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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]

In this paper, a new method based on Adaptive Neuro-Fuzzy Inference System (ANFIS) is proposed for locating the switched capacitor banks in distribution systems. To train the proposed ANFIS model, an index based on current transient is introduced, which is calculated either offline by using data or online by real time simulation. The proposed method uses only current transient waveforms, immediately before and after the switching instant. Since only the current signal is used which is available in several locations, the method is simple and can be applied online. The method uses wavelet to determine the capacitor switching instant, which is needed for the ANFIS model to locate the switching capacitor. The method is simulated using PSCAD. Through various simulations, it is shown that other power quality disturbances such as voltage dip, unbalances and harmonics cannot disturb the method. Moreover, the size and connection type of the capacitor bank do not affect the method accuracy. The proposed algorithm is validated by simulating the IEEE 13-bus distribution system. According to the simulation results, the method is reliable enough to be applied to real systems. [ABSTRACT FROM AUTHOR]