Propagation of Electrical Trees under the Influence of Mechanical Stresses: A Short Review

The present paper deals with the phenomenon of electrical treeing in solid insulation, under the influence of mechanical stresses. In this short review, it is indicated that mechanical stressing can affect the propagation of electrical trees and –depending on whether it is tensile or compressive- it can facilitate (or render more difficult) the breakdown. In aged insulating materials, electrical trees can appear very quickly and can lead to breakdown

2017 3rd International Conference on Condition Assessment Techniques in Electrical Systems, CATCON 2017 - Proceedings

Very low frequency (VLF) high voltage testing had been used as a simple withstand test (go/no-go). Recently, VLF diagnostic testing has emerged as a promising tool for insulation assessment of power cables. The term VLF implies testing insulation with an excitation voltage at frequency of 0.1 Hz or lower. In this paper, a comparative analysis of the dielectric dissipation factor (DDF) or tanδ measurement is presented for 11-kV cross-linked polyethylene (XLPE) cable at power frequency (50 Hz) and at VLF. Here, the DDF response is measured from frequency 50 Hz to 0.1 Hz for four short cable sections where each sample has a capacitance lower than 300 pF. The experimental results show that the DDF value at 0.1 Hz is much higher than that at 50 Hz. Furthermore, differential tangent delta (DTD) and correlation of DDF values are calculated to incorporate with experimental results

Measurement and modeling of partial discharge arising from different cavity geometries at very low frequency

In this paper, a comparative study including measurement and modeling of partial discharge for various void geometries (cylinder, block, and prisms) at very low frequency (VLF) and power frequency (PF) voltage is presented. Results from experiments and simulations are presented with phase-resolved discharge patterns and integrated parameters (maximum/average discharge magnitudes, and repetition rates). Dynamic simulation, achieved using a combination of finite element analysis and Matlab, matches the experimental results. Differences of discharge characteristics between VLF and PF may be attributed to the physical mechanisms in the modeling including cavity surface conductivity and space charge decay rate. Compared with discharge activities at PF, the VLF excitation in general exhibits relatively lower discharge magnitude and repetition rate. Also, the inception voltage is found to be lower at VLF

Integration of electric vehicles and management in the internet of energy

Due to the environmental and energy crisis, many countries around the world are electrifying transportation, which will significantly change the way the current power grid operates. It is expected that the deployment of future smart grids will allow two-way energy and information flows through plug-and-play operation of small distributed mobile power generators like electric vehicles (EVs) to benefit the prosumers and at the same time make the grid more efficient and robust. However, the issues associated with the energy and information transfer, battery technologies, battery charging schemes, their standards and management need to be addressed in order to achieve the full benefits of EV integration in the future smart grids and internet of energy (IoE) with local renewable generation. As the current grid with existing infrastructure cannot ensure maximum benefits from EVs, this paper reviews the EV technologies, their connectivity, impacts on grid and standards required for the efficient and economic operation of EVs with distributed energy resources in the IoE. The evolution, comparison, and storage potential of EV technologies are thoroughly discussed. This paper also extensively reviews the connectivity issues, for example current EV charging schemes, software tools required to design smart charging, associated challenges, and possible solutions. The architecture of distributed energy management schemes with EVs and the IoE is discussed in detail. Finally, the standards related to EV integration, energy transfers, and safety aspects are provided. Based on the comprehensive review, future directions are put forward which will be useful for researchers and engineers working with EVs

Integration of electric vehicles and management in the internet of energy

© 2017 Elsevier Ltd Due to the environmental and energy crisis, many countries around the world are electrifying transportation, which will significantly change the way the current power grid operates. It is expected that the deployment of future smart grids will allow two-way energy and information flows through plug-and-play operation of small distributed mobile power generators like electric vehicles (EVs) to benefit the prosumers and at the same time make the grid more efficient and robust. However, the issues associated with the energy and information transfer, battery technologies, battery charging schemes, their standards and management need to be addressed in order to achieve the full benefits of EV integration in the future smart grids and internet of energy (IoE) with local renewable generation. As the current grid with existing infrastructure cannot ensure maximum benefits from EVs, this paper reviews the EV technologies, their connectivity, impacts on grid and standards required for the efficient and economic operation of EVs with distributed energy resources in the IoE. The evolution, comparison, and storage potential of EV technologies are thoroughly discussed. This paper also extensively reviews the connectivity issues, for example current EV charging schemes, software tools required to design smart charging, associated challenges, and possible solutions. The architecture of distributed energy management schemes with EVs and the IoE is discussed in detail. Finally, the standards related to EV integration, energy transfers, and safety aspects are provided. Based on the comprehensive review, future directions are put forward which will be useful for researchers and engineers working with EVs

Towards an internet of energy

The current model of centralized electricity generation, transmission and distribution is under pressure to change for a variety of reasons; environmental concerns are driving a shift away from large coal-fired generation systems to increasing adoption of renewable energy sources, which tend to be distributed and not always available on demand, and hence requiring distributed storage support. Moreover, to support electric vehicles, energy needs to be provided as a service to consumers independent of location, rather than a product delivered and billed to a fixed location. In this work, we compare and contrast modern internet and energy networks and services, identifying key functionalities and the main technical challenges to be faced in transforming the electricity distribution system to a flexible yet reliable and robust platform for the exchange of electrical energy.6 page(s

[[alternative]]Electroencephalography (EEG) Signal Acquisition System Design

[[abstract]]　　為了解腦電活動，腦電 (EEG) 信號記錄了頭皮間所發出的微弱信號，也提供大腦動態活動表現的波形。本研究致力於電路設計和設備開發，用以實現所需之腦波電 (EEG) 信號擷取系統。採集信號需要一定強度的幅度，通常以毫伏為單位表示 (millivolts)。一般而言，數據擷取過程含了三個階段：1)原始EEG信號的擷取可以通過有源電極和具有較小增益的儀表放大器完成；2)使用帶通濾波器和帶斥濾波器改善信號質量；3)將EEG信號透過內嵌於微控制器的類比-數位轉換器(ADC)來轉換成數位碼。數位碼可再儲存於記憶體中，並由藍牙模組進一步傳輸。實驗結果說明該系統可以有效地實現EEG信號的擷取和存儲。設計的印刷電路板(PCB)尺寸小於5×5 cm2。所提出之系統將有益於所有參與使用EEG進行臨床診斷和監測人員，腦機介面開發。[[abstract]]　　Electroencephalography (EEG) signals are recorded for knowing the electrical activity of brain from the scalp, and the recorded waveform provides acquits into the dynamic aspects of brain activity. This study incorporates the circuit design and device development to achieve the Electroencephalography (EEG) signal acquisition front-end circuit design for future Brain Computer Interface (BCI) applications. The amplitude of acquired signals should be strong enough and is usually expressed in unit of millivolts. The data acquisition procedure consists three stages: 1) The acquisition of original EEG signal can be done by the active electrode and an instrumentation amplifier with a smaller gain; 2) Improves the signal quality by using band-pass filter and band-stop filter; 3) Those EEG signals were converted into the digital code through the analog-to-digital converter (ADC) that was integrated to a micro-controller. The digital code is stored into an embedded memory, and is further transmitted via Bluetooth module. The experimental results show that the system could implement the acquisition and storage of the EEG signals efficiently. The size of printed circuit board (PCB) for the proposed deign is smaller than 5×5 cm2. This system would be benefit to all involve in the use of EEG for clinical diagnosis and monitoring, or even for brain computer interface