Eigenvalue Analysis of a DFIG Based Wind Power System under Different Modes of Operations

This chapter discussed the various modes of operation of the Doubly Fed Induction Generator (DFIG) based wind farm system. The impact of a auxiliary damping controller on the different modes of operation for the DFIG based wind generation system is investigated. The co-ordinated tuning of the damping controller to enhance the damping of the oscillatory modes using Bacteria Foraging (BF) technique is presented. The results from eigenvalue analysis are presented to elucidate the effectiveness of the tuned damping controller in the DFIG system under Super/Sub-synchronous speed of operation. The robustness issue of the damping controller is also investigated.

Rough Fuzzy Control of SVC for Power System Stability Enhancement

Modern power systems have become more complex due to the growth in load demand, the installation of Flexible AC Transmission Systems (FACTS) devices and the integration of new HVDC links into existing AC grids. On the other hand, the introduction of the deregulated and unbundled power market operational mechanism, together with present changes in generation sources including connections of large renewable energy generation with intermittent feature in nature, have further increased the complexity and uncertainty for power system operation and control. System operators and engineers have to confront a series of technical challenges from the operation of currently interconnected power systems. Among the many challenges, how to evaluate the steady state and dynamic behaviors of existing interconnected power systems effectively and accurately using more powerful computational analysis models and approaches becomes one of the key issues in power engineering. The traditional computing techniques have been widely used in various fields for power system analysis with varying degrees of success. The rapid development of computational intelligence, such as neural networks, fuzzy systems and evolutionary computation, provides tools and opportunities to solve the complex technical problems in power system planning, operation and control.

Synthetic rating system for railway bridge management

This thesis developed a condition assessment and rating method to identify those bridges in a network which are in most need of repair for an effective life cycle management. The method estimates the contribution of critical factors towards bridge deterioration and uses structural analysis to overcome the subjectivity of traditional current condition assessment methods. This research was a part of the CRC project titled 'Life Cycle Management of Railway Bridges'. Efficient usage of resources and enhancing the safety and serviceability of railway bridges are the significant outcomes of using the proposed method.

Foreign-currency and monetary geopolitics of United States and its effects on the future of the international system

The US dollar is still considered as the main strategic deposit among the currencies of different countries of the world and the policies of the World Bank and the International Financial Organizations have been and will always be influenced by the US economy. Despite the economic crises and commercial balance deficits in the United States, dollar has maintained its high position in and its domination over foreign exchanges and foreign-currency deposits of the countries. The novelty of the present research relies on its consideration of the political properties of the governments and the geopolitical effects of these countries on the position of their monetary and foreign-currency policies and consequently, on the international financial organizations such as the International Monetary Fund and the World Bank, which can determine the future of international economy and the political relations among countries. Our research proves that the political development of the United States and its geopolitical situation have been of the effective factors on dollar growth; and unless the competitors acquire such a relative advantage, they will not be able to seriously challenge the currency of dollar and the monetary policies of the United States, at least in a short time

Stability analysis and implementation of Power-Hardware-in-the-Loop for power system testing

This project develops the required guidelines to assure stable and accurate operation of Power-Hardware-in-the-Loop implementations. The proposals of this research have been theoretically analyzed and practically examined using a Real-Time Digital Simulator. In this research, the interaction between software simulated power network and the physical power system has been studied. The conditions for different operating regimes have been derived and the corresponding analyses have been presented.

When an eco-feedback system joins the family

The dynamic, chaotic, intimate and social nature of family life presents many challenges when designing interactive systems in the household space. This paper presents findings from a whole-of-family approach to studying the use of an energy awareness and management system called “Ecosphere”. Using a novel methodology of inviting 12 families to create their own self-authored videos documenting their energy use, we report on the family dynamics and nuances of family life that shape and affect this use. Our findings suggest that the momentum of existing family dynamics in many cases obstructs behaviour change and renders some family members unaware of energy consumption despite the presence of an energy monitor display in the house. The implication for eco-feedback design is that it needs to recognise and respond to the kinds of family relations into which the system is embedded. In response, we suggest alternative ways of sharing energy-related information among families and incentivising engagement among teenagers.

Analysing governance of Australia's system of landscape-based greenhouse gas abatement

Healthy governance systems are key to delivering effective outcomes in any broad domain of natural resource management (NRM). One of Australia's emerging NRM governance domains is our national framework for greenhouse gas abatement (GGA), as delivered through a wide range of management practices in the Australian landscape. The emerging Landscape-Based GGA Domain represents an innovative governance space that straddles both the nation's broader NRM Policy and Delivery Domain and Australia's GGA Domain. As a point-in-time benchmark, we assess the health of this hybrid domain as it stood at the end of 2013. At that time, the domain was being progressed through the Australian government's Clean Energy Package and, more particularly, its Carbon Farming Initiative (CFI). While significant changes are currently under development by a new Australian government, this paper explores key areas of risk within the governance system underpinning this emerging hybrid domain at that point in time. We then map some potential reform or continuous improvement pathways required (from national to paddock scale) with the view to securing improved landscape outcomes over time through widespread GGA activities.

Proactive training system for safe and efficient precast installation

The construction industry is a crucial component of the Hong Kong economy, and the safety and efficiency of workers are two of its main concerns. The current approach to training workers relies primarily on instilling practice and experience in conventional teacher-apprentice settings on and off site. Both have their limitations however, on-site training is very inefficient and interferes with progress on site, while off-site training provides little opportunity to develop the practical skills and awareness needed through hands-on experience. A more effective way is to train workers in safety awareness and efficient working by current novel information technologies. This paper describes a new and innovative prototype system – the Proactive Construction Management System (PCMS) – to train precast installation workers to be highly productive while being fully aware of the hazards involved. PCMS uses Chirp-Spread-Spectrum-based (CSS) real-time location technology and Unity3D-based data visualisation technology to track construction resources (people, equipment, materials, etc.) and provide real-time feedback and post-event visualisation analysis in a training environment. A trial of a precast facade installation on a real site demonstrates the benefits gained by PCMS in comparison with equivalent training using conventional methods. It is concluded that, although the study is based on specific industrial conditions found in Hong Kong construction projects, PCMS may well attract wider interest and use in future.

Hospital care in Iran : an examination of national health system performance

This study examines hospital care system performance in Iran. We first briefly review hospital care delivery system in Iran. Then, the hospital care system in Iran has been investigated from financial, utilization, and quality perspectives. In particular, we examined the extent to which health care system in Iran protects people from the financial consequence of health care expenses and whether inpatient care distributed according to need. We also empirically analyzed the quality of hospital care in Iran using patient satisfaction information collected in a national health service survey. The Iranian health care system consists of unequal access to hospital care; mismatch between the distribution of services and inpatients' need; and high probability of financial catastrophe due to out-of-pocket payments for inpatient services. Our analysis indicates that the quality of hospital care among Iranian provinces favors patients residing in provinces with high numbers of hospital beds per capita such as Esfahan and Yazd. Patients living in provinces with low levels of accessibility to hospital care (e.g. Gilan, Kermanshah, Hamadan, Chahar Mahall and Bakhtiari, Khuzestan, and Sistan and Baluchestan) receive lower-quality services. These findings suggest that policymakers in Iran should work on several fronts including utilization, financing, and service quality to improve hospital care.

Knowledge gain or system benefit in environmental decision making?

The quality of environmental decisions are gauged according to the management objectives of a conservation project. Management objectives are generally about maximising some quantifiable measure of system benefit, for instance population growth rate. They can also be defined in terms of learning about the system in question, in such a case actions would be chosen that maximise knowledge gain, for instance in experimental management sites. Learning about a system can also take place when managing practically. The adaptive management framework (Walters 1986) formally acknowledges this fact by evaluating learning in terms of how it will improve management of the system and therefore future system benefit. This is taken into account when ranking actions using stochastic dynamic programming (SDP). However, the benefits of any management action lie on a spectrum from pure system benefit, when there is nothing to be learned about the system, to pure knowledge gain. The current adaptive management framework does not permit management objectives to evaluate actions over the full range of this spectrum. By evaluating knowledge gain in units distinct to future system benefit this whole spectrum of management objectives can be unlocked. This paper outlines six decision making policies that differ across the spectrum of pure system benefit through to pure learning. The extensions to adaptive management presented allow specification of the relative importance of learning compared to system benefit in management objectives. Such an extension means practitioners can be more specific in the construction of conservation project objectives and be able to create policies for experimental management sites in the same framework as practical management sites.

Design of coreless PCB transformers for power and signal isolation in a modular ADC system for power quality data acquisition

Available industrial energy meters offer high accuracy and reliability, but are typically expensive and low-bandwidth, making them poorly suited to multi-sensor data acquisition schemes and power quality analysis. An alternative measurement system is proposed in this paper that is highly modular, extensible and compact. To minimise cost, the device makes use of planar coreless PCB transformers to provide galvanic isolation for both power and data. Samples from multiple acquisition devices may be concentrated by a central processor before integration with existing host control systems. This paper focusses on the practical design and implementation of planar coreless PCB transformers to facilitate the module's isolated power, clock and data signal transfer. Calculations necessary to design coreless PCB transformers, and circuits designed for the transformer's practical application in the measurement module are presented. The designed transformer and each application circuit have been experimentally verified, with test data and conclusions made applicable to coreless PCB transformers in general.

The potential impact of climate change and ultraviolet radiation on vaccine preventable infectious diseases and immunisation service delivery system

Climate change and solar ultraviolet radiation may affect vaccine-preventable infectious diseases (VPID), the human immune response process and the immunization service delivery system. We systematically reviewed the scientific literature and identified 37 relevant publications. Our study shows that climate variability and ultraviolet radiation may potentially affect VPID and the immunization delivery system through modulating vector reproduction and vaccination effectiveness, possibly influencing human immune response systems to the vaccination, and disturbing immunization service delivery. Further research is needed to determine these affects on climate-sensitive VPID and on human immune response to common vaccines. Such research will facilitate the development and delivery of optimal vaccination programs for target populations, to meet the goal of disease control and elimination.

Prediction of GMA welding characteristic parameter by artificial neural network system

Nowadays, demand for automated Gas metal arc welding (GMAW) is growing and consequently need for intelligent systems is increased to ensure the accuracy of the procedure. To date, welding pool geometry has been the most used factor in quality assessment of intelligent welding systems. But, it has recently been found that Mahalanobis Distance (MD) not only can be used for this purpose but also is more efficient. In the present paper, Artificial Neural Networks (ANN) has been used for prediction of MD parameter. However, advantages and disadvantages of other methods have been discussed. The Levenberg–Marquardt algorithm was found to be the most effective algorithm for GMAW process. It is known that the number of neurons plays an important role in optimal network design. In this work, using trial and error method, it has been found that 30 is the optimal number of neurons. The model has been investigated with different number of layers in Multilayer Perceptron (MLP) architecture and has been shown that for the aim of this work the optimal result is obtained when using MLP with one layer. Robustness of the system has been evaluated by adding noise into the input data and studying the effect of the noise in prediction capability of the network. The experiments for this study were conducted in an automated GMAW setup that was integrated with data acquisition system and prepared in a laboratory for welding of steel plate with 12 mm in thickness. The accuracy of the network was evaluated by Root Mean Squared (RMS) error between the measured and the estimated values. The low error value (about 0.008) reflects the good accuracy of the model. Also the comparison of the predicted results by ANN and the test data set showed very good agreement that reveals the predictive power of the model. Therefore, the ANN model offered in here for GMA welding process can be used effectively for prediction goals.