Identification of Permanent Faults and Disturbance Induced by Deicing Based on Permutation Entropy for the Large-Scale Clean Energy Transmission in Winter

Ice shedding may induce isolated ground wires’ temporary grounding, which can cause electric quantities of direct current (DC) deicing devices to fluctuate. Hence, the disturbance of ice shedding is able to trigger the protective relay frequently and unnecessarily, which adversely affects the deicing process. Due to the randomness of ice shedding, the grounding resistance varies quickly; thus, the disturbance in poles of deicing devices can be detected multiple times in a short time. Moreover, the permanent fault requires steady arc plasma because of the low output voltage and current of deicing devices, which cannot bring out multiple-time disturbances in the poles. This paper proposes the identification of permanent faults and disturbance induced by deicing based on the permutation entropy, which is verified by a large number of simulations.

Comprehensive power swing detection by current signal modeling and prediction using the GMDH method

Power swing is an undesirable variation in power flow. This can be caused by large disturbances in demand load, switching, disconnection or reclosing lines. This phenomenon may enter the zones of distance relays and cause relay malfunction leading to the disconnection of healthy lines and undermining network reliability. Accordingly, this paper presents a new power swing detection method based on the prediction of current signal with a GMDH (Group Method of Data Handling) artificial neural network. The main advantage of the proposed method over its counterparts is the immunity to noise effect in signals. In addition, the proposed method can detect stable, unstable, and multi-mode power swings and is capable of distinguishing them from the variety of permanent faults occurring simultaneously. The method is tested for different types of power swings and simultaneous faults using DIgSILENT and MATLAB, and compared with some latest power swing detection methods. The results demonstrate the superiority of the proposed method in terms of response time, the ability to detect power swings of different varieties, and the ability to detect different faults that may occur simultaneously with power swings.

DYRE: a DYnamic REconfigurable solution to increase GPGPU’s reliability

General-purpose graphics processing units (GPGPUs) are extensively used in high-performance computing. However, it is well known that these devices’ reliability may be limited by the rising of faults at the hardware level. This work introduces a flexible solution to detect and mitigate permanent faults affecting the execution units in these parallel devices. The proposed solution is based on adding some spare modules to perform two in-field operations: detecting and mitigating faults. The solution takes advantage of the regularity of the execution units in the device to avoid significant design changes and reduce the overhead. The proposed solution was evaluated in terms of reliability improvement and area, performance, and power overhead costs. For this purpose, we resorted to a micro-architectural open-source GPGPU model (FlexGripPlus). Experimental results show that the proposed solution can extend the reliability by up to 57%, with overhead costs lower than 2% and 8% in area and power, respectively.

Multi-Objective Evolutionary Algorithm for Service Restoration in the Presence of Distributed Generation

Distributed Generators (DGs) have been used to improve quality and reliability of service in Distribution Systems (DSs). They can be used to reduce faults impact on System Average Interruption Duration Index by allowing the minimization of healthy out-ofservice (OFS) loads after the occurrence of permanent faults. IEEE also encourages power supply companies and customers to restore OFS loads by intentional islanding. This paper proposes a modification in recently proposed Multi-Objective Evolutionary Algorithm (MOEA) in subpopulation tables to combine intentional islanding of DGs with network reconfiguration to maximize restoration of OFS loads. The idea is to force intentional islanding whenever OFS heathy areas can be fully supplied by DGs. Simulation results (with a DS presented in the literature) have demonstrated the reliability of the MOEA new version to deal with service restoration problem in the presence of DGs.

Resource Management for Improving Overall Reliability of Multi-Processor Systems-on-Chip

Multi-processor systems on a chip (MPSoCs) are widely deployed in real-time embedded systems. In such systems, soft-error reliability (caused by transient faults) and lifetime reliability (caused by permanent faults) are both imperative design concerns. Most existing work considers only one of the two classes of faults. Unfortunately, techniques that increase one may adversely impact the other. Achieving high overall reliability requires a trade-off of soft-error reliability and lifetime reliability. In this chapter, we first introduce concepts and models associated with the two reliability metrics, then present two techniques that optimize them separately. Finally, we show how to make appropriate trade-offs using two case studies involving “big–little” type MPSoCs and CPU–GPU integrated MPSoCs.