Unintentional islanding is one of the serious concerns to be addressed when interfacing a distributed generation source, as it causes damage to the equipment and personnel. Many algorithms have been proposed for islanding detection in the literature which are classified into local methods (passive, active and hybrid), communication-based methods, and methods employing signal processing and classifiers techniques. Out of which, passive islanding detection methods have been mostly adopted in practice since they have an edge over other islanding detection methods (IDMs) such as there is no degradation of power quality as in active methods and are simple to implement and cheap as compared to communication-based methods. Therefore, in this paper, an attempt has been made to systematically put forward a detailed review of islanding detection methods exclusively with a passive approach. This review provides an insight into passive parameters (which are islanding detection indicators) considered by various researchers and their performance with respect to detection time (also known as run-on-time), non-detection zone, performance in a noisy environment exclusively for passive schemes employing signal processing techniques, difficulty level and process of selecting threshold value(s). Additionally, this review provides a brief account on the future role of passive schemes and also passive IDMs incorporating ride-through requirements in compliance with recent interconnection standards.

Methods to Detect the Occurrence of an Unintentional Island with Passive Approach: A Review

A comprehensive literature review of conventional and modern islanding detection methods

This paper presents an Abrupt Change Detection (ACD) algorithm based on Mathematical Morphology Gradient (MMG) for Non-Intrusive Load Monitoring (NILM). In the present research of MMG, it is focused on filtering the original signals rather than locating change points. Therefore, this paper considers this approach to detect abrupt changes. For the purpose of evaluating the performance of different algorithms, the True Positive Rate (TPR) and the F-score are employed in this paper. The simulation studies have been carried out on low-frequency signals and high-frequency signals from the Reference Energy Disaggregation Data Set (REDD) respectively. The MMG algorithm, which has the advantages of high accuracy and fast calculation speed, is superior for both two types of signals. In addition, it can provide not only the information of the position of a change but also the direction of a change. The results demonstrate that the MMG algorithm shows better performance than the CUmulative SUM (CUSUM), the Bayesian Information Criterion (BIC) and the Generalized Likelihood Ratio (GLR) algorithms.

Abrupt Change Detection of Home Electrical Appliance Signals Using Mathematical Morphology Gradient

ABSTRACT Renewable-based distributed generation (DG) has a vital contribution to the evolution of the microgrid model. It is usually operated in both grid-connected mode and island mode. Detection of the islanding event (IE) is required to avail benefits like safety and protection of the connecting devices and personnel or crewmen. The improper islanding detection may lead to power quality degradation (PQD), out-of-phase reclosing, and grid protection interference. The IE can be properly detected by using an islanding detection scheme (IDS). IDS regularly monitors the EPS state, and if there is a problem with the grid’s healthiness, the TS is delivered. Usually, when load demand is the same as DG generation, or load demand is more than DG generation capacity, it is an IE. To mitigate these issues concerning islanding detection, numerous researchers have suggested various strategies that are widely categorized as Passive, Active, Hybrid, Communication-based, Signal Processing-based, and Intelligent-technique-based. Here, a review of several proposed methods is discussed with their performance indices like control variables, merits, demerits, non-detection zone (NDZ), Power quality issues, speed of detection, and computational burden. Conventional passive IDS lies within 80% accuracy that is very poor, Active IDS and hybrid IDS are intermediate range, and communication-based IDS (CIDS) is known to be a good one, but signal processing-based IDS and intelligent-based IDS have the highest accuracy in the range of 95% to 100%. Researchers and scientists can use this review to assist them in choosing the best approach for future applications.

A comparative Studies on different islanding detection methods for distributed generation systems

The use of distributed generation (DG) in distribution system is on the rise. In some setups, DG enables the distribution systems to operate in autonomous mode. However, this mode is not widely utilized due to safety and stability issues. This paper presents a scheme that facilitates the distribution system to maintain stability when transitioning to autonomous mode. Firstly, boundary detection method is proposed to determine the topology of the island formed. Next, voltage collapse prediction index (VCPI) is adopted to determine the stability state of each bus in the islanded system. For the third step, a stability enhancement scheme based on VCPI to shed the critical bus for stabilizing the system is proposed. The proposed scheme is simulated in a generic 9-bus system via EMTDC/PSCAD and MATLAB software operating in parallel. Results show that the proposed scheme can identify the island topology accurately and maintain voltage stability post-islanding.

Stability Enhancement of Islanding Event Through Boundary Detection and Voltage Stability Index

The paper presents a novel method for islanding detection based on time domain, non linear signal processing tool called Mathematical Morphology. The method uses Multi-resolution morphological gradient (MMG) algorithm to operate on three phase voltages and currents at target DG location. The result of MMG algorithm is used to compute norm of the three phase voltage and current. The ratio of these norms (voltage and current) are used to obtain a norm ratio index for each phase. Norm index for Islanding detection is obtained by summing the norm ratio index of each of the three phases. Norm index is found to be very effective in detecting island in distribution system with distributed generation integration.

Islanding detection using mathematical morphology for distributed generation

Unintentional islanding is a critical issue in the integration of distributed generation to the power distribution network. Islanding detection or anti islanding protection for a distribution generation is important in this regard. The paper proposes a new islanding detection scheme in time domain based on Mathematical morphology. The detection technique uses the Morphological gradient wavelet(MGW) to operate on voltage and current in any phase. The Norm of the voltage and current after passing through the MGW is calculated. This ratio is used as a criteria for detecting an island. Simulations are carried out for different islanding and non islanding events to study the effectiveness of the algorithm.

M A Aneesa Farhan

Papers

Islanding detection using mathematical morphology for distributed generation

Islanding detection scheme based on morphological wavelets