short Circuit (SC) faults, but also cascading events and islanding.

Temporary islanding of offshore wind farm will happen owing to the HVDC (High Voltage Direct Current system) blocking while transient DC-fault occurs in the connected FB-MMC (Full Bridge Modular Multilevel Converter) HVDC system. As the mainstream of offshore wind farm, DFIG (Doubly Fed Induction Generator) has defects under islanding conditions in control strategy, which causes the phenomena of overvoltage and instantaneous impulse current in PCC (Point of Common Coupling) node, threating to security of both HVDC and wind-farm. This paper analyzes response of DFIG under temporary islanding in detail and proposes a solution of transient DC FRT (Fault Ride Through) for DFIG, which is verified by simulation on PSCAD/EMTDC.

This paper proposes a novel active anti-islanding scheme for inverter fed roof-top solar PV generation connected to LT distribution grid with unbalanced non-linear loads. The method is based on creating a perturbation in the system using positive feedback and d-q implementation algorithm. The conventional passive anti-islanding schemes fail to detect islanding during power balancing conditions, but the novel active anti-islanding controller ensures that the voltage (or frequency) at the point of common coupling (PCC) is automatically driven beyond the threshold preset values. This proposed scheme has been tested in the presence of non-linear loads and development has found faster islanding detection compared to the existing methods. Further, the islanding conditions are simulated and accurately verified on real time.

To improve the quality of input data of multivariate calibration model, a new hybrid preprocessing algorithm (WPT-GA-OSC) was proposed, which is the combination of wavelet packet transform (WPT), genetic algorithm (GA) and orthogonal signal correction (OSC) algorithm. At first, WPT algorithm is applied to split the raw spectra into different frequency components. Then, based on the root mean square error of prediction models, the genetic algorithm is employed to select the WPT components related to analyte as the input data of regression model. At last, to further improve the quality of input data, OSC algorithm is applied to each GA-filtered component to eliminate the information irrelevant to analyte information. To validate the WPT-GA-OSC algorithm, it was applied to develop the calibration model for oil concentration measurement of corn. Compared with the conventional preprocessing algorithm, the WPT-GA-OSC algorithm can take full advantages of multiscale property of near infrared (NIR) spectra, and also can significantly decrease the prediction error by up to 48.3%, indicating that it is a promising way for filtering the spectral data to develop the NIR calibration model.