Developing sustainable housing through building utilities and transport innovation

Sustainability concerns every citizen. Housing affordability and sustainable solutions are being highlighted in research and practice in many parts of the world. This paper discusses the development of a Commuter Energy and Building Utilities System (CEBUS) in sustainable housing projects as a means of bridging the gap between current median house pricing and target affordable house pricing for low income earners. Similar scales of sustainable housing development cannot be achieved through independent application of current best practice methods in ecologically sustainable development strategies or transit oriented development master plans. This paper presents the initial stage of research on first capital and ongoing utilities and transport cost savings available from these sustainable design methods. It also outlines further research and development of a CEBUS Dynamic Simulation Model and Conceptual Framework for the Australian property development and construction industry.

Moving from outsider to insider : peer status and partnerships between electricity utilities and residential consumers

An electricity demand reduction project based on comprehensive residential consumer engagement was established within an Australian community in 2008. By 2011, both the peak demand and grid supplied electricity consumption had decreased to below pre-intervention levels. This case study research explored the relationship developed between the utility, community and individual consumer from the residential customer perspective through qualitative research of 22 residential households. It is proposed that an energy utility can be highly successful at peak demand reduction by becoming a community member and a peer to residential consumers and developing the necessary trust, access, influence and partnership required to create the responsive environment to change. A peer-community approach could provide policymakers with a pathway for implementing pro-environmental behaviour for low carbon communities, as well as peak demand reduction, thereby addressing government emission targets while limiting the cost of living increases from infrastructure expenditure.

Towards an acoustic environmental observatory

The need for large scale environmental monitoring to manage environmental change is well established. Ecologists have long used acoustics as a means of monitoring the environment in their field work, and so the value of an acoustic environmental observatory is evident. However, the volume of data generated by such an observatory would quickly overwhelm even the most fervent scientist using traditional methods. In this paper we present our steps towards realising a complete acoustic environmental observatory - i.e. a cohesive set of hardware sensors, management utilities, and analytical tools required for large scale environmental monitoring. Concrete examples of these elements, which are in active use by ecological scientists, are also presented

Motivation and perception factors influence buying home behaviour in Dilly, East Timor

Demand of low cost housing increased from 1995 to 1997 which is shown by the number of housing loan approval. In order to develop the most suitable marketing plan, developer needs to know some factors which influenced to the decision making process of buying house. This research used a residential development in PT Delta Comoro Permai, Dilly as a case study. A survey to homeowners has been done to evaluate the motivation and perception factors in buying home behaviour. The survey has been done on the 3rd August to 29th August 1998. In this study, four main components have been examined. Physical and linkage are not as important as environment and utilities for the homebuyer. Moreover, the result is consistent with developer’s motto ‘clean, secure, aesthetic, healthy and prosperity’. This study provides further recommendation in the environment and utilities components for the new development in the future.

Attractiveness of venture ideas : a conjoint study

Principal Topic : According to Shane & Venkataraman (2000) entrepreneurship consists of the recognition and exploitation of venture ideas - or opportunities as they often called - to create future goods and services. This definition puts venture ideas is at the heart of entrepreneurship research. Substantial research has been done on venture ideas in order to enhance our understanding of this phenomenon (e.g. Choi & Shepherd, 2004; Shane, 2000; Shepherd & DeTienne, 2005). However, we are yet to learn what factors drive entrepreneurs' perceptions of the relative attractiveness of venture ideas, and how important different idea characteristics are for such assessments. Ruef (2002) recognized that there is an uneven distribution of venture ideas undertaken by entrepreneurs in the USA. A majority introduce either a new product/service or access a new market or market segment. A smaller percentage of entrepreneurs introduce a new method of production, organizing, or distribution. This implies that some forms of venture ideas are perceived by entrepreneurs as more important or valuable than others. However, Ruef does not provide any information regarding why some forms of venture ideas are more common than others among entrepreneurs. Therefore, this study empirically investigates what factors affect the attractiveness of venture ideas as well as their relative importance. Based on two key characteristics of venture ideas, namely venture idea newness and relatedness, our study investigates how different types and degrees of newness and relatedness of venture ideas affect their attractiveness as perceived by expert entrepreneurs. Methodology/Key : Propositions According to Schumpeter (1934) entrepreneurs introduce different types of venture ideas such as new products/services, new method of production, enter into new markets/customer and new method of promotion. Further, according to Schumpeter (1934) and Kirzner (1973) venture ideas introduced to the market range along a continuum of innovative to imitative ideas. The distinction between these two extremes of venture idea highlights an important property of venture idea, namely their newness. Entrepreneurs, in order to gain competitive advantage or above average returns introduce their venture ideas which may be either new to the world, new to the market that they seek to enter, substantially improved from current offerings and an imitative form of existing offerings. Expert entrepreneurs may be more attracted to venture ideas that exhibit high degree of newness because of the higher newness is coupled with increased market potential (Drucker, 1985) Moreover, certain individual characteristics also affect the attractiveness of venture idea. According to Shane (2000), individual's prior knowledge is closely associated with the recognition of venture ideas. Sarasvathy's (2001) Effectuation theory proposes a high degree of relatedness between venture ideas and the resource position of the individual. Thus, entrepreneurs may be more attracted to venture ideas that are closely aligned with the knowledge and/or resources they already possess. On the other hand, the potential financial gain (Shepherd & DeTienne, 2005) may be larger for ideas that are not close to the entrepreneurs' home turf. Therefore, potential financial gain is a stimulus that has to be considered separately. We aim to examine how entrepreneurs weigh considerations of different forms of newness and relatedness as well as potential financial gain in assessing the attractiveness of venture ideas. We use conjoint analysis to determine how expert entrepreneurs develop preferences for venture ideas which involved with different degrees of newness, relatedness and potential gain. This analytical method paves way to measure the trade-offs they make when choosing a particular venture idea. The conjoint analysis estimates respondents' preferences in terms of utilities (or part-worth) for each level of newness, relatedness and potential gain of venture ideas. A sample of 50 expert entrepreneurs who were awarded young entrepreneurship awards in Sri Lanka in 2007 is used for interviews. Each respondent is interviewed providing with 32 scenarios which explicate different combinations of possible profiles open them into consideration. Conjoint software (SPSS) is used to analyse data. Results and Implications : The data collection of this study is still underway. However, results of this study will provide information regarding the attractiveness of each level of newness, relatedness and potential gain of venture idea and their relative importance in a business model. Additionally, these results provide important implications for entrepreneurs, consultants and other stakeholders as regards the importance of different of attributes of venture idea coupled with different levels. Entrepreneurs, consultants and other stakeholders could make decisions accordingly.

On the optimal capacity expansion of electric power systems

The analysis of investment in the electric power has been the subject of intensive research for many years. The efficient generation and distribution of electrical energy is a difficult task involving the operation of a complex network of facilities, often located over very large geographical regions. Electric power utilities have made use of an enormous range of mathematical models. Some models address time spans which last for a fraction of a second, such as those that deal with lightning strikes on transmission lines while at the other end of the scale there are models which address time horizons consisting of ten or twenty years; these usually involve long range planning issues. This thesis addresses the optimal long term capacity expansion of an interconnected power system. The aim of this study has been to derive a new, long term planning model which recognises the regional differences which exist for energy demand and which are present in the construction and operation of power plant and transmission line equipment. Perhaps the most innovative feature of the new model is the direct inclusion of regional energy demand curves in the nonlinear form. This results in a nonlinear capacity expansion model. After review of the relevant literature, the thesis first develops a model for the optimal operation of a power grid. This model directly incorporates regional demand curves. The model is a nonlinear programming problem containing both integer and continuous variables. A solution algorithm is developed which is based upon a resource decomposition scheme that separates the integer variables from the continuous ones. The decompostion of the operating problem leads to an interactive scheme which employs a mixed integer programming problem, known as the master, to generate trial operating configurations. The optimum operating conditions of each trial configuration is found using a smooth nonlinear programming model. The dual vector recovered from this model is subsequently used by the master to generate the next trial configuration. The solution algorithm progresses until lower and upper bounds converge. A range of numerical experiments are conducted and these experiments are included in the discussion. Using the operating model as a basis, a regional capacity expansion model is then developed. It determines the type, location and capacity of additional power plants and transmission lines, which are required to meet predicted electicity demands. A generalised resource decompostion scheme, similar to that used to solve the operating problem, is employed. The solution algorithm is used to solve a range of test problems and the results of these numerical experiments are reported. Finally, the expansion problem is applied to the Queensland electricity grid in Australia.

On the optimal capacity expansion of electric power systems

The analysis of investment in the electric power has been the subject of intensive research for many years. The efficient generation and distribution of electrical energy is a difficult task involving the operation of a complex network of facilities, often located over very large geographical regions. Electric power utilities have made use of an enormous range of mathematical models. Some models address time spans which last for a fraction of a second, such as those that deal with lightning strikes on transmission lines while at the other end of the scale there are models which address time horizons consisting of ten or twenty years; these usually involve long range planning issues. This thesis addresses the optimal long term capacity expansion of an interconnected power system. The aim of this study has been to derive a new, long term planning model which recognises the regional differences which exist for energy demand and which are present in the construction and operation of power plant and transmission line equipment. Perhaps the most innovative feature of the new model is the direct inclusion of regional energy demand curves in the nonlinear form. This results in a nonlinear capacity expansion model. After review of the relevant literature, the thesis first develops a model for the optimal operation of a power grid. This model directly incorporates regional demand curves. The model is a nonlinear programming problem containing both integer and continuous variables. A solution algorithm is developed which is based upon a resource decomposition scheme that separates the integer variables from the continuous ones. The decompostion of the operating problem leads to an interactive scheme which employs a mixed integer programming problem, known as the master, to generate trial operating configurations. The optimum operating conditions of each trial configuration is found using a smooth nonlinear programming model. The dual vector recovered from this model is subsequently used by the master to generate the next trial configuration. The solution algorithm progresses until lower and upper bounds converge. A range of numerical experiments are conducted and these experiments are included in the discussion. Using the operating model as a basis, a regional capacity expansion model is then developed. It determines the type, location and capacity of additional power plants and transmission lines, which are required to meet predicted electicity demands. A generalised resource decompostion scheme, similar to that used to solve the operating problem, is employed. The solution algorithm is used to solve a range of test problems and the results of these numerical experiments are reported. Finally, the expansion problem is applied to the Queensland electricity grid in Australia

Developing regional precise positioning services using the legacy and future GNSS receivers

This paper presents an overview of technical solutions for regional area precise GNSS positioning services such as in Queensland. The research focuses on the technical and business issues that currently constrain GPS-based local area Real Time Kinematic (RTK) precise positioning services so as to operate in future across larger regional areas, and therefore support services in agriculture, mining, utilities, surveying, construction, and others. The paper first outlines an overall technical framework that has been proposed to transition the current RTK services to future larger scale coverage. The framework enables mixed use of different reference GNSS receiver types, dual- or triple-frequency, single or multiple systems, to provide RTK correction services to users equipped with any type of GNSS receivers. Next, data processing algorithms appropriate for triple-frequency GNSS signals are reviewed and some key performance benefits of using triple carrier signals for reliable RTK positioning over long distances are demonstrated. A server-based RTK software platform is being developed to allow for user positioning computations at server nodes instead of on the user's device. An optimal deployment scheme for reference stations across a larger-scale network has been suggested, given restrictions such as inter-station distances, candidates for reference locations, and operational modes. For instance, inter-station distances between triple-frequency receivers can be extended to 150km, which doubles the distance between dual-frequency receivers in the existing RTK network designs.

Analysis of distrubances in large interconnected power systems

World economies increasingly demand reliable and economical power supply and distribution. To achieve this aim the majority of power systems are becoming interconnected, with several power utilities supplying the one large network. One problem that occurs in a large interconnected power system is the regular occurrence of system disturbances which can result in the creation of intra-area oscillating modes. These modes can be regarded as the transient responses of the power system to excitation, which are generally characterised as decaying sinusoids. For a power system operating ideally these transient responses would ideally would have a “ring-down” time of 10-15 seconds. Sometimes equipment failures disturb the ideal operation of power systems and oscillating modes with ring-down times greater than 15 seconds arise. The larger settling times associated with such “poorly damped” modes cause substantial power flows between generation nodes, resulting in significant physical stresses on the power distribution system. If these modes are not just poorly damped but “negatively damped”, catastrophic failures of the system can occur. To ensure system stability and security of large power systems, the potentially dangerous oscillating modes generated from disturbances (such as equipment failure) must be quickly identified. The power utility must then apply appropriate damping control strategies. In power system monitoring there exist two facets of critical interest. The first is the estimation of modal parameters for a power system in normal, stable, operation. The second is the rapid detection of any substantial changes to this normal, stable operation (because of equipment breakdown for example). Most work to date has concentrated on the first of these two facets, i.e. on modal parameter estimation. Numerous modal parameter estimation techniques have been proposed and implemented, but all have limitations [1-13]. One of the key limitations of all existing parameter estimation methods is the fact that they require very long data records to provide accurate parameter estimates. This is a particularly significant problem after a sudden detrimental change in damping. One simply cannot afford to wait long enough to collect the large amounts of data required for existing parameter estimators. Motivated by this gap in the current body of knowledge and practice, the research reported in this thesis focuses heavily on rapid detection of changes (i.e. on the second facet mentioned above). This thesis reports on a number of new algorithms which can rapidly flag whether or not there has been a detrimental change to a stable operating system. It will be seen that the new algorithms enable sudden modal changes to be detected within quite short time frames (typically about 1 minute), using data from power systems in normal operation. The new methods reported in this thesis are summarised below. The Energy Based Detector (EBD): The rationale for this method is that the modal disturbance energy is greater for lightly damped modes than it is for heavily damped modes (because the latter decay more rapidly). Sudden changes in modal energy, then, imply sudden changes in modal damping. Because the method relies on data from power systems in normal operation, the modal disturbances are random. Accordingly, the disturbance energy is modelled as a random process (with the parameters of the model being determined from the power system under consideration). A threshold is then set based on the statistical model. The energy method is very simple to implement and is computationally efficient. It is, however, only able to determine whether or not a sudden modal deterioration has occurred; it cannot identify which mode has deteriorated. For this reason the method is particularly well suited to smaller interconnected power systems that involve only a single mode. Optimal Individual Mode Detector (OIMD): As discussed in the previous paragraph, the energy detector can only determine whether or not a change has occurred; it cannot flag which mode is responsible for the deterioration. The OIMD seeks to address this shortcoming. It uses optimal detection theory to test for sudden changes in individual modes. In practice, one can have an OIMD operating for all modes within a system, so that changes in any of the modes can be detected. Like the energy detector, the OIMD is based on a statistical model and a subsequently derived threshold test. The Kalman Innovation Detector (KID): This detector is an alternative to the OIMD. Unlike the OIMD, however, it does not explicitly monitor individual modes. Rather it relies on a key property of a Kalman filter, namely that the Kalman innovation (the difference between the estimated and observed outputs) is white as long as the Kalman filter model is valid. A Kalman filter model is set to represent a particular power system. If some event in the power system (such as equipment failure) causes a sudden change to the power system, the Kalman model will no longer be valid and the innovation will no longer be white. Furthermore, if there is a detrimental system change, the innovation spectrum will display strong peaks in the spectrum at frequency locations associated with changes. Hence the innovation spectrum can be monitored to both set-off an “alarm” when a change occurs and to identify which modal frequency has given rise to the change. The threshold for alarming is based on the simple Chi-Squared PDF for a normalised white noise spectrum [14, 15]. While the method can identify the mode which has deteriorated, it does not necessarily indicate whether there has been a frequency or damping change. The PPM discussed next can monitor frequency changes and so can provide some discrimination in this regard. The Polynomial Phase Method (PPM): In [16] the cubic phase (CP) function was introduced as a tool for revealing frequency related spectral changes. This thesis extends the cubic phase function to a generalised class of polynomial phase functions which can reveal frequency related spectral changes in power systems. A statistical analysis of the technique is performed. When applied to power system analysis, the PPM can provide knowledge of sudden shifts in frequency through both the new frequency estimate and the polynomial phase coefficient information. This knowledge can be then cross-referenced with other detection methods to provide improved detection benchmarks.

Monte Carlo modelling of X-ray absorptiometry and its application to body composition studies

This thesis applies Monte Carlo techniques to the study of X-ray absorptiometric methods of bone mineral measurement. These studies seek to obtain information that can be used in efforts to improve the accuracy of the bone mineral measurements. A Monte Carlo computer code for X-ray photon transport at diagnostic energies has been developed from first principles. This development was undertaken as there was no readily available code which included electron binding energy corrections for incoherent scattering and one of the objectives of the project was to study the effects of inclusion of these corrections in Monte Carlo models. The code includes the main Monte Carlo program plus utilities for dealing with input data. A number of geometrical subroutines which can be used to construct complex geometries have also been written. The accuracy of the Monte Carlo code has been evaluated against the predictions of theory and the results of experiments. The results show a high correlation with theoretical predictions. In comparisons of model results with those of direct experimental measurements, agreement to within the model and experimental variances is obtained. The code is an accurate and valid modelling tool. A study of the significance of inclusion of electron binding energy corrections for incoherent scatter in the Monte Carlo code has been made. The results show this significance to be very dependent upon the type of application. The most significant effect is a reduction of low angle scatter flux for high atomic number scatterers. To effectively apply the Monte Carlo code to the study of bone mineral density measurement by photon absorptiometry the results must be considered in the context of a theoretical framework for the extraction of energy dependent information from planar X-ray beams. Such a theoretical framework is developed and the two-dimensional nature of tissue decomposition based on attenuation measurements alone is explained. This theoretical framework forms the basis for analytical models of bone mineral measurement by dual energy X-ray photon absorptiometry techniques. Monte Carlo models of dual energy X-ray absorptiometry (DEXA) have been established. These models have been used to study the contribution of scattered radiation to the measurements. It has been demonstrated that the measurement geometry has a significant effect upon the scatter contribution to the detected signal. For the geometry of the models studied in this work the scatter has no significant effect upon the results of the measurements. The model has also been used to study a proposed technique which involves dual energy X-ray transmission measurements plus a linear measurement of the distance along the ray path. This is designated as the DPA( +) technique. The addition of the linear measurement enables the tissue decomposition to be extended to three components. Bone mineral, fat and lean soft tissue are the components considered here. The results of the model demonstrate that the measurement of bone mineral using this technique is stable over a wide range of soft tissue compositions and hence would indicate the potential to overcome a major problem of the two component DEXA technique. However, the results also show that the accuracy of the DPA( +) technique is highly dependent upon the composition of the non-mineral components of bone and has poorer precision (approximately twice the coefficient of variation) than the standard DEXA measurements. These factors may limit the usefulness of the technique. These studies illustrate the value of Monte Carlo computer modelling of quantitative X-ray measurement techniques. The Monte Carlo models of bone densitometry measurement have:- 1. demonstrated the significant effects of the measurement geometry upon the contribution of scattered radiation to the measurements, 2. demonstrated that the statistical precision of the proposed DPA( +) three tissue component technique is poorer than that of the standard DEXA two tissue component technique, 3. demonstrated that the proposed DPA(+) technique has difficulty providing accurate simultaneous measurement of body composition in terms of a three component model of fat, lean soft tissue and bone mineral,4. and provided a knowledge base for input to decisions about development (or otherwise) of a physical prototype DPA( +) imaging system. The Monte Carlo computer code, data, utilities and associated models represent a set of significant, accurate and valid modelling tools for quantitative studies of physical problems in the fields of diagnostic radiology and radiography.

Householder experiences with resource monitoring technology in sustainable homes

The use of feedback technologies, in the form of products such as Smart Meters, is increasingly seen as the means by which 'consumers' can be made aware of their patterns of resource consumption, and to then use this enhanced awareness to change their behaviour to reduce the environmental impacts of their consumption. These technologies tend to be single-resource focused (e.g. on electricity consumption only) and their functionality defined by persons other than end-users (e.g. electricity utilities). This paper presents initial findings of end-users' experiences with a multi-resource feedback technology, within the context of sustainable housing. It proposes that an understanding of user context, supply chain management and market diffusion issues are important design considerations that contribute to technology 'success'.

Attractiveness of venture idea amongst expert entrepreneurs : a conjoint analysis

Principal Topic Venture ideas are at the heart of entrepreneurship (Davidsson, 2004). However, we are yet to learn what factors drive entrepreneurs’ perceptions of the attractiveness of venture ideas, and what the relative importance of these factors are for their decision to pursue an idea. The expected financial gain is one factor that will obviously influence the perceived attractiveness of a venture idea (Shepherd & DeTienne, 2005). In addition, the degree of novelty of venture ideas along one or more dimensions such as new products/services, new method of production, enter into new markets/customer and new method of promotion may affect their attractiveness (Schumpeter, 1934). Further, according to the notion of an individual-opportunity nexus venture ideas are closely associated with certain individual characteristics (relatedness). Shane (2000) empirically identified that individual’s prior knowledge is closely associated with the recognition of venture ideas. Sarasvathy’s (2001; 2008) Effectuation theory proposes a high degree of relatedness between venture ideas and the resource position of the individual. This study examines how entrepreneurs weigh considerations of different forms of novelty and relatedness as well as potential financial gain in assessing the attractiveness of venture ideas. Method I use conjoint analysis to determine how expert entrepreneurs develop preferences for venture ideas which involved with different degrees of novelty, relatedness and potential gain. The conjoint analysis estimates respondents’ preferences in terms of utilities (or part-worth) for each level of novelty, relatedness and potential gain of venture ideas. A sample of 32 expert entrepreneurs who were awarded young entrepreneurship awards were selected for the study. Each respondent was interviewed providing with 32 scenarios which explicate different combinations of possible profiles open them into consideration. Results and Implications Results indicate that while the respondents do not prefer mere imitation they receive higher utility for low to medium degree of newness suggesting that high degrees of newness are fraught with greater risk and/or greater resource needs. Respondents pay considerable weight on alignment with the knowledge and skills they already posses in choosing particular venture idea. The initial resource position of entrepreneurs is not equally important. Even though expected potential financial gain gives substantial utility, result indicate that it is not a dominant factor for the attractiveness of venture idea.

Impacts and adaptation response of infrastructure and communities to heatwaves : the southern Australian experience of 2009

From 27 January to 8 February during the summer of 2009, southern Australia experienced one of the nation‘s most severe heatwaves. Governments, councils, utilities, hospitals and emergency response organisations and the community were largely underprepared for an extreme event of this magnitude. This case study targets the experience and challenges faced by decision makers and policy makers and focuses on the major metropolitan areas affected by the heatwave — Melbourne and Adelaide. The study examines the 2009 heatwave‘s characteristics; its impacts (on human health, infrastructure and human services); the degree of adaptive capacity (vulnerability and resilience) of various sectors, communities and individuals; and the reactive responses of government and emergency and associated services and their effectiveness. Barriers and challenges to adaptation and increasing resilience are also identified and further areas for research are suggested. This study does not include details of the heatwave‘s effects beyond Victoria and South Australia, or its economic impacts, or of Victoria‘s 'Black Saturday‘ bushfires.

Directional earth fault relay operation in mutually coupled multiple circuit distribution lines

Many of the power utilities around the world experienced spurious tripping of directional earth fault relays in their mesh distribution networks due to induced circulating currents. This circulating current is zero sequence and induced in the healthy circuit due to the zero sequence current flow resulting from a ground fault of a parallel circuit. This paper quantitatively discusses the effects of mutual coupling on earth fault protection of distribution systems. An actual spurious tripping event is analyzed to support the theory and to present options for improved resilience to spurious tripping.