Islanding detection for grid integrated distributed generation using adaptive neuro-fuzzy inference system

Intelligence Techniques in Sustainable Energy: Analysis of a Decade of Advances

“…For several reasons, islanding detection in gridlinked photovoltaic-based distributed power generation (PVDPG) systems is critical. This includes ensuring the safety of line workers and the general public, protecting consumer and utility equipment, preventing malfunctions of power system protective equipment, maintaining power quality, and strengthening the overarching security of the power system [129,130]. A significant challenge in devising reliable detection mechanisms lies in the inconsistent power output often associated with renewable energy sources like PVDPG, which can lead to voltage disturbances and unforeseen blackouts [131].…”

“…Numerous AI methodologies exhibit promise in islanding detection. For instance, ANFIS is an advanced technique for islanding detection, capitalizing on passive detection parameters such as voltage, frequency rate changes, and power variations [129,133]. Additionally, the synergy of LSTM networks with the empirical wavelet transform boosts the reliability of smart islanding detection [134].…”