Voltage Dip Benchmarking in Power Quality and Disturbance Monitoring

This paper examines power quality benchmarks in the electricity supply industry (ESI) and impact of standards for the reduction of voltage dip incidents. The paper considers adherence to particular standards and is supported by several case studies from incidents where voltage dips have been detected and assessed by the power systems division of Scottish Power and where improvements have been implemented to help militate against subsequent incidents.

Development of a Bridge Weigh-in-Motion Sensor: Performance comparison using fibre optic and electric resistance strain sensor systems

This paper addresses the problems of effective in situ measurement of the real-time strain for bridge weigh in motion in reinforced concrete bridge structures through the use of optical fiber sensor systems. By undertaking a series of tests, coupled with dynamic loading, the performance of fiber Bragg grating-based sensor systems with various amplification techniques were investigated. In recent years, structural health monitoring (SHM) systems have been developed to monitor bridge deterioration, to assess load levels and hence extend bridge life and safety. Conventional SHM systems, based on measuring strain, can be used to improve knowledge of the bridge's capacity to resist loads but generally give no information on the causes of any increase in stresses. Therefore, it is necessary to find accurate sensors capable of capturing peak strains under dynamic load and suitable methods for attaching these strain sensors to existing and new bridge structures. Additionally, it is important to ensure accurate strain transfer between concrete and steel, adhesives layer, and strain sensor. The results show the benefits in the use of optical fiber networks under these circumstances and their ability to deliver data when conventional sensors cannot capture accurate strains and/or peak strains.

The performance of a cathodic protection system in reinforced concrete structure: Monitoring and Service Life Modelling

The use of cathodic protection in reinforced concrete is becoming increasingly common with such systems being installed on a number of structures throughout the United Kingdom and Ireland. However the prescribed design lives (or service life) of each cathodic protection system vary widely. The aim of this project was to assess the effectiveness of a sacrificial anode cathodic protection system and to predict its design life through a series of laboratory based experiments. The experimental plan involved casting a number of slabs which represented a common road bridge structure. The corrosion of the steel within the experimental slabs was then accelerated prior to installation of a cathodic protection system. During the experiment corrosion potential of the steel reinforcement was monitored using half-cell measurement. Additionally the current flow between the cathodic protection system and the steel reinforcement was recorded to assess the degree of protection. A combination of theoretical calculations and experimental results were then collated to determine the design life of this cathodic protection system. It can be concluded that this sacrificial anode based cathodic protection system was effective in halting the corrosion of steel reinforcement in the concrete slabs studied. Both the corrosion current and half-cell potentials indicated a change in passivity for the steel reinforcement once sacrificial anodes were introduced. The corrosion current was observed to be sensitive to the changes to the exposure environment. Based on the experimental variables studied the design life of this sacrificial anode can be taken as 26 to 30 years.

Hand-held voltammetric analyser for real-time monitoring of heavy metals in situ

This paper presents a novel hand-held instrument capable of real-time in situ detection and identification of heavy metals. The proposed system provides the facilities found in a traditional lab-based instrument in a hand held a design. In contrast to existing commercial systems, it can stand alone without the need of an associated computer. The electrochemical instrument uses anodic stripping voltammetry which is a precise and sensitive analytical method with excellent limits of detection. The sensors comprise disposable screen-printed (solid working) electrodes rather than the more common hanging mercury drop electrodes. The system is reliable, easy to use, safe, avoids expensive and time-consuming procedures and may be used in a variety of situations to help in the fields of environmental assessment and control.

PESSTO monitoring of SN 2012hn: further heterogeneity among faint Type I supernovae

We present optical and infrared monitoring data of SN 2012hn collectedby the Public European Southern Observatory Spectroscopic Survey forTransient Objects. We show that SN 2012hn has a faint peak magnitude(MR ˜ -15.65) and shows no hydrogen and no clearevidence for helium in its spectral evolution. Instead, we detectprominent Ca II lines at all epochs, which relates this transient topreviously described `Ca-rich' or `gap' transients. However, thephotospheric spectra (from -3 to +32 d with respect to peak) of SN2012hn show a series of absorption lines which are unique and a redcontinuum that is likely intrinsic rather than due to extinction. Linesof Ti II and Cr II are visible. This may be a temperature effect, whichcould also explain the red photospheric colour. A nebular spectrum at+150 d shows prominent Ca II, O I, C I and possibly Mg I lines whichappear similar in strength to those displayed by core-collapsesupernovae (SNe). To add to the puzzle, SN 2012hn is located at aprojected distance of 6 kpc from an E/S0 host and is not close to anyobvious star-forming region. Overall SN 2012hn resembles a group offaint H-poor SNe that have been discovered recently and for which aconvincing and consistent physical explanation is still missing. Theyall appear to explode preferentially in remote locations offset from amassive host galaxy with deep limits on any dwarf host galaxies,favouring old progenitor systems. SN 2012hn adds heterogeneity to thissample of objects. We discuss potential explosion channels includingHe-shell detonations and double detonations of white dwarfs as well aspeculiar core-collapse SNe.

Synchrophasor-Based Islanding Detection for Distributed Generation Systems Using Systematic Principal Component Analysis Approaches

Systematic principal component analysis (PCA) methods are presented in this paper for reliable islanding detection for power systems with significant penetration of distributed generations (DGs), where synchrophasors recorded by Phasor Measurement Units (PMUs) are used for system monitoring. Existing islanding detection methods such as Rate-of-change-of frequency (ROCOF) and Vector Shift are fast for processing local information, however with the growth in installed capacity of DGs, they suffer from several drawbacks. Incumbent genset islanding detection cannot distinguish a system wide disturbance from an islanding event, leading to mal-operation. The problem is even more significant when the grid does not have sufficient inertia to limit frequency divergences in the system fault/stress due to the high penetration of DGs. To tackle such problems, this paper introduces PCA methods for islanding detection. Simple control chart is established for intuitive visualization of the transients. A Recursive PCA (RPCA) scheme is proposed as a reliable extension of the PCA method to reduce the false alarms for time-varying process. To further reduce the computational burden, the approximate linear dependence condition (ALDC) errors are calculated to update the associated PCA model. The proposed PCA and RPCA methods are verified by detecting abnormal transients occurring in the UK utility network.

A novel radial basis function neural network principal component analysis scheme for PMU-based wide-area power system monitoring

A novel model-based principal component analysis (PCA) method is proposed in this paper for wide-area power system monitoring, aiming to tackle one of the critical drawbacks of the conventional PCA, i.e. the incapability to handle non-Gaussian distributed variables. It is a significant extension of the original PCA method which has already shown to outperform traditional methods like rate-of-change-of-frequency (ROCOF). The ROCOF method is quick for processing local information, but its threshold is difficult to determine and nuisance tripping may easily occur. The proposed model-based PCA method uses a radial basis function neural network (RBFNN) model to handle the nonlinearity in the data set to solve the no-Gaussian issue, before the PCA method is used for islanding detection. To build an effective RBFNN model, this paper first uses a fast input selection method to remove insignificant neural inputs. Next, a heuristic optimization technique namely Teaching-Learning-Based-Optimization (TLBO) is adopted to tune the nonlinear parameters in the RBF neurons to build the optimized model. The novel RBFNN based PCA monitoring scheme is then employed for wide-area monitoring using the residuals between the model outputs and the real PMU measurements. Experimental results confirm the efficiency and effectiveness of the proposed method in monitoring a suite of process variables with different distribution characteristics, showing that the proposed RBFNN PCA method is a reliable scheme as an effective extension to the linear PCA method.

Loss-of-Main Monitoring and Detection for Distributed Generations Using Dynamic Principal Component Analysis

In this paper, our previous work on Principal Component Analysis (PCA) based fault detection method is extended to the dynamic monitoring and detection of loss-of-main in power systems using wide-area synchrophasor measurements. In the previous work, a static PCA model was built and verified to be capable of detecting and extracting system faulty events; however the false alarm rate is high. To address this problem, this paper uses a well-known ‘time lag shift’ method to include dynamic behavior of the PCA model based on the synchronized measurements from Phasor Measurement Units (PMU), which is named as the Dynamic Principal Component Analysis (DPCA). Compared with the static PCA approach as well as the traditional passive mechanisms of loss-of-main detection, the proposed DPCA procedure describes how the synchrophasors are linearly
auto- and cross-correlated, based on conducting the singular value decomposition on the augmented time lagged synchrophasor matrix. Similar to the static PCA method, two statistics, namely T2 and Q with confidence limits are calculated to form intuitive charts for engineers or operators to monitor the loss-of-main situation in real time. The effectiveness of the proposed methodology is evaluated on the loss-of-main monitoring of a real system, where the historic data are recorded from PMUs installed in several locations in the UK/Ireland power system.

Evolving techniques for characterising and monitoring the stability of infrastructure slopes

Landslides and debris flows, commonly triggered by rainfall, pose a geotechnical risk causing disruption to transport routes and incur significant financial expenditure. With infrastructure maintenance budgets becoming ever more constrained, this paper provides an overview of some of the developing methods being implemented by Queen’s University, Belfast in collaboration with the Department for Regional Development to monitor the stability of two distinctly different infrastructure slopes in Northern Ireland. In addition to the traditional, intrusive ground investigative and laboratory testing methods, aerial LiDAR, terrestrial LiDAR, geophysical techniques and differential Global Positioning Systems have been used to monitor slope stability. Finally, a comparison between terrestrial LiDAR, pore water pressure and soil moisture deficit (SMD) is presented to outline the processes for a more informed management regime and to highlight the season relationship between landslide activity and the aforementioned parameters.

Monitoring Bridge Dynamic Behaviour using an Instrumented Two Axle Vehicle

Highway structures such as bridges are subject to continuous degradation primarily due to ageing, loading and environmental factors. A rational transport policy must monitor and provide adequate maintenance to this infrastructure to guarantee the required levels of transport service and safety. Increasingly in recent years, bridges are being instrumented and monitored on an ongoing basis due to the implementation of Bridge Management Systems. This is very effective and provides a high level of protection to the public and early warning if the bridge becomes unsafe. However, the process can be expensive and time consuming, requiring the installation of sensors and data acquisition electronics on the bridge. This paper investigates the use of an instrumented 2-axle vehicle fitted with accelerometers to monitor the dynamic behaviour of a bridge network in a simple and cost-effective manner. A simplified half car-beam interaction model is used to simulate the passage of a vehicle over a bridge. This investigation involves the frequency domain analysis of the axle accelerations as the vehicle crosses the bridge. The spectrum of the acceleration record contains noise, vehicle, bridge and road frequency components. Therefore, the bridge dynamic behaviour is monitored in simulations for both smooth and rough road surfaces. The vehicle mass and axle spacing are varied in simulations along with bridge structural damping in order to analyse the sensitivity of the vehicle accelerations to a change in bridge properties. These vehicle accelerations can be obtained for different periods of time and serve as a useful tool to monitor the variation of bridge frequency and damping with time.

Assessment Of various sensors for structural health monitoring for bridge weigh-in-motion (B-WIM).

In recent years, Structural Health Monitoring (SHM) systems have been developed to monitor bridge deterioration, assess real load levels and hence extend bridge life and safety. A road bridge is only safe if the stresses caused by the passing vehicles are less than the capacity of the bridge to resist them. Conventional SHM systems can be used to improve knowledge of the bridges capacity to resist stresses but generally give no information on the causes of any increase in stresses (based on measuring strain). The concept of in Bridge Weigh-in-Motion (B-WIM) is to establish axle loads, without interruption to traffic flow, by using strain sensors at a bridge soffit and subsequently converting the data to real time axle loads or stresses. Recent studies have shown it would be most beneficial to develop a portable system which can be easily attached to existing and new bridge structures for a specified monitoring period. The sensors could then be left in place while the data acquisition can be moved for various other sites. Therefore it is necessary to find accurate sensors capable of capturing peak strains under dynamic load and suitable methods for attaching these strain sensors to existing and new bridge structures. Additionally, it is important to ensure accurate strain transfer between concrete and steel, the adhesives layer and the strain sensor. This paper describes research investigating the suitably of using various sensors for the monitoring of concrete structures under dynamic vehicle load. Electrical resistance strain (ERS) gauges, vibrating wire (VW) gauges and fibre optic sensors (FOS) are commonly used for SHM. A comparative study will be carried out to select a suitable sensor for a bridge Weigh in Motion System. This study will look at fixing methods, durability, scanning rate and accuracy range. Finite element modeling is used to predict the strains which are then validated in laboratory trials.

A Novel Approach for Axle Detection in Bridge Weigh-In-Motion Systems

Bridge weigh-in-motion (B-WIM), a system that uses strain sensors to calculate the weights of trucks passing on bridges overhead, requires accurate axle location and speed information for effective performance. The success of a B-WIM system is dependent upon the accuracy of the axle detection method. It is widely recognised that any form of axle detector on the road surface is not ideal for B-WIM applications as it can cause disruption to the traffic (Ojio & Yamada 2002; Zhao et al. 2005; Chatterjee et al. 2006). Sensors under the bridge, that is Nothing-on-Road (NOR) B-WIM, can perform axle detection via data acquisition systems which can detect a peak in strain as the axle passes. The method is often successful, although not all bridges are suitable for NOR B-WIM due to limitations of the system. Significant research has been carried out to further develop the method and the NOR algorithms, but beam-and-slab bridges with deep beams still present a challenge. With these bridges, the slabs are used for axle detection, but peaks in the slab strains are sensitive to the transverse position of wheels on the beam. This next generation B-WIM research project extends the current B-WIM algorithm to the problem of axle detection and safety, thus overcoming the existing limitations in current state-of–the-art technology. Finite Element Analysis was used to determine the critical locations for axle detecting sensors and the findings were then tested in the field. In this paper, alternative strategies for axle detection were determined using Finite Element analysis and the findings were then tested in the field. The site selected for testing was in Loughbrickland, Northern Ireland, along the A1 corridor connecting the two cities of Belfast and Dublin. The structure is on a central route through the island of Ireland and has a high traffic volume which made it an optimum location for the study. Another huge benefit of the chosen location was its close proximity to a nearby self-operated weigh station. To determine the accuracy of the proposed B-WIM system and develop a knowledge base of the traffic load on the structure, a pavement WIM system was also installed on the northbound lane on the approach to the structure. The bridge structure selected for this B-WIM research comprised of 27 pre-cast prestressed concrete Y4-beams, and a cast in-situ concrete deck. The structure, a newly constructed integral bridge, spans 19 m and has an angle of skew of 22.7°.

A validated UPLC–MS/MS method for the surveillance of ten aquatic biotoxins in European brackish and freshwater systems

Over the past few decades, there has been an increased frequency and duration of cyanobacterial Harmful Algal Blooms (HABs) in freshwater systems globally. These can produce secondary metabolites called cyanotoxins, many of which are hepatotoxins, raising concerns about repeated exposure through ingestion of contaminated drinking water or food or through recreational activities such as bathing/ swimming. An ultra-performance liquid chromatography tandem mass spectrometry (UPLC–MS/MS) multi-toxin method has been developed and validated for freshwater cyanotoxins; microcystins-LR, -YR, -RR, -LA, -LY and -LF, nodularin, cylindrospermopsin, anatoxin-a and the marine diatom toxin domoic acid. Separation was achieved in around 9 min and dual SPE was incorporated providing detection limits of between 0.3 and 5.6 ng/L of original sample. Intra- and inter-day precision analysis showed relative
standard deviations (RSD) of 1.2–9.6% and 1.3–12.0% respectively. The method was applied to the analysis of aquatic samples (n = 206) from six European countries. The main class detected were the hepatotoxins; microcystin-YR (n = 22), cylindrospermopsin (n = 25), microcystin-RR (n = 17), microcystin-LR (n = 12), microcystin-LY (n = 1), microcystin-LF (n = 1) and nodularin (n = 5). For microcystins, the levels detected ranged from 0.001 to 1.51 mg/L, with two samples showing combined levels above the guideline set by the WHO of 1 mg/L for microcystin-LR. Several samples presented with multiple toxins indicating the potential for synergistic effects and possibly enhanced toxicity. This is the first published pan European survey of freshwater bodies for multiple biotoxins, including two identified for the first time; cylindrospermopsin in Ireland and nodularin in Germany, presenting further incentives for improved monitoring and development of strategies to mitigate human exposure.