This paper presents a fast hybrid fault location method for active distribution networks with distributed generation (DG) and microgrids. The method uses the voltage and current data from the measurement points at the main substation, and the connection points of DG and microgrids. The data is used in a single feedforward artificial neural network (ANN) to estimate the distances to fault from all the measuring points. A k-nearest neighbors (KNN) classifier then interprets the ANN outputs and estimates a single fault location. Simulation results validate the accuracy of the fault location method under different fault conditions including fault types, fault points, and fault resistances. The performance is also validated for non-synchronized measurements and measurement errors.

Summary This paper presents a protection method for microgrids by data mining of voltage disturbances. The occurrence of a fault on the system is associated with a sudden voltage depression, which is fast detected by the adaptive cumulative sum (ACUSUM) algorithm. There are other operational (no‐fault) events causing voltage depression such as motor starting, transformer energizing, and capacitor or heavy load switching. In order to discriminate between the fault and no‐fault events, one cycle of the voltage waveform is preprocessed by the short‐time Fourier transform (STFT) to extract and construct effective features of the disturbance. The features are then used in the decision trees (DTs) for the discrimination. The proposed protection method is tested for fault or no‐fault conditions of grid‐connected or islanded mode of the microgrid operation, as well as radial or meshed topology. The proposed method also identifies the fault type and faulted phase(s) for selective phase tripping. The immunity of the method against different noise levels is investigated. It is shown by the simulation study that by using only two features for symmetrical events and six features for asymmetrical events, any fault can be detected accurately.

Summary Protection is the main challenge for the operation of microgrids. This paper presents a new data mining method for identification of faulted line section for the protection of microgrids. This method uses wavelet packet transform (WPT) to extract a set of features from the fault voltage and current waveforms. The features are then pre‐processed and used for identifying the faulted line section through classification. Three classifiers are examined in this paper. In order to improve the classifiers performance, two pre‐processing steps are applied on the features. First, using three different feature selection methods, the irrelevant and redundant features are removed from the feature set. Secondly, using a supervised discretisation technique, the continuous features are converted into finite interval features. The performance of the proposed method is investigated and compared with previous methods using extensive simulation study on a complex microgrid. The results indicate that with only six discretised features, the proposed method has a fast and accurate performance by using the three classifiers examined, whereas one is more effective. Moreover, the proposed method only uses the measurement at the main substation, obviating the need for communication links to exchange data as used by most previous methods.

Traditional protection schemes are not adequate for the protection of microgrids because of bidirectional flow in feeders and reduced fault levels in islanded operations, thus it is needed a new protection scheme. This paper proposes a protection scheme that primarily depends on differential protection. In the event of primary protection failure, a robust backup protection is developed to isolate the fault after a certain time delay. It should be noted that the proposed primary protection scheme is applicable irrespective of the operational mode. Meanwhile, communication system plays a critical role on the protection of microgrid in the proposed protection strategy. This protection scheme is simulated on an 18-bus distribution system containing a high penetration of distributed energy resources and the climes made in this paper are evaluated using simulations. Index termsprotection of microgrid, distributed energy resources, digital relays, communication-aided protection I.High Low III. COMMUNICATION INFRASTRUCTURE A. Communication TechnologiesDifferential protection with its highest selectivity requires a reliable communication media for instantaneous data transfer between terminals of the protected elements. Such a communication system is capable of transferring the information in less than 2ms enables the main protection system to clear the fault in less than 6 cycles. The backup directional over current or over and under voltage protection will operate if primary protection scheme or the communication system fails.It is evident that the current communications infrastructure, which is characterized by a low-bandwidth and low data rate, does not meet the needs of microgrids and smart grids. The upgrade of that infrastructure is required. Different communication technologies supported by two main communication media, i.e., wired and wireless, can be used for data transmission between smart meters and electric utilities [16]. In some cases, wireless communications have some advantages over wired technologies including [17]:

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