Integration of renewable energy including solar energy is growing faster than ever before. Solar energy supplies more than 1.3% of global power, and it is predicted to become the largest electricity source by 2050 with about 11% of global power consumption. However, the improper installation, non-frequently scheduled maintenance, and aging effect can accelerate the deterioration of PV system components, which directly increase the possibility of arc fault occurrence. The undetected arc faults pose a severe fire hazard to residential, commercial, and utility-scaled PV systems. To deliver electricity in a safe and reliable manner, such a dangerous event must be detected at early stage. This paper presents a comprehensive review of the-state-of-art techniques for DC arc faults detection in photovoltaic systems (PV). Different methods and the features used for detection are discussed and compared in detail. This paper also emphasizes the importance of DC arc fault simulation for characteristics study and fault diagnosis purpose. Several DC arc fault models have been reviewed and compared.

A comprehensive review on DC arc faults and their diagnosis methods in photovoltaic systems

In the past decades, with the rapid development of modern technologies, a special kind of fault, the intermittent fault (IF) has become a serious threat to system securities. Although fruitful research results have been obtained for fault diagnosis, most of them are concerned with permanent faults. Furthermore, up to now, there has been no overview on the diagnosis techniques for IFs in dynamic systems. In fact, IFs are common in a variety of fields, whereas their research is far from mature and many open issues still remain to be solved. Therefore, in this overview, our main objective is to attract direct attentions from more researchers and engineers into the fascinating area of IF diagnosis. In this paper, the concept, research background, challenges and research motivations of IFs are introduced. Then, current research into diagnostics of IFs is reviewed, along with discussions on their strengths, limitations, and future directions.

Review on Diagnosis Techniques for Intermittent Faults in Dynamic Systems

Because of lack of current zero, dc arc is hard to be extinguished, which has become the main reason causing faults in dc system. To find an effective method to detect dc arc faults is of great significance. In this paper, a method for detecting dc arc fault based on electromagnetic radiation signal is presented. A dc arc generating device is designed to simulate dc arc faults caused by loose connection in dc systems. A fourth-order Hilbert curve fractal antenna is adopted to detect the electromagnetic radiation signals of dc arc. The amplitude and spectrums of electromagnetic radiation signals measured under different circuit currents are analyzed. A photovoltaic (PV) system is constructed and the dc arc generated in that system is measured. The test results show that, under the present experimental condition, the electromagnetic radiation pulses have an obvious characteristic frequency, which are in a range of 39–41 MHz. The characteristic frequency of electromagnetic radiation of dc arc generated in PV system is around 39 MHz. Moreover, the characteristic frequency of dc arc is compared with that of switch operation. The dc arc has higher characteristic frequency and longer interval of each electromagnetic radiation pulse than those of the switch operation. The results indicate that the characteristic frequency of electromagnetic radiation signals can be used as the detection parameter of dc arc.

A Novel DC Arc Fault Detection Method Based on Electromagnetic Radiation Signal

Protection devices are extensively utilized in direct current (DC) systems to ensure their normal operation and safety. However, series arc faults that establish current paths in the air between conductors introduce arc impedance to the system. Consequently, they can result in a decrease of current, and thus conventional protection devices may not be triggered. Undetected series arc faults can cause malfunctions and even lead to fire hazards. Therefore, a series arc-fault detection system is essential to DC systems to operate reliably and efficiently. In this paper, a series arc-fault detection system based on arc time-frequency signatures extracted by a modified empirical mode decomposition (EMD) technique and using a support vector machine (SVM) algorithm in decision making is proposed for DC systems. The oscillatory frequencies from the arc current are decomposed by the EMD with an analysis of the Hurst exponent ( ${H}$ ) to reject interference from the power electronics noise. ${H}$ analyzes the trend of a signal and the intrinsic oscillations of the signal are those with values of ${H}$ larger than 1/2. Comparing to traditional filters or wavelet transforms, this method does not require knowledge of the frequency range of the interference which varies from system to system. The capability and applicability of the proposed technique are validated in a photovoltaic system. The effectiveness of arc-fault detection is significantly improved by this technique because it can acquire sufficient and accurate arc signatures and it does not need to predefine various thresholds.

DC Arc-Fault Detection Based on Empirical Mode Decomposition of Arc Signatures and Support Vector Machine

Arc faults can produce very high temperatures and can easily ignite combustible materials; thus, they represent one of the most important causes of electrical fires. The application of arc fault detection, as an emerging early fire detection technology, is required by the National Electrical Code to reduce the occurrence of electrical fires. However, the concealment, randomness and diversity of arc faults make them difficult to detect. To improve the accuracy of arc fault detection, a novel arc fault detector (AFD) is developed in this study. First, an experimental arc fault platform is built to study electrical fires. A high-frequency transducer and a current transducer are used to measure typical load signals of arc faults and normal states. After the common features of these signals are studied, high-frequency energy and current variations are extracted as an input eigenvector for use by an arc fault detection algorithm. Then, the detection algorithm based on a weighted least squares support vector machine is designed and successfully applied in a microprocessor. Finally, an AFD is developed. The test results show that the AFD can detect arc faults in a timely manner and interrupt the circuit power supply before electrical fires can occur. The AFD is not influenced by cross talk or transient processes, and the detection accuracy is very high. Hence, the AFD can be installed in low-voltage circuits to monitor circuit states in real-time to facilitate the early detection of electrical fires.

https://www.mdpi.com/1424-8220/16/4/500/pdf

A Novel Arc Fault Detector for Early Detection of Electrical Fires

A feasibility study of utilizing radiated electromagnetic energy from spark/arc source as a means of detecting arcing faults is conducted using two types of simple antenna, stick and loop. From the investigation, it is concluded that arc/spark of low voltage can be detected by portable antennas with frequency bands of low amplitude modulation and megahertz as an alternative method to the conventional arcing detection methods and their apparatus. In addition, each of the first two phases of arc process, initial glow-like discharge and transient arc development, is distinguished by the respective inception time and radiation spectral content of the captured signals by the antennas.

Electromagnetic Radiation Behavior of Low-Voltage Arcing Fault

Leakage impulse current of the faulty insulators was experimentally studied. The leakage impulse current was characterized in terms of the phase-time base of the applied voltage. The study showed that the leakage impulse is observed only in a distinct location in phase-time space. Based on the findings, prioritized maintenance scheduling was proposed, which could be used for status monitoring of insulators and distribution feeders.

/pdf/phase-time-analysis-of-the-leakage-impulse-current-of-faulty-2p663yxwur.pdf

C.J. Kim

Papers

Electromagnetic Radiation Behavior of Low-Voltage Arcing Fault

Phase-time analysis of the leakage impulse current of faulty line-post pin insulators