497 resultados para Real Electricity Markets


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Investment in residential property in Australia is not dominated by the major investment institutions in to the same degree as the commercial, industrial and retail property markets. As at December 2001, the Property Council of Australia Investment Performance Index contained residential property with a total value of $235 million, which represents only 0.3% of the total PCA Performance Index value. The majority of investment in the Australian residential property market is by small investment companies and individual investors. The limited exposure of residential property in the institutional investment portfolios has also limited the research that has been undertaken in relation to residential property performance. However the importance of individual investment in residential property is continuing to gain importance as both individuals are now taking control of their own superannuation portfolios and the various State Governments of Australia are decreasing their involvement in the construction of public housing by subsidizing low-income families into the private residential property market. This paper will: • Provide a comparison of the cost to initially purchase residential property in the various capital city residential property markets in Australia, and • Analyse the true cost and investment performance of residential property in the main residential property markets in Australia based on a standard investment portfolio in each of the State capital cities and relate these results to real estate marketing and agency practice.

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The paper investigates if there are any discernible trends in the U.S. and Australian commercial property public debt markets with the onset of the global financial crisis (GFC). Commercial mortgage-backed securities and unsecured bonds issued by real estate investment trusts for the period 2000 to Q3:2009 are reviewed. It is shown that events in the equity markets have an impact on the pricing of these two instruments. Furthermore, the impact of subdued activity in these financing instruments on the commercial property market is discussed.

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Regardless of ‘bear’ or ‘bull’ markets, the great Australian dream remains to own your own home. Central to this dream of home ownership is unflagging interest in the property market, reflected in bulging real estate news sections of newspapers in South East Queensland, the focus area for this thesis research. While there has been much scholarly research into other areas of public relations spin and its impact on news-gathering processes, there appears to be next to no research on real estate spin, how it is prepared and by whom, and journalism’s attitude to and the managing of the spin. Real estate spin remains an under-researched topic requiring further investigation not only in South East Queensland but Australia-wide given the ‘big bucks’ allotted to the promotion of real estate and the income it generates for news media outlets, particularly newspapers. This thesis examines the influence of public relations practitioners and journalists specialising in real estate spin through interviews, content analysis, and how real estate spin envelopes itself in today’s society. From content analyses and observations of journalism in the real estate rounds of the two major newspapers in South East Queensland, I found that journalists were using massive quantities of real estate spin supplied by PR practitioners and other associated industry sources. This spin is supplanting investigative newsroom journalism, thus allowing newspapers to operate with minimal staffing levels yet still able to publish large weekly real estate news sections. My research also revealed growing commercialisation of real estate news through increasing outsourcing of journalistic work to a writing bureau, which could jeopardise both the professions of journalism and public relations in the future.

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The authors currently engage in two projects to improve human-computer interaction (HCI) designs that can help conserve resources. The projects explore motivation and persuasion strategies relevant to ubiquitous computing systems that bring real-time consumption data into the homes and hands of residents in Brisbane, Australia. The first project seeks to increase understanding among university staff of the tangible and negative effects that excessive printing has on the workplace and local environment. The second project seeks to shift attitudes toward domestic energy conservation through software and hardware that monitor real-time, in situ electricity consumption in homes across Queensland. The insights drawn from these projects will help develop resource consumption user archetypes, providing a framework linking people to differing interface design requirements.

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One of the major fall outs from the Global Financial Crisis has been the decline in residential property construction, home lending and residential property prices. This has lead to some extent to a reduction in the number of small investors willing to commit funds to an investment market that is not seen to perform as well as other investment assets, particularly in relation to income return.With a decreasing supply of rental accommodation in the housing markets, less public housing being constructed by both State and Commonwealth Governments, there is the potential for the residential property market to provide more substantial returns than previous years.This paper will analyse the current residential housing market in Brisbane, Australia to determine if there are sectors in this market that are outperforming the average income and total return for residential investment property and the variation in investment performance across the various housing sub-markets. The results show that property investment in residential property provides opportunities to maximize returns based on geographic location and socio-economic economic status, with lower value areas showing the highest income returns and higher value suburbs showing greater capital returns

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The global financial crisis that impacted on all world economies throughout 2008 and 2009. This impact has not been confined to the finance industries but has had a direct and indirect impact on the property industry worldwide from both an ownership and investment perspective. Property markets have experienced various levels of impact from this event, but universally the greatest impact has been on the traditional commercial and industrial property sectors from the investor perspective, with investment and superannuation funds reporting significant declines in the reported value of these investments. Despite the very direct impact of these declining property markets, the GFC has also had a very significant indirect impact on the various property professions and how these professions are now operating in this declining property market. Of particular interest is the comparison of the property market forecasts in late 2007 to the actual results in 2008/2009.

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Widespread adoption by electricity utilities of Non-Conventional Instrument Transformers, such as optical or capacitive transducers, has been limited due to the lack of a standardised interface and multi-vendor interoperability. Low power analogue interfaces are being replaced by IEC 61850 9 2 and IEC 61869 9 digital interfaces that use Ethernet networks for communication. These ‘process bus’ connections achieve significant cost savings by simplifying connections between switchyard and control rooms; however the in-service performance when these standards are employed is largely unknown. The performance of real-time Ethernet networks and time synchronisation was assessed using a scale model of a substation automation system. The test bed was constructed from commercially available timing and protection equipment supplied by a range of vendors. Test protocols have been developed to thoroughly evaluate the performance of Ethernet networks and network based time synchronisation. The suitability of IEEE Std 1588 Precision Time Protocol (PTP) as a synchronising system for sampled values was tested in the steady state and under transient conditions. Similarly, the performance of hardened Ethernet switches designed for substation use was assessed under a range of network operating conditions. This paper presents test methods that use a precision Ethernet capture card to accurately measure PTP and network performance. These methods can be used for product selection and to assess ongoing system performance as substations age. Key findings on the behaviour of multi-function process bus networks are presented. System level tests were performed using a Real Time Digital Simulator and transformer protection relay with sampled value and Generic Object Oriented Substation Events (GOOSE) capability. These include the interactions between sampled values, PTP and GOOSE messages. Our research has demonstrated that several protocols can be used on a shared process bus, even with very high network loads. This should provide confidence that this technology is suitable for transmission substations.

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This project researched the performance of emerging digital technology for high voltage electricity substations that significantly improves safety for staff and reduces the potential impact on the environment of equipment failure. The experimental evaluation used a scale model of a substation control system that incorporated real substation control and networking equipment with real-time simulation of the power system. The outcomes confirm that it is possible to implement Ethernet networks in high voltage substations that meet the needs of utilities; however component-level testing of devices is necessary to achieve this. The assessment results have been used to further develop international standards for substation communication and precision timing.

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Energy prices are highly volatile and often feature unexpected spikes. It is the aim of this paper to examine whether the occurrence of these extreme price events displays any regularities that can be captured using an econometric model. Here we treat these price events as point processes and apply Hawkes and Poisson autoregressive models to model the dynamics in the intensity of this process.We use load and meteorological information to model the time variation in the intensity of the process. The models are applied to data from the Australian wholesale electricity market, and a forecasting exercise illustrates both the usefulness of these models and their limitations when attempting to forecast the occurrence of extreme price events.

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Price based technique is one way to handle increase in peak demand and deal with voltage violations in residential distribution systems. This paper proposes an improved real time pricing scheme for residential customers with demand response option. Smart meters and in-home display units are used to broadcast the price and appropriate load adjustment signals. Customers are given an opportunity to respond to the signals and adjust the loads. This scheme helps distribution companies to deal with overloading problems and voltage issues in a more efficient way. Also, variations in wholesale electricity prices are passed on to electricity customers to take collective measure to reduce network peak demand. It is ensured that both customers and utility are benefitted by this scheme.

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Agent-based modelling (ABM), like other modelling techniques, is used to answer specific questions from real world systems that could otherwise be expensive or impractical. Its recent gain in popularity can be attributed to some degree to its capacity to use information at a fine level of detail of the system, both geographically and temporally, and generate information at a higher level, where emerging patterns can be observed. This technique is data-intensive, as explicit data at a fine level of detail is used and it is computer-intensive as many interactions between agents, which can learn and have a goal, are required. With the growing availability of data and the increase in computer power, these concerns are however fading. Nonetheless, being able to update or extend the model as more information becomes available can become problematic, because of the tight coupling of the agents and their dependence on the data, especially when modelling very large systems. One large system to which ABM is currently applied is the electricity distribution where thousands of agents representing the network and the consumers’ behaviours are interacting with one another. A framework that aims at answering a range of questions regarding the potential evolution of the grid has been developed and is presented here. It uses agent-based modelling to represent the engineering infrastructure of the distribution network and has been built with flexibility and extensibility in mind. What distinguishes the method presented here from the usual ABMs is that this ABM has been developed in a compositional manner. This encompasses not only the software tool, which core is named MODAM (MODular Agent-based Model) but the model itself. Using such approach enables the model to be extended as more information becomes available or modified as the electricity system evolves, leading to an adaptable model. Two well-known modularity principles in the software engineering domain are information hiding and separation of concerns. These principles were used to develop the agent-based model on top of OSGi and Eclipse plugins which have good support for modularity. Information regarding the model entities was separated into a) assets which describe the entities’ physical characteristics, and b) agents which describe their behaviour according to their goal and previous learning experiences. This approach diverges from the traditional approach where both aspects are often conflated. It has many advantages in terms of reusability of one or the other aspect for different purposes as well as composability when building simulations. For example, the way an asset is used on a network can greatly vary while its physical characteristics are the same – this is the case for two identical battery systems which usage will vary depending on the purpose of their installation. While any battery can be described by its physical properties (e.g. capacity, lifetime, and depth of discharge), its behaviour will vary depending on who is using it and what their aim is. The model is populated using data describing both aspects (physical characteristics and behaviour) and can be updated as required depending on what simulation is to be run. For example, data can be used to describe the environment to which the agents respond to – e.g. weather for solar panels, or to describe the assets and their relation to one another – e.g. the network assets. Finally, when running a simulation, MODAM calls on its module manager that coordinates the different plugins, automates the creation of the assets and agents using factories, and schedules their execution which can be done sequentially or in parallel for faster execution. Building agent-based models in this way has proven fast when adding new complex behaviours, as well as new types of assets. Simulations have been run to understand the potential impact of changes on the network in terms of assets (e.g. installation of decentralised generators) or behaviours (e.g. response to different management aims). While this platform has been developed within the context of a project focussing on the electricity domain, the core of the software, MODAM, can be extended to other domains such as transport which is part of future work with the addition of electric vehicles.

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This thesis introduces advanced Demand Response algorithms for residential appliances to provide benefits for both utility and customers. The algorithms are engaged in scheduling appliances appropriately in a critical peak day to alleviate network peak, adverse voltage conditions and wholesale price spikes also reducing the cost of residential energy consumption. Initially, a demand response technique via customer reward is proposed, where the utility controls appliances to achieve network improvement. Then, an improved real-time pricing scheme is introduced and customers are supported by energy management schedulers to actively participate in it. Finally, the demand response algorithm is improved to provide frequency regulation services.

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With the recent development of advanced metering infrastructure, real-time pricing (RTP) scheme is anticipated to be introduced in future retail electricity market. This paper proposes an algorithm for a home energy management scheduler (HEMS) to reduce the cost of energy consumption using RTP. The proposed algorithm works in three subsequent phases namely real-time monitoring (RTM), stochastic scheduling (STS) and real-time control (RTC). In RTM phase, characteristics of available controllable appliances are monitored in real-time and stored in HEMS. In STS phase, HEMS computes an optimal policy using stochastic dynamic programming (SDP) to select a set of appliances to be controlled with an objective of the total cost of energy consumption in a house. Finally, in RTC phase, HEMS initiates the control of the selected appliances. The proposed HEMS is unique as it intrinsically considers uncertainties in RTP and power consumption pattern of various appliances. In RTM phase, appliances are categorized according to their characteristics to ease the control process, thereby minimizing the number of control commands issued by HEMS. Simulation results validate the proposed method for HEMS.

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The aim of this research is to determine if a range of crimes in a suburb have an impact on the residential property sectors in that particular suburb. With the increasing media coverage of crime in specific locations, this knowledge of crime in Brisbane Australia is more available to potential residential property buyers This research is based on the analysis of the crime statistics for 30 suburbs in Brisbane across a range of major crime activities and compares the level of crime to property median prices, sales volume and in a range of suburbs the volume of sale and lease listings. The results of the research show a significant variation in the response of buyers in residential property markets based on the type of crime and the socio-economic status of the suburb. In a range of suburbs, value factors other than crime are the major drivers of the market. The study provides an insight into consumer behaviour in a major city and the response of residential property buyers to an increasing level and awareness of crime statistics in the suburbs they are considering to buy. Implications of this research are that with a greater level of awareness of factors that could be a disadvantage to some potential buyers are not always reflected across a full residential property market. Valuers, property financiers and the public need to be aware of the type of crime and locations that have a direct impact on property prices and saleability These results expand on the current knowledge of value drivers in major residential property markets.