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Islanding is one of the important challenges in power networks in the presence of distributed generation which is considered an undesirable incident due to the possibility of damage to operators, network equipment, and consumers. Therefore, it is necessary to quickly detect islanding and make a decision regarding the connection status of local distributed generation units in the network. In this paper, a passive islanding detection method is proposed using adaptive threshold-based instantaneous frequency droop characteristic. The proposed threshold limit is dynamically changed depending on under-studied conditions to discriminate the island from load changes, capacitor bank switching, motor start-up, and short circuit types. Two medium voltage networks of Cigre and 34-bus IEEE are used to evaluate the proposed method. The simulations are performed in Digsilent software and the proposed method is implemented in MATLAB software. The simulation results indicate that the island is correctly detected with appropriate accuracy in a short period of time from other disturbances in the presence of wind, solar and diesel types of distributed generations. [ABSTRACT FROM AUTHOR]

Islanding is one of the important challenges in power networks in the presence of distributed generation which is considered an undesirable incident due to the possibility of damage to operators, network equipment, and consumers. Therefore, it is necessary to quickly detect islanding and make a decision regarding the connection status of local distributed generation units in the network. In this paper, a passive islanding detection method is proposed using adaptive threshold-based instantaneous frequency droop characteristic. The proposed threshold limit is dynamically changed depending on under-studied conditions to discriminate the island from load changes, capacitor bank switching, motor start-up, and short circuit types. Two medium voltage networks of Cigre and 34-bus IEEE are used to evaluate the proposed method. The simulations are performed in Digsilent software and the proposed method is implemented in MATLAB software. The simulation results indicate that the island is correctly detected with appropriate accuracy in a short period of time from other disturbances in the presence of wind, solar and diesel types of distributed generations. [ABSTRACT FROM AUTHOR]