Effects of VSC based HVDC system on distance protection of transmission lines

The priority to reactive power contribution from the Voltage Source Converter (VSC) based High Voltage Direct Current (HVDC) connection to support the grid during faults as suggested by the modern Network Code (NC) for HVDC affects the distance protection of transmission lines. Moreover, suppressing the negative sequence current during an unbalanced condition also interferes with the proper operation of the distance relays. This is because the current contribution from the converter is limited in magnitude and modified in the waveform in order to protect the power electronic devices during the fault in comparison to the synchronous generator fault current characteristics. This paper discusses the cause as well as the severity of the problems faced by the distance protection of transmission lines connected to the VSC based HVDC system by analyzing the apparent impedance analytically and in the simulation. The response of the relay to balanced and unbalanced faults lying on transmission lines is investigated. It is shown that the VSC limited reactive support and suppressed negative sequence current affect fault detection, forcing the relay to malfunction. The results of this paper can be used as a reference for understanding the effects of VSC-HVDC system on the operation of the distance protection during faults.     

Assessing the width of Gaussian density of states in organic semiconductors

The Density of States (DOS) is an ingredient of critical importance for the accurate physical understanding of the optoelectronic properties of organic semiconductors. The disordered nature of this class of materials, though, renders the task of determining the DOS far from trivial. Its extraction from experimental measurements is often performed by driving the semiconductor out of thermal equilibrium and therefore requires making assumptions on the charge transport properties of the material under examination. This entanglement of DOS and charge transport models is unfavorable since transport mechanisms in organic semiconductors are themselves still subject of debate. To avoid this, we propose an alternative approach which is based on populating and probing the DOS by means of capacitive coupling in Metal Insulator Semiconductors (MIS) structures while keeping the semiconductor in thermal equilibrium. Assuming a Gaussian shape, we extract the DOS width by numerical fitting of experimental Capacitance–Voltage curves, exploiting the fact that the DOS width affects the spatial distribution of accumulated charge carriers which in turn concurs to define the MIS capacitance. The proposed approach is successfully tested on two benchmark semiconducting polymers, one of n-type and one of p-type and it is validated by verifying the robustness of the extraction procedure with respect to varying the insulator electrical permittivity. Finally, as an example of the usefulness and effectiveness of our approach, we study the static characteristics of thin film transistors based on the aforementioned polymers in the framework of the Extended Gaussian Disorder transport model. Thanks to the extracted DOS widths, the functional dependence of current on the gate voltage is nicely predicted and physical insight on transistor operation is achieved.     

Process variability-induced NoC link failure: A probabilistic model

As technology scales down, the amount of process variations increases causing Networks-on-Chip (NoC) links, designed to be identical, to have current and delay variations. Thus, some links may fail to meet design timing or power constraints. Using current and delay variations with design constraints, we estimate link failure probability across NoC links. Modeling results show that the average NoC link failure probability across a 4×4 mesh reaches 3.3% for voltage mode (VM) links and 3.7% for current mode (CM) links at 32 nm. The average NoC link failure probability also increases as the supply voltage decreases or the operating frequency increases. As NoC mesh size scales from 4×4 to 8×8, the link failure probability doubles to 8% for VM links at 22 nm. Topology evaluation shows that for small NoC size, the grid topology outperforms the tree one with lower amount of variation. On the other hand, for relatively large NoC sizes, the hierarchical tree and ring topologies outperform the grid topology with lower amount of variations across the links.     

Direct model-based predictive control scheme without cost function for voltage source inverters with reduced common-mode voltage

This paper presents a direct model-based predictive control scheme for voltage source inverters (VSIs) with reduced common-mode voltages (CMVs). The developed method directly finds optimal vectors without using repetitive calculation of a cost function. To adjust output currents with the CMVs in the range of –V_dc/6 to +V_dc/6, the developed method uses voltage vectors, as finite control resources, excluding zero voltage vectors which produce the CMVs in the VSI within ±V_dc/2. In a model-based predictive control (MPC), not using zero voltage vectors increases the output current ripples and the current errors. To alleviate these problems, the developed method uses two non-zero voltage vectors in one sampling step. In addition, the voltage vectors scheduled to be used are directly selected at every sampling step once the developed method calculates the future reference voltage vector, saving the efforts of repeatedly calculating the cost function. And the two non-zero voltage vectors are optimally allocated to make the output current approach the reference current as close as possible. Thus, low CMV, rapid current-following capability and sufficient output current ripple performance are attained by the developed method. The results of a simulation and an experiment verify the effectiveness of the developed method.     

Multi-purpose droop controllers incorporating a passivity-based stabilizer for unified control of electronically interfaced distributed generators including primary source dynamics

This paper presents multi-purpose droop controllers for electronically-interfaced distributed generators (EI-DGs). These controllers allow the micro-grids to operate in grid-connected mode, islanded mode and mode transition transients with a unique control configuration. The active and reactive-power sharing among EI-DGs are satisfied by the proposed droop controllers in islanded mode. On the other hand, in the grid-connected mode, the droop controllers adjust the output active and reactive-powers of EI-DGs at the pre-programmed constant levels. The provision of sufficient damping capability and maintenance of the transient stability in all operational modes of EI-DGs are warranted by the suggested stabilizer. This stabilizer, which is designed using the passivity-based control (PBC) approach, is incorporated in the droop controllers to dampen power-angle, frequency and voltage deviations during large transients using solely local information. The primary source dynamics of EI-DGs are also considered. It is analytically proven that the presence of the primary source dynamics leads to attenuation of the damping capability of EI-DGs in transients. To compensate the adverse effect of the primary source dynamics during transients a novel compensator is inserted in the frequency-droop loop. Finally, time-domain simulations are performed on a multi-resources MG to verify the analytical results compared to those obtained, based on a recently-developed strategy.     

建筑物低压电气火灾智能预防系统的研制

在建筑火灾未发生或刚开始时，及时发现并实施扑救，是防止建筑火灾造成重大损失的关键。本文主要研制了一个智能火灾预防系统。该系统运用自主研发的新型火灾预防检测电缆作为主要传感器，集成智能检测模块和电脑网络技术，具有高效、经济、安全、可靠的特性。     

Some Statistical Aspects of the Economics of Analytical Testing

In establishing an economical testing program the costs of routine analytical tests must be weighed against losses due to shipping material which is either above or below stated specifications. A method for obtaining an optimum sampling and testing procedure is described and examples given.     

A Bayesian approach to model dispersal for decision support

In agricultural and environmental sciences dispersal models are often used for risk assessment to predict the risk associated with a given configuration and also to test scenarios that are likely to minimise those risks. Like any biological process, dispersal is subject to biological, climatic and environmental variability and its prediction relies on models and parameter values which can only approximate the real processes. In this paper, we present a Bayesian method to model dispersal using spatial configuration and climatic data (distances between emitters and receptors; main wind direction) while accounting for uncertainty, with an application to the prediction of adventitious presence rate of genetically modified maize (GM) in a non-GM field. This method includes the design of candidate models, their calibration, selection and evaluation on an independent dataset. A group of models was identified that is sufficiently robust to be used for prediction purpose. The group of models allows to include local information and it reflects reliably enough the observed variability in the data so that probabilistic model predictions can be performed and used to quantify risk under different scenarios or derive optimal sampling schemes.     

The Flexible Rare Event Sampling Harness System (FRESHS)

We present the software package FRESHS (http://www.freshs.org) for parallel simulation of rare events using sampling techniques from the ‘splitting’ family of methods. Initially, Forward Flux Sampling (FFS) and Stochastic Process Rare Event Sampling (SPRES) have been implemented. These two methods together make rare event sampling available for both quasi-static and full non-equilibrium regimes. Our framework provides a plugin system for software implementing the underlying physics of the system of interest. At present, example plugins exist for our framework to steer the popular MD packages GROMACS, LAMMPS and ESPResSo, but due to the simple interface of our plugin system, it is also easy to attach other simulation software or self-written code. Use of our framework does not require recompilation of the simulation program. The modular structure allows the flexible implementation of further sampling methods or physics engines and creates a basis for objective comparison of different sampling algorithms.