In this paper, a method for fault locating in HVDC transmission lines is proposed which only uses the voltage signal measured at one of the line terminals. The postfault voltage signal, in a relatively short-time window, is considered and the corresponding fault location is estimated based on the similarity of the captured voltage signal to existing patterns. In this approach, the Pearson correlation coefficient is used to measure the similarity. Despite simplicity and low complexity of the proposed fault-location method, it does not suffer from the technical problems which are associated with the traveling-wave-based methods, such as the difficulty of identifying traveling wavefronts or the strong dependency of accuracy on the sampling frequency. Numerous training and test patterns are obtained by simulating various fault types in a long overhead HVDC transmission line under different fault location, fault resistance, and prefault current values. The accuracy of the proposed fault-location method is verified using these patterns.Index Terms-HVDC system, pattern recognition, similarity measure, single-end fault-location method.

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In this paper, some useful features are extracted from voltage signals measured at one terminal of the transmission line, which are highly efficient for accurate fault locating. These features are the amplitude of harmonic components, which are extracted after fault inception through applying discrete Fourier transform on one cycle of three-phase voltage signals and then are normalized by a transformation. In this paper, the location of single-line-toground faults as the most probable type of fault in the transmission networks is considered. The SLG fault locator, which is designed based on the simple algorithm of k-nearest neighbor ( -NN) in regression mode, estimates the location of fault related to the new input pattern based on existing available patterns. The proposed approach only needs the measured data from one terminal; hence, data communication between both ends of the line and synchronization are not required. In addition, current signals are not used; therefore, the proposed approach is immune against current-transformer saturation and its related errors. Tests conducted on an untransposed transmission line indicate that the proposed fault locator has accurate performance despite simultaneous changes in fault location, fault inception angle, fault resistance, and magnitude and direction of load current.

This article proposes a new passive islanding detection technique for inverter-based distributed generation (DG) in microgrids based on local synchrophasor measurements. The proposed method utilizes the voltage and current phasors measured at the DG connection point (point of connection, PoC). In this paper, the rate of change of voltages and the ratio of the voltage and current magnitudes (VoI index) at the PoC are monitored using micro-phasor measurement units. The developed local measurements based decentralized islanding detection technique is based on the VoI index in order to detect any kind of utility grid frequency fluctuations or oscillations and distinguishing them from islanding condition. The simulation studies confirm that the proposed scheme is accurate, robust, fast, and simple to implement for inverter-based DGs.

Original scientific paperHaving electricity with high quality is one of the more important aims in electrical systems. Disturbances in distribution systems can change voltage waveform. There are some methods to prepare high power quality for sensitive loads. In this research we use "Dynamic Voltage Restorer" to compensate the harmful effects of disturbances on voltage. Since power systems fundamentally have complicated dynamic behavior, especially during faults, "Hebb" learning self-tuning controller, which is a powerful adaptive controller, has been used. In order to improve the performance of this controller from point of view of power quality's indices, such as flash and sensitive load voltage THD, a new structure is proposed for this controller with fuzzification method. Simulation results indicate better operation of the system for the case of proposed controller. Voltage sag and harmonics in faulty conditions are both improved by the proposed controller. According to simulation results, it works better than both classical PI controller and conventional Hebb learning controller.Key words: DVR, Sensitive load, Power quality, Fuzzy membership function, Multi-objective Hebb learning algorithm, Self-tuning controller Promjena indikatora kvalitete električne energije trošila predstavljanjem adaptivne metode za upravljanje DVR-om zasnovane na Hebbovom algoritmu učenja. Jedan od važnijih ciljeva elektroenergetskog sustava visoka je kvaliteta električne energije. Poremećaji u distribucijskom sustavu mogu neželjeno izmijeniti valni oblik napona. Postoji nekoliko metoda kako osigurati visoku kvalitetu energije za osjetljiva trošila. U istraživanju koristimo "dinamičku obnovu napona" za kompenziranje štetnih efekata poremećaja u naponu. Kako energetski sustavi u osnovi imaju složeno dinamičko ponašanje, posebno tijekom kvarova, korišten je vrlo moćan adaptivni regulator: "Hebbov" samopodešavajući regulator sa sposobnošću učenja. Da bi se unaprijedilo vladanje spomenutog regulatora s aspekta indikatora kvalitete energije kao što su parcijalna izbijanja i THD osjetljivog trošila, predložena je nova struktura regulatora s uključenim metodama neizrazite logike. Simulacijski rezultati pokazuju bolji rad sustava uz korištenje predloženog regulatora. Regulator smanjuje propade napona i poboljšava harmonični sastav sustava u kvarnim uvjetima. Rezultati simulacija tako er pokazuju bolje ponašanje u odnosu na uobičajeni PI regulator te konvencionalni Hebbov regulator s učenjem.