Optimal allocation and sizing of capacitors to minimize the transmission line loss and to improve the voltage profile

To allocate and size capacitors in a distribution system, an optimization algorithm, called Discrete Particle Swarm Optimization (DPSO), is employed in this paper. The objective is to minimize the transmission line loss cost plus capacitors cost. During the optimization procedure, the bus voltage, the feeder current and the reactive power flowing back to the source side should be maintained within standard levels. To validate the proposed method, the semi-urban distribution system that is connected to bus 2 of the Roy Billinton Test System (RBTS) is used. This 37-bus distribution system has 22 loads being located in the secondary side of a distribution substation (33/11 kV). Reducing the transmission line loss in a standard system, in which the transmission line loss consists of only about 6.6 percent of total power, the capabilities of the proposed technique are seen to be validated.

Towards automatic power line detection for a UAV surveillance system using pulse coupled neural filter and an improved Hough transform

Spatial information captured from optical remote sensors on board unmanned aerial vehicles (UAVs) has great potential in automatic surveillance of electrical infrastructure. For an automatic vision-based power line inspection system, detecting power lines from a cluttered background is one of the most important and challenging tasks. In this paper, a novel method is proposed, specifically for power line detection from aerial images. A pulse coupled neural filter is developed to remove background noise and generate an edge map prior to the Hough transform being employed to detect straight lines. An improved Hough transform is used by performing knowledge-based line clustering in Hough space to refine the detection results. The experiment on real image data captured from a UAV platform demonstrates that the proposed approach is effective for automatic power line detection.

Classification of Airborne LIDAR Intensity Data Using Statistical Analysis and Hough Transform with Application to Power Line Corridors

Light Detection and Ranging (LIDAR) has great potential to assist vegetation management in power line corridors by providing more accurate geometric information of the power line assets and vegetation along the corridors. However, the development of algorithms for the automatic processing of LIDAR point cloud data, in particular for feature extraction and classification of raw point cloud data, is in still in its infancy. In this paper, we take advantage of LIDAR intensity and try to classify ground and non-ground points by statistically analyzing the skewness and kurtosis of the intensity data. Moreover, the Hough transform is employed to detected power lines from the filtered object points. The experimental results show the effectiveness of our methods and indicate that better results were obtained by using LIDAR intensity data than elevation data.

Sustainable urban development : a quadruple bottom line assessment framework

Sustainable development has long been promoted as the best answer to the world's environmental problems. This term has generated mass appeal as it implies that the development of the built environment and its associated resource consumption can both be achieved without jeopardising the natural environment. In the urban context, sustainability issues have been reflected in the pomotion of sustainable urbanisation in a manner that allows future generations to repeat this process. This paper attempts to highlight an increasing urgency in formulating a suitable model for assessing sustainability at urban level, because this is where the bulk of a nation's population reside, and where sustainability problems mostly occur. It will also point out to the increasing importance of governance in facilitating urban sustainability research. This assessment involves the use of physical, social, environmental and goverance aspects in assessing the extent to which development of an urban settlement is sustainable. Specifically, this assessment model is carried out to determine whether or not sustainable urban development pratice is implemented in the provision of residential development, and in particular whether the development of master-planned residential communities have more desireable outcomes compared to traditional residential subdivision.

Evaluation of aerial remote sensing techniques for vegetation management in power line corridors

The following paper presents an evaluation of airborne sensors for use in vegetation management in powerline corridors. Three integral stages in the management process are addressed including, the detection of trees, relative positioning with respect to the nearest powerline and vegetation height estimation. Image data, including multi-spectral and high resolution, are analyzed along with LiDAR data captured from fixed wing aircraft. Ground truth data is then used to establish the accuracy and reliability of each sensor thus providing a quantitative comparison of sensor options. Tree detection was achieved through crown delineation using a Pulse-Coupled Neural Network (PCNN) and morphologic reconstruction applied to multi-spectral imagery. Through testing it was shown to achieve a detection rate of 96%, while the accuracy in segmenting groups of trees and single trees correctly was shown to be 75%. Relative positioning using LiDAR achieved a RMSE of 1.4m and 2.1m for cross track distance and along track position respectively, while Direct Georeferencing achieved RMSE of 3.1m in both instances. The estimation of pole and tree heights measured with LiDAR had a RMSE of 0.4m and 0.9m respectively, while Stereo Matching achieved 1.5m and 2.9m. Overall a small number of poles were missed with detection rates of 98% and 95% for LiDAR and Stereo Matching.

The importance of a triple bottom line approach for safeguarding urban water quality

Water environments are greatly valued in urban areas as ecological and aesthetic assets. However, it is the water environment that is most adversely affected by urbanisation. Urban land use coupled with anthropogenic activities alters the stream flow regime and degrade water quality with urban stormwater being a significant source of pollutants. Unfortunately, urban water pollution is difficult to evaluate in terms of conventional monetary measures. True costs extend beyond immediate human or the physical boundaries of the urban area and affect the function of surrounding ecosystems. Current approaches for handling stormwater pollution and water quality issues in urban landscapes are limited as these are primarily focused on ‘end-of-pipe’ solutions. The approaches are commonly based either on, insufficient design knowledge, faulty value judgements or inadequate consideration of full life cycle costs. It is in this context that the adoption of a triple bottom line approach is advocated to safeguard urban water quality. The problem of degradation of urban water environments can only be remedied through innovative planning, water sensitive engineering design and the foresight to implement sustainable practices. Sustainable urban landscapes must be designed to match the triple bottom line needs of the community, starting with ecosystem services first such as the water cycle, then addressing the social and immediate ecosystem health needs, and finally the economic performance of the catchment. This calls for a cultural change towards urban water resources rather than the current piecemeal and single issue focus approach. This paper discusses the challenges in safeguarding urban water environments and the limitations of current approaches. It then explores the opportunities offered by integrating innovative planning practices with water engineering concepts into a single cohesive framework to protect valuable urban ecosystem assets. Finally, a series of recommendations are proposed for protecting urban water resources within the context of a triple bottom line approach.

Investigation of 'off-line‘ relaxation phenomena in oil filled transformers

Power transformers are one of the most important and costly equipment in power generation, transmission and distribution systems. Current average age of transformers in Australia is around 25 years and there is a strong economical tendency to use them up to 50 years or more. As the transformers operate, they get degraded due to different loading and environmental operating stressed conditions. In today‘s competitive energy market with the penetration of distributed energy sources, the transformers are stressed more with minimum required maintenance. The modern asset management program tries to increase the usage life time of power transformers with prognostic techniques using condition indicators. In the case of oil filled transformers, condition monitoring methods based on dissolved gas analysis, polarization studies, partial discharge studies, frequency response analysis studies to check the mechanical integrity, IR heat monitoring and other vibration monitoring techniques are in use. In the current research program, studies have been initiated to identify the degradation of insulating materials by the electrical relaxation technique known as dielectrometry. Aging leads to main degradation products like moisture and other oxidized products due to fluctuating thermal and electrical loading. By applying repetitive low frequency high voltage sine wave perturbations in the range of 100 to 200 V peak across available terminals of power transformer, the conductive and polarization parameters of insulation aging are identified. An in-house novel digital instrument is developed to record the low leakage response of repetitive polarization currents in three terminals configuration. The technique is tested with known three transformers of rating 5 kVA or more. The effects of stressing polarization voltage level, polarizing wave shapes and various terminal configurations provide characteristic aging relaxation information. By using different analyses, sensitive parameters of aging are identified and it is presented in this thesis.

A new method for improving reliability and line loss in distribution networks

In this paper, both Distributed Generators (DG) and capacitors are allocated and sized optimally for improving line loss and reliability. The objective function is composed of the investment cost of DGs and capacitors along with loss and reliability which are converted to the genuine dollar. The bus voltage and line current are considered as constraints which should be satisfied during the optimization procedure. Hybrid Particle Swarm Optimization as a heuristic based technique is used as the optimization method. The IEEE 69-bus test system is modified and employed to evaluate the proposed algorithm. The results illustrate that the lowest cost planning is found by optimizing both DGs and capacitors in distribution networks.

Overhead electricity line connector tester

Assessment of the condition of connectors in the overhead electricity network has traditionally relied on the heat dissipation or voltage drop from existing load current (50Hz) as a measurable parameter to differentiate between satisfactory and failing connectors. This research has developed a technique which does not rely on the 50Hz current and a prototype connector tester has been developed. In this system a high frequency signal is injected into the section of line under test and measures the resistive voltage drop and the current at the test frequency to yield the resistance in micro-ohms. From the value of resistance a decision as to whether a connector is satisfactory or approaching failure can be made. Determining the resistive voltage drop in the presence of a large induced voltage was achieved by the innovative approach of using a representative sample of the magnetic flux producing the induced voltage as the phase angle reference for the signal processing rather than the phase angle of the current, which can be affected by the presence of nearby metal objects. Laboratory evaluation of the connector tester has validated the measurement technique. The magnitude of the load current (50Hz) has minimal effect on the measurement accuracy. Addition of a suitable battery based power supply system and isolated communications, probably radio and refinement of the printed circuit board design and software are the remaining development steps to a production instrument.

Sustainable urban infrastructure development in south east Asia : evidence from Hong Kong, Kuala Lumpur and Singapore

Many South East Asian cities have experienced substantial physical, economic and social transformations during the past several decades. The rapid pace of globalisation and economic restructuring has resulted in these cities receiving the full impact of urbanisation pressures. In an attempt to ease these pressures, cities such as Singapore, Hong Kong and Kuala Lumpur have advocated growth management approaches focussing especially on urban infrastructure sustainability. These approaches aim to achieve triple bottom line sustainability by balancing economic and social development, and environmental protection. This chapter evaluates three Asia-Pacific city cases, Singapore, Hong Kong and Kuala Lumpur, and assesses their experiences in managing their urban forms and infrastructure whilst promoting sustainable patterns of urban development.

Empirical comparison of machine learning algorithms for image texture classification with application to vegetation management in power line corridors

This paper reports on the empirical comparison of seven machine learning algorithms in texture classification with application to vegetation management in power line corridors. Aiming at classifying tree species in power line corridors, object-based method is employed. Individual tree crowns are segmented as the basic classification units and three classic texture features are extracted as the input to the classification algorithms. Several widely used performance metrics are used to evaluate the classification algorithms. The experimental results demonstrate that the classification performance depends on the performance matrix, the characteristics of datasets and the feature used.

Advances in vegetation management for power line corridor monitoring using aerial remote sensing techniques

This paper presents a comprehensive discussion of vegetation management approaches in power line corridors based on aerial remote sensing techniques. We address three issues 1) strategies for risk management in power line corridors, 2) selection of suitable platforms and sensor suite for data collection and 3) the progress in automated data processing techniques for vegetation management. We present initial results from a series of experiments and, challenges and lessons learnt from our project.