Distributed Adaptive Learning Framework for Wide Area Monitoring of Power Systems Integrated with Distributed Generations

This paper presents a preliminary study of developing a novel distributed adaptive real-time learning framework for wide area monitoring of power systems integrated with distributed generations using synchrophasor technology. The framework comprises distributed agents (synchrophasors) for autonomous local condition monitoring and fault detection, and a central unit for generating global view for situation awareness and decision making. Key technologies that can be integrated into this hierarchical distributed learning scheme are discussed to enable real-time information extraction and knowledge discovery for decision making, without explicitly accumulating and storing all raw data by the central unit. Based on this, the configuration of a wide area monitoring system of power systems using synchrophasor technology, and the functionalities for locally installed open-phasor-measurement-units (OpenPMUs) and a central unit are presented. Initial results on anti-islanding protection using the proposed approach are given to illustrate the effectiveness.

True navigation in birds: from quantum physics to global migration

Birds are capable of true navigation, the ability to return to a known goal from a place they have never visited before. This is demonstrated most spectacularly during the vast migratory journeys made by these animals year after year, often between continents and occasionally global in nature. However, it remains one of the great unanswered questions in science, despite more than 50 years of research in this field. Nevertheless, the study of true navigation in birds has made significant advances in the previous 20 years, in part thanks to the integration of many disciplines outside its root in behavioural biology, to address questions of neurobiology, molecular aspects, and the physics of sensory systems and environmental cues involved in bird navigation, often involving quantum physics. However, true navigation remains a controversial field, with many conflicting and confusing results making interpretation difficult, particularly for those outside or new to the field. Unlike many general texts on migration, which avoid discussion of these issues, this review will present these conflicting findings and assess the state of the field of true navigation during bird migration.

A drive-by inspection system via vehicle moving force identification

This paper presents a novel method to carry out monitoring of transport infrastructure such as pavements and bridges through the analysis of vehicle accelerations. An algorithm is developed for the identification of dynamic vehicle-bridge interaction forces using the vehicle response. Moving force identification theory is applied to a vehicle model in order to identify these dynamic forces between the vehicle and the road and/or bridge. A coupled half-car vehicle-bridge interaction model is used in theoretical simulations to test the effectiveness of the approach in identifying the forces. The potential of the method to identify the global bending stiffness of the bridge and to predict the pavement roughness is presented. The method is tested for a range of bridge spans using theoretical simulations and the influences of road roughness and signal noise on the accuracy of the results are investigated.

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.

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.

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 of a novel FlexiArchTM bridge system to investigate soil-structure interaction

Masonry arch bridges are one of the oldest forms of bridge construction and have been around for thousands of years. Brick and stone arch bridges have proven to be highly durable as most of them have remained serviceable after hundreds of years. In contrast, many bridges built of modern materials have required extensive repair and strengthening after being in service for a relatively short part of their design life. This paper describes the structural monitoring of a novel flexible concrete arch known as: FlexiArchTM. This is a bridge system that can be transported as a flat-pack system to form an arch in-situ by the use of a flexible polymeric membrane. The system has been developed under a Knowledge Transfer Partnership between Queen’s University Belfast (QUB) and Macrete Ltd. Tievenameena Bridge in Northern Ireland was a replacement bridge for the Northern Ireland Roads Service and was monitored under different axle loadings using a range of sensors including discrete fiber optic Bragg gratings to measure the change in strain in the arch ring under live loading. This paper discusses the results of a laboratory model study carried out at QUB. A scaled arch system was loaded with a simulated moving axle. Various techniques were used to monitor the arch under the moving axle load with particular emphasis on the interaction of the arch ring and engineered backfill.