Summary form only given as follows. One of critical concerns in the operation of grid-connected dispersed generating units is the occurrence of islanding. It is known that the islanding may pose hazards to utility personnel and complicate the orderly reconnection of the grid. Hence, in this paper, a new algorithm based on the monitoring of the change in /spl delta/f//spl delta/P/sub L/ to detect the islanding is proposed. By the proposed method, a detection index can be evaluated that serves as a useful reference to activate the protective relays. This approach has been applied to investigate different scenarios, including the loss of grid and the parallel operation. Effects of load change and power-quality disturbances to the detection performance are also examined. From these test results, they help solidify the feasibility and effectiveness of the approach for the applications considered.

A Detection Algorithm for Islanding-Prevention of Dispersed Consumer-Owned Storage and Generating Units

Recently there has been a resurgence of concern about islanding of grid-connected photovoltaic (PV) systems. This condition occurs when the PV system continues to energize a section of the grid after that section has been isolated from the main utility voltage source. Generally, islanding is undesirable because it poses a safety hazard to utility service personnel, and also because it can lead to asynchronous reclosure which can damage equipment. It is therefore important that PV systems incorporate methods to prevent islanding. The purpose of this paper is threefold: (1) to critically review the literature on islanding prevention methods for PV systems and discuss their strengths and shortcomings; (2) to review and analyze the islanding behavior of four converters which are prominent in the literature in order to demonstrate the implementation and effectiveness of some islanding prevention methods; and (3) to introduce a new islanding prevention scheme, active frequency drift with positive feedback, which overcomes many of the shortcomings of existing schemes. It is concluded that no ‘perfect’ islanding prevention method yet exists, but also that many existing methods or combinations thereof work very well in practical situations. Finally, it is noted than an investigation of what constitutes ‘sufficient’ islanding prevention is needed. Copyright © 1999 John Wiley & Sons, Ltd.

https://onlinelibrary.wiley.com/doi/pdf/10.1002/%28SICI%291099-159X%28199901/02%297%3A1%3C39%3A%3AAID-PIP246%3E3.0.CO%3B2-J

Prevention of islanding in grid‐connected photovoltaic systems

http://ir.lib.ksu.edu.tw/bitstream/987654321/3762/1/%C3%A8%C2%AC%20%C3%A6%E2%80%B0%C2%BF%C3%A9%20%E2%80%9CJEPE1086-.pdf

Enhancement of islanding-detection of distributed generation systems via wavelet transform-based approaches

A summary is presented of the results of a research project on the islanding potential of a Teslaco self-commutated static power converter (SPC). This project included computer simulations, laboratory testing, and field testing. Laboratory and field tests verified that the SPC model developed for computer simulations accurately predicts SPC islanding performance under a variety of system conditions. The impact of a number of system parameters on the islanding potential of a Teslaco SPC are presented. These include the mismatch between load and generation within the island, the type of load within the island, the number of SPCs within the island, load variations, and solar insolation variations. >

Investigation of potential islanding of a self-commutated static power converter in photovoltaic systems

This paper presents a passive islanding detection method based on means of a neuro-fuzzy approach for wind turbines. Several methods based on passive and active detection scheme have been proposed. While passive schemes have a large Non detection zone (NDZ), concern has been raised on active method due to its degrading power quality effect. Reliably detecting this condition is regarded by many as an ongoing challenge as existing methods are not entirely satisfactory. The proposed method is based on voltage measurements and processing of the hybrid intelligent system called the Adaptive neuro-fuzzy inference system (ANFIS) for islanding detection. This new method based on passive methods will help to reduce the NDZ without any perturbation that deteriorates the output power quality opposite active methods. This method detects the islanding conditions with the analysis of these signals. The studies reported in this paper are based on an experimental system (wind turbine simulator). The results showed that, the ANFIS-based algorithm detects islanding situation accurate than other islanding detection algorithms. Moreover, for those regions which are in need of a better visualization, the proposed approach would serve as an efficient aid such that the mains power disconnection can be better distinguished.

	 

	Key words: Distributed generation, islanding detection, non detection zone, adaptive neuro fuzzy inference system, fuzzy subtractive clustering.

/pdf/adaptive-neuro-fuzzy-inference-system-anfis-islanding-1cd3g23wmf.pdf

Adaptive neuro-fuzzy inference system (ANFIS) islanding detection based on wind turbine simulator

The development of a model for a commercially available self-commutated static power converter (SPC) to investigate the conditions under which isolated operation (islanding) occurs is described. The approach used in modeling the SPC is unique in islanding studies. It is based on solving complex-AC system equations and phase-locked loop differential equations simultaneously to determine the SPC response. The model accurately and optimistically predicts the islanding performance of the self-commutated SPC, as verified in laboratory experiments and detailed computer simulations. >

Ali F. Imece

Papers

An Approach for Modeling Self-Commutated Static Power Converters for Photovoltaic Islanding Studies