A New Passive Islanding Detection Solution Based on Accumulated Phase Angle Drift

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 proposes a novel hybrid approach for islanding detection of inverter-based distributed generations (DG) based on combination of the Slip mode frequency-shift (SMS) as an active and rate of change of frequency (ROCOF) relay and over/under frequency relay as passive methods. This approach is utilized to force the DG to lose its stable operation and drift the frequency out of the allowed range of the frequency threshold. Performance of the proposed approach is evaluated under the IEEE 1547, UL 1741 and multiple-DG operation. The simulation results demonstrate the effectiveness of the proposed approach for detection of islanding, especially for loads with high quality factor. It operates accurately under the condition of load switching and does not interfere with the power system operation during normal condition. In other words, not only it holds the benefits of both SMS and ROCOF, but also it removes their drawbacks by having less non-detection zone and faster response.

Interconnection of distributed generation (DG) in distribution system will result in formation of islands in the event of loss of main supply. This scenario is harmful to the power system, hence quick detection is critical to halt the formation of islands. Among the common passive and active detection methods available, the hybrid detection method is identified as the most reliable method. This paper proposes a new hybrid method using the combination of passive and active technique which is the rate of change of frequency (ROCOF) and load impedance, respectively. The passive method works when the value of ROCOF exceeds the threshold value which is set at 0.3Hz/s. The active method works when it detects low value of ROCOF and immediately inject a pre-specified load into the system to increase the ROCOF value up to its threshold value. Simulation study on different case studies is carried out on distribution test system to evaluate the performance of the proposed method. Results show that this method is effective in detecting any events that could result in islanding.

Microgrids with large distribution networks require an adaptive protection system due to their complex nature of fault behavior and different modes of operation. Conventionally, the adaptive protection in microgrids is realized through one of the passive islanding detection methods due to the ease of implementation and economy. The main drawback of the passive islanding detection methods is the specific non-detection zone (NDZ) associated with each method. To address these gaps, this paper proposes an adaptive protection scheme based on a hybrid method that detects microgrid islanding considering the dynamic operating behavior of the microgrid system, instantaneous current measurement and fault recovery behavior. The proposed adaptive protection scheme allows for timely detection of microgrid islanding, auto-tuning of relay settings while increasing the overall NDZ compared to the existing methods. Moreover, the proposed scheme is fully autonomous and independent of communication links. The effectiveness of the proposed adaptive protection scheme has been thoroughly investigated in DIgSILENT PowerFactory software for a wide-range of practical operating scenarios.

One of the facing problems in distributed generation is being unintentionally islanded which the detection of this phenomenon is of great importance. Common methods are active and passive islanding detection. These two methods are based on changing in parameters such as frequency, voltage and current harmonics. If, after the islanding occur, this changes are revealing and visible, islanding phenomenon is demonstrated which is detected by passive methods. If the generated power of inverter is equal to local loads consumption and assuming of the generated reactive power of grid connected inverter equal to zero, it should be detected by active methods but these two methods have some challenges such as reduction in power quality or wide Non Detection Zone (NDZ). In this paper, in proposed method, change of a new parameter will be studied for islanding detection diagnosis. With the difference that the studied system is a three phase system and unbalanced load is studied which is more consistent to reality. Because of small changes in parameters, we have to find the right approach toward active methods. Generally there are two views about the islanding performance. At first view, this phenomenon is seems negatively but in fact this is an opportunity. The first view suggests that all generators in the island should bring out of grid within a maximum of two seconds. In this view the concept of anti-islanding protection is proposed to tackle the task of creating such islands. The second view expresses the concept of micro grid. In this case as far as possible, power required by Inner Island loads were provided by distributed generators. The studied system was similar to standard IEEE-1547 and UL-1741. With the difference that we used three phase and local loads are assumed unbalanced. Conventional active detection methods are not able to identify the island with the aim to help keep it stable. They usually try to bring out the electrical parameters such as voltage and frequency from nominal limits. So in micro grids the island should be diagnosed using passive or remote techniques. Note that detection time of 2 seconds which is referred to on standards is not good and the detection time must be lower than this value. However, the proposed method that is one of the active detection methods is capable for use in micro grids. Simulation results using PSIM software on standard network shows the effectiveness of the proposed method. Keywords: Islanding, Unbalanced Loads, dq-frame, Phase Locked Loop (PLL), Non Detection Zone (NDZ), Micro-grid.

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.

Real-time validation of RoCoF – Enhancing advanced coordinated control strategy for voltage unbalance mitigation implementing demand side management

Active and Passive Methods of Detecting Parkinson's Disease.

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 & 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.

Owning to the extensive enhancement of renewable energy resources in the distribution grids, the employment of such sources has also introduced various issues, such as the islanding problem. In this paper, an effective method is proposed for the detection of islanding in micro-grids. The proposed method employs the concept of potential energy function to drive the islanding detection index. Based on swing and potential energy function equations, an islanding detection criterion is derived based on the rate of change of the potential energy function. The islanding detection index (IDI) takes into account the frequency changes and the rate of change of frequency (ROCOF) of DG. The superiority of the proposed islanding detection method is manifested in the condition where the generation of distributed resources is in balance with the loading consumption. The performance of the proposed method has been evaluated considering the conditions where islanding is difficult to detect or might be mistaken for other phenomena given by loads within the Non-Detection Zone (NDZ) region, different fault types, and loads with different power factors. The performance evaluation has been carried out through simulations and, furthermore, has been compared with the state-of-the-art algorithms.

In the area of renewable energy technologies, islanding of distributed generation system needs to be prevented due to safety reasons and to ensure quality of power supplied to the customers. Several islanding detection methods based on passive and active schemes have been proposed in the literature. Passive methods have a large non detection zone (NDZ), While active schemes degrade power quality. This paper proposed a new passive islanding detection method which combines the Wavelet-transform and neural network techniques. This method can reduce the NDZ to zero without any perturbation that deteriorates the power quality. The simulation results show that the proposed islanding detection method is effective and robust in all kind of conditions.

Droop control, inertia control, and PD control are three typical frequency response (FR) strategies of grid-tied inverters interfaced renewable energy sources (RES) to restrain the power system frequency indicators, i.e., frequency deviation ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\Delta \omega $ </tex-math></inline-formula> ) and the rate of change of frequency (RoCoF). Due to the highly limited inverter capacity, the FR performance in power systems with high RES penetration should be optimized. To this end, this paper first analyzes the impact of high-penetration renewable energy injection on power system frequency stability, and derives the system frequency expressions in the absence of an FR scheme, and in the presence of droop/inertia/PD controls that are representative for various virtual synchronous generator-based FR schemes. Under the same constraint of available FR capacity, control parameter ranges of these FR schemes are obtained, and their optimal conditions for restraining the maxima of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\Delta \omega $ </tex-math></inline-formula> and RoCoF are identified and compared analytically. Comparison conclusions are finally proved by the provided experiment and simulation results.

A new reliability assessment method for distribution system with distributed generations (DGs) is proposed in this paper, aiming to quantitatively analyze the undesired impact caused by passive islanding detection failure. Firstly, the paper analyzes the impacts of DG interconnection on auto-reclosing operation and system reliability due to failure of anti-islanding detection when a transient or permanent fault occurs. Secondly, the power features in the moment of detection-failure are calculated and utilized for judging whether they exist in the nondetection zones (NDZ) of several common passive islanding detection methods. Then, the new reliability evaluation procedure is given and reliability indices of distribution system could be obtained considering passive islanding detection failure. In the end, the IEEE RBTS Bus6 test system, connected with photovoltaic and wind power, is built to prove the effectiveness of the proposed approach.

Multi grid-connected inverters islanding detection methods include two categories: passive islanding detection and active islanding detection. Firstly, an active islanding detection method based on negative sequence current disturbance is analyzed. Aiming at the shortcomings of this method, a novel passive islanding detection method is proposed in this paper. The proposed islanding detection method uses wavelet transform to extract signal features, and then according to the extracted signal features adopts the neural network to judge whether or not the islanding occurs. The simulation results show that the passive multi grid-connected inverters islanding detection method has good islanding detection performance, and does not affect the stability and power quality of the system.

This paper presents the implementation of the Grid-Forming (GFM) control technique in renewable energy source inverters to synchronize with the grid and provide frequency support. Specifically, the GFM Droop Control technique, based on the Power–Frequency relationship, is employed. The proposed model was developed and validated in the Matlab-Simulink environment. By using electromagnetic transient (EMT) simulations, we were able to precisely monitor and analyze voltage and current waveforms, thereby confirming the approach’s effectiveness in enhancing grid stability and power quality. The implementation of the GFM control technique in islanded mode demonstrated high system frequency stability. In response to sudden load changes up to 5 MW (equivalent to over 30% of the total load), a maximum frequency deviation of 0.04 Hz and a maximum Rate of Change of Frequency (RoCoF) of 4 Hz/s were observed. The system ensured the frequency’s return to its nominal value of 60 Hz, thanks to the virtual inertia and frequency regulation provided by the GFM. The total harmonic distortion (THD) of current and voltage in steady-state operation consistently remained below 1%, thus complying with IEEE 1547 standards. In tests with the GFM interconnected to the grid, the droop+LPF control provided dynamic support to the external system, effectively mitigating both frequency deviations and RoCoF. The GFM contributes to the grid’s frequency stability by providing virtual inertia. The power quality at the point of common coupling (PCC) was excellent, as the voltage distortion was maintained below 0.5%, confirming that the injection of harmonic currents does not violate established limits.