Abstract
The increased penetration of distributed generation (DG), renewable energy utilization, and the introduction of the microgrid concept have changed the shape of conventional electric power networks. Most of the new power system networks are transforming into the DG model integrated with renewable and non-renewable energy resources by forming a microgrid. Islanding detection in DG systems is a challenging issue that causes several protection and safety problems. A microgrid operates in the grid-connected or stand-alone mode. In the grid-connected mode, the main utility network is responsible for a smooth operation in coordination with the protection and control units, while in the stand-alone mode, the microgrid operates as an independent power island that is electrically separated from the main utility network. Fast islanding detection is, therefore, necessary for efficient and reliable microgrid operations. Many islanding detection methods (IdMs) are proposed in the literature, and each of them claims better reliability and high accuracy. This study describes a comprehensive review of various IdMs in terms of their merits, viability, effectiveness, and feasibility. The IdMs are extensively analysed by providing a fair comparison from different aspects. Moreover, a fair analysis of a feasible and economical solution in view of the recent research trend is presented.
Highlights
As the distributed generation (DG) industry continues its path of rapid growth and technological revolution, integrated power and energy networks are emerging as a fundamental enabling technology.With the increasing energy demands globally and fear of depleting conventional fossil fuels, the integration of DG networks has become essential [1]
This paper presents a comprehensive review of various islanding detection methods (IdMs) considering their performances and operational capabilities
The commonly used intelligent IdMs associated with signal processing techniques include the artificial neural network (ANN), decision tree (DT), probabilistic neural network (PNN), support vector machine (SVM), or fuzzy logic (FL)
Summary
As the distributed generation (DG) industry continues its path of rapid growth and technological revolution, integrated power and energy networks are emerging as a fundamental enabling technology. The influx of DG integration into the main utility networks is increasing rapidly Besides the advantages, such influx may cause some abnormal conditions in case of regular electrical faults or common power system disturbances [7]. If a DG unit and the main utility network are working in parallel to supply power to the load centres, the operation is known as a grid-connected mode [9]. In an islanding situation, the DG units are not capable enough to provide sufficient fault current in order to operate the conventional protection devices [15] Such an islanding can damage the system equipment, affect power system reliability, and endanger the maintenance worker’s life. The outline of the review report is presented as follows: Section 2 describes the problem definition and future challenges pertaining to islanding detection and microgrid systems.
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