Joe-Air Jiang

An adaptive PMU based fault detection/location technique for transmission lines. I. Theory and algorithms

An adaptive fault detection/location technique based on a phasor measurement unit (PMU) for an EHV/UHV transmission line is presented. A fault detection/location index in terms of Clarke components of the synchronized voltage and current phasors is derived. The line parameter estimation algorithm is also developed to solve the uncertainty of parameters caused by aging of transmission lines. This paper also proposes a new discrete Fourier transform (DFT) based algorithm (termed the smart discrete Fourier transform, SDFT) to eliminate system noise and measurement errors such that extremely accurate fundamental frequency components can be extracted for calculation of fault detection/location index. The EMTP was used to simulate a high voltage transmission line with faults at various locations. To simulate errors involved in measurements, Gaussian-type noise has been added to the raw output data generated by EMTP. Results have shown that the new DFT based method can extract exact phasors in the presence of frequency deviation and harmonics. The parameter estimation algorithm can also trace exact parameters very well. The accuracy of both new DFT based method and parameter estimation algorithm can achieve even up to 99.999% and 99.99% respectively, and is presented in Part II. The accuracy of fault location estimation by the proposed technique can achieve even up to 99.9% in the performance evaluation, which is also presented in Part II.

A New PMU-Based Fault Location Algorithm for Series Compensated Lines

This work presents a new fault location algorithm based on phasor measurement units (PMUs) for series compensated lines. Traditionally, the voltage drop of a series device is computed by the device model in the fault locator of series compensated lines, but by using this approach errors are induced by the inaccuracy of the series device model or the uncertainty operation mode of the series device. The proposed algorithm does not utilize the series device model or knowledge of the operation mode of the series device to compute the voltage drop during the fault period. Instead, the proposed algorithm uses the two-step algorithm, prelocation step and correction step, to calculate the voltage drop and fault location. The proposed technique can be easily applied to any series FACTS compensated line. EMTP generated data using a 300 km, 345 kV transmission line has been used to test the accuracy of the proposed algorithm. The tested cases include various fault types, fault locations, fault resistances, fault inception angles, etc. The study also considers the effect of various operation modes of the compensated device during the fault period. Simulation results indicate that the proposed algorithm can achieve up to 99.95% accuracy for most tested cases.

A New Adaptive PMU-Based Protection Scheme for Transposed/Untransposed Parallel Transmission Lines

This paper proposes a brand-new adaptive phasor measurement unit (PMU)-based protection scheme for both transposed and untransposed parallel transmission lines. The development of the scheme is based on the distributed line model and the synchronized phasor measurements at both ends of lines. The fault detection and location indices are derived by means of eigenvalue/eigenvector theory to decouple the mutual coupling effects between parallel lines. The two proposed indices are used in coordination such that the internal and external fault events can be distinguished completely. By on-line estimating the line parameters under the actual power system conditions, the proposed scheme will respond more accurately to power system faults. Extensive simulation results using EMTP have verified that the accuracy of the fault location achieved is up to 99.9%. The proposed protection system responds well and fast with regard to dependability and security. All the results show that the performance of the proposed detection/location indices is independent of fault types, locations, resistance, source impedance, fault inception angles, and load flows.

Transmission network fault location observability with minimal PMU placement

This paper presents a concept of fault-location observability and a new fault-location scheme for transmission networks based on synchronized phasor measurement units (PMUs). Using the proposed scheme, minimal PMUs are installed in existing power transmission networks so that the fault, if it occurs, can be located correctly in the network. The scheme combines the fault-location algorithm and the fault-side selector. Extensive simulation results verify the proposed scheme.

Closure on "A new protection scheme for fault detection, direction discrimination, classification, and location in transmission lines"

This paper presents a new adaptive fault protection scheme for transmission lines using synchronized phasor measurements. The work includes fault detection, direction discrimination, classification and location. Both fault detection and fault location indices are derived by using two-terminal synchronized measurements incorporated with distributed line model and modal transformation theory. The fault detection index is composed of two complex phasors and the angle difference between the two phasors determines whether the fault is intemal or external to the protected zone. The fault types can be classified by the modal fault detection index. The proposed scheme also combines on-line parameter estimation to assure protection scheme performance and to achieve adaptive protection. Extensive simulation studies show that the proposed scheme provides a fast relay response and high accuracy in fault location under various system and fault conditions. The proposed method responds very well with regard to dependability, security and sensitivity (high-resistance fault coverage).

A Hybrid Framework for Fault Detection, Classification, and Location—Part I: Concept, Structure, and Methodology

Bridging the gap between the theoretical modeling and the practical implementation is always essential for fault detection, classification, and location methods in a power transmission-line network. In this paper, a novel hybrid framework that is able to rapidly detect and locate a fault on power transmission lines is presented. The proposed algorithm presents a fault discrimination method based on the three-phase current and voltage waveforms measured when fault events occur in the power transmission-line network. Negative-sequence components of the three-phase current and voltage quantities are applied to achieve fast online fault detection. Subsequently, the fault detection method triggers the fault classification and fault-location methods to become active. A variety of methods-including multilevel wavelet transform, principal component analysis, support vector machines, and adaptive structure neural networks-are incorporated into the framework to identify fault type and location at the same time. This paper lays out the fundamental concept of the proposed framework and introduces the methodology of the analytical techniques, a pattern-recognition approach via neural networks and a joint decision-making mechanism. Using a well-trained framework, the tasks of fault detection, classification, and location are accomplished in 1.28 cycles, significantly shorter than the critical fault clearing time.

A Universal Fault Location Technique for N-Terminal

This paper presents a universal fault location technique for N-terminal transmission lines based on synchronized phasor measurement units. The development of the technique is based on two-terminal fault location technique. The proposed algorithm is different from traditional multiterminal fault location techniques. We apply two-terminal fault location technique to N-terminal transmission lines and propose a novel fault section selector/fault locator. The proposed method has a very good tolerance. The proposed approach provides an analytical solution and its computational burden is very low since it does not require iterative operations. An extensive series of simulations were conducted to verify the accuracy of the proposed algorithm. The average fault location error under various fault conditions is well below 1%.

({N}\geqq 3)

This paper presents a novel solution of a hand-held external controller to a miniaturized capsule endoscope in the gastrointestinal (GI) tract. Traditional capsule endoscopes move passively by peristaltic wave generated in the GI tract and the gravity, which makes it impossible for endoscopists to manipulate the capsule endoscope to the diagnostic disease areas. In this study, the main objective is to present an endoscopic capsule and a magnetic field navigator (MFN) that allows endoscopists to remotely control the locomotion and viewing angle of an endoscopic capsule. The attractive merits of this study are that the maneuvering of the endoscopic capsule can be achieved by the external MFN with effectiveness, low cost, and operation safety, both from a theoretical and an experimental point of view. In order to study the magnetic interactions between the endoscopic capsule and the external MFN, a magnetic-analysis model is established for computer-based finite-element simulations. In addition, experiments are conducted to show the control effectiveness of the MFN to the endoscopic capsule. Finally, several prototype endoscopic capsules and a prototype MFN are fabricated, and their actual capabilities are experimentally assessed via in vitro and ex vivo tests using a stomach model and a resected porcine stomach, respectively. Both in vitro and ex vivo test results demonstrate great potential and practicability of achieving high-precision rotation and controllable movement of the capsule using the developed MFN.

Transmission Lines

OBJECTIVE The purpose of this placebo-controlled study was to investigate the therapeutic effects of the 830-nm diode laser on carpal tunnel syndrome (CTS). BACKGROUND DATA Many articles in the literature have demonstrated that low-level laser therapy (LLLT) may help to alleviate various types of nerve pain, especially for CTS treatment. We placed an 830-nm laser directly above the transverse carpal ligament, which is between the pisiform and navicular bones of the tested patients, to determine the therapeutic effect of LLLT. MATERIALS AND METHODS Thirty-six patients with mild to moderate degree of CTS were randomly divided into two groups. The laser group received laser treatment (10 Hz, 50% duty cycle, 60 mW, 9.7 J/cm(2), at 830 nm), and the placebo group received sham laser treatment. Both groups received treatment for 2 wk consisting of a 10-min laser irradiation session each day, 5 d a week. The therapeutic effects were assessed on symptoms and functional changes, and with nerve conduction studies (NCS), grip strength assessment, and with a visual analogue scale (VAS), soon after treatment and at 2-wk follow-up. RESULTS Before treatment, there were no significant differences between the two groups for all assessments (p > 0.05). The VAS scores were significantly lower in the laser group than the placebo group after treatment and at follow-up (p < 0.05). After 2 wk of treatment, no significant differences were found in grip strengths or for symptoms and functional assessments (p > 0.05). However, there were statistically significant differences in these variables at 2-wk follow-up (p < 0.05). Regarding the findings of NCS, there was no statistically significant difference between groups after treatment and at 2-wk follow-up. CONCLUSIONS LLLT was effective in alleviating pain and symptoms, and in improving functional ability and finger and hand strength for mild and moderate CTS patients with no side effects.

Magnetic Control System Targeted for Capsule Endoscopic Operations in the Stomach—Design, Fabrication, and in vitro and ex vivo Evaluations

This paper focuses on localization that serves as a smart service. Among the primary services provided by Internet of Things (IoT), localization offers automatically discoverable services. Knowledge relating to an objects position, especially when combined with other information collected from sensors and shared with other smart objects, allows us to develop intelligent systems to fast respond to changes in an environment. Today, wireless sensor networks (WSNs) have become a critical technology for various kinds of smart environments through which different kinds of devices can connect with each other coinciding with the principles of IoT. Among various WSN techniques designed for positioning an unknown node, the trilateration approach based on the received signal strength is the most suitable for localization due to its implementation simplicity and low hardware requirement. However, its performance is susceptible to external factors, such as the number of people present in a room, the shape and dimension of an environment, and the positions of objects and devices. To improve the localization accuracy of trilateration, we develop a novel distributed localization algorithm with a dynamic-circle-expanding mechanism capable of more accurately establishing the geometric relationship between an unknown node and reference nodes. The results of real world experiments and computer simulation show that the average error of position estimation is 0.67 and 0.225 m in the best cases, respectively. This suggests that the proposed localization algorithm outperforms other existing methods.