Islanding detection method for grid connected photovoltaic systems

Abstract

The detection of islanding effect is one of the important issues for photovoltaic (PV) power system since islanding is dangerous to utility equipment and workers, and result in severe injuries and death. The novelty of this study is combining extension neural networks and Chaos synchronisation (CS) on islanding detection of grid connected PV systems based on non-autonomous Chua's circuit. Combining CS and extension neural network type-2 (ENN-2), this research is to propose a novel detection method at detecting and distinguishing the occurrence of islanding effect based on non-autonomous Chua's circuit. Simulation and experimental designs through powersim (PSIM) were applied to mimic PV power system to demonstrate the effectiveness of the proposed method. Results show that the accuracy of ENN-2 achieves 98.4% on detecting the islanding effect for PV power system.

Shifting of research trends in islanding detection method - a comprehensive survey

“…MPNN is used in [108] for islanding and power quality disturbance classification for a hybrid DG system. [109] combines chaos synchronization and type 2 ENN for ID for a grid connected Chua's circuit based PV system. It has 98.4% accuracy.…”

Application of the Extension Taguchi Method to Optimal Capability Planning of a Stand-alone Power System

“…The simulated experiment data cannot be compared or calculated for the unit reference value difference, thus it requires per-unit value calculation to get the physical quantity relative to the reference value [22]. The necessary equation is as shown in Equations (3) and (4).…”

“…If V o " xa, by and V p " xc, dy are two sections in the real domain, it shall firstly confirm the classical domain and the neighborhood domain before getting the matter-element in. Establishing the system's matter-element model, the defined classical domain is as Equation (21) and the neighborhood domain is as Equation (22). Defining the range according to the design factor demand, in extension theory, the classical domain is the expected value, and the neighborhood domain is the overall range.…”

An active frequency drift method for island problem of grid‐connected photovoltaic power generation system

“…Wang et al . proposed an island detection method combining extended neural network and chaotic synchronization, which was detected on the basis of nonautonomous Chua circuit and had a good detection effect. Do et al .…”