110 resultados para Energy-efficiency


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Purpose – The purpose of this paper is to examine the buyer awareness and acceptance of environmental and energy efficiency measures in the New Zealand residential property markets. This study aims to provide a greater understanding of consumer behaviour in the residential property market in relation to green housing issues ---------- Design/methodology/approach – The paper is based on an extensive survey of Christchurch real estate offices and was designed to gather data on the factors that were considered important by buyers in the residential property market. The survey was designed to allow these factors to be analysed on a socio-economic basis and to compare buyer behaviour based on property values. ---------- Findings – The results show that regardless of income levels, buyers still consider that the most important factor in the house purchase decision is the location of the property and price. Although the awareness of green housing issues and energy efficiency in housing is growing in the residential property market, it is only a major consideration for young and older buyers in the high income brackets and is only of some importance for all other buyer sectors of the residential property market. Many of the voluntary measures introduced by Governments to improve the energy efficiency of residential housing are still not considered important by buyers, indicating that a more mandatory approach may have to be undertaken to improve energy efficiency in the established housing market, as these measures are not valued by the buyer. ---------- Originality/value – The paper confirms the variations in real estate buyer behaviour across the full range of residential property markets and the acceptance and awareness of green housing issues and measures. These results would be applicable to most established and transparent residential property markets.

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Emerging data streaming applications in Wireless Sensor Networks require reliable and energy-efficient Transport Protocols. Our recent Wireless Sensor Network deployment in the Burdekin delta, Australia, for water monitoring [T. Le Dinh, W. Hu, P. Sikka, P. Corke, L. Overs, S. Brosnan, Design and deployment of a remote robust sensor network: experiences from an outdoor water quality monitoring network, in: Second IEEE Workshop on Practical Issues in Building Sensor Network Applications (SenseApp 2007), Dublin, Ireland, 2007] is one such example. This application involves streaming sensed data such as pressure, water flow rate, and salinity periodically from many scattered sensors to the sink node which in turn relays them via an IP network to a remote site for archiving, processing, and presentation. While latency is not a primary concern in this class of application (the sampling rate is usually in terms of minutes or hours), energy-efficiency is. Continuous long-term operation and reliable delivery of the sensed data to the sink are also desirable. This paper proposes ERTP, an Energy-efficient and Reliable Transport Protocol for Wireless Sensor Networks. ERTP is designed for data streaming applications, in which sensor readings are transmitted from one or more sensor sources to a base station (or sink). ERTP uses a statistical reliability metric which ensures the number of data packets delivered to the sink exceeds the defined threshold. Our extensive discrete event simulations and experimental evaluations show that ERTP is significantly more energyefficient than current approaches and can reduce energy consumption by more than 45% when compared to current approaches. Consequently, sensor nodes are more energy-efficient and the lifespan of the unattended WSN is increased.

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Despite the general evolution and broadening of the scope of the concept of infrastructure in many other sectors, the energy sector has maintained the same narrow boundaries for over 80 years. Energy infrastructure is still generally restricted in meaning to the transmission and distribution networks of electricity and, to some extent, gas. This is especially true in the urban development context. This early 20th century system is struggling to meet community expectations that the industry itself created and fostered for many decades. The relentless growth in demand and changing political, economic and environmental challenges require a shift from the traditional ‘predict and provide’ approach to infrastructure which is no longer economically or environmentally viable. Market deregulation and a raft of demand and supply side management strategies have failed to curb society’s addiction to the commodity of electricity. None of these responses has addressed the fundamental problem. This chapter presents an argument for the need for a new paradigm. Going beyond peripheral energy efficiency measures and the substitution of fossil fuels with renewables, it outlines a new approach to the provision of energy services in the context of 21st century urban environments.

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Air quality and temperatures in classrooms are important factors influencing the student learning process. To improve the thermal comfort of classrooms for Queensland State Schools, Queensland Government initiated the "Cooler Schools Program". One of the key objectives under this program was to develop low energy cooling systems as an alternative to high energy demand conventioanl split system of air conditioning (AC) systems. In order to compare and evaluate the energy performance of different types of air conditioners installed in classrooms, monitoring systems were installed in a state primary school located in the greater outer urban area of Brisbane, Australia. It was found that the installation of monitoring systems could have a significant impact on the accuracy of the data being collected. By comparing the estimated energy efficiency ratio (EER)for four qualified air conditioners included in this study, it was also found that AC6, a hybrid air conditioner newly developed by the Queensland Department of Public Works (DPW), had the best energy performance, although the current data were not able to show the full advantages of the system.

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The Australian Government is about to release Australia’s first sustainable population policy. Sustainable population growth, among other things, implies sustainable energy demand. Current modelling of future energy demand both in Australia and by agencies such as the International Energy Agency sees population growth as one of the key drivers of energy demand. Simply increasing the demand for energy in response to population policy is sustainable only if there is a radical restructuring of the energy system away from energy sources associated with environmental degradation towards one more reliant on renewable fuels and less reliant on fossil fuels. Energy policy can also address the present nexus between energy consumption per person and population growth through an aggressive energy efficiency policy. The paper considers the link between population policies and energy policies and considers how the overall goal of sustainability can be achieved. The methods applied in this analysis draw on the literature of sustainable development to develop elements of an energy planning framework to support a sustainable population policy. Rather than simply accept that energy demand is a function of population increase moderated by an assumed rate of energy efficiency improvement, the focus is on considering what rate of energy efficiency improvement is necessary to significantly reduce the standard connections between population growth and growth in energy demand and what policies are necessary to achieve this situation. Energy efficiency policies can only moderate unsustainable aspects of energy demand and other policies are essential to restructure existing energy systems into on-going sustainable forms. Policies to achieve these objectives are considered. This analysis shows that energy policy, population policy and sustainable development policies are closely integrated. Present policy and planning agencies do not reflect this integration and energy and population policies in Australia have largely developed independently and whether the outcome is sustainable is largely a matter of chance. A genuinely sustainable population policy recognises the inter-dependence between population and energy policies and it is essential that this is reflected in integrated policy and planning agencies

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The Australian Government is about to release Australia’s first sustainable population policy. Sustainable population growth, among other things, implies sustainable energy demand. Current modelling of future energy demand both in Australia and by agencies such as the International Energy Agency sees population growth as one of the key drivers of energy demand. Simply increasing the demand for energy in response to population policy is sustainable only if there is a radical restructuring of the energy system away from energy sources associated with environmental degradation towards one more reliant on renewable fuels and less reliant on fossil fuels. Energy policy can also address the present nexus between energy consumption per person and population growth through an aggressive energy efficiency policy. The paper considers the link between population policies and energy policies and considers how the overall goal of sustainability can be achieved. The methods applied in this analysis draw on the literature of sustainable development to develop elements of an energy planning framework to support a sustainable population policy. Rather than simply accept that energy demand is a function of population increase moderated by an assumed rate of energy efficiency improvement, the focus is on considering what rate of energy efficiency improvement is necessary to significantly reduce the standard connections between population growth and growth in energy demand and what policies are necessary to achieve this situation. Energy efficiency policies can only moderate unsustainable aspects of energy demand and other policies are essential to restructure existing energy systems into on-going sustainable forms. Policies to achieve these objectives are considered. This analysis shows that energy policy, population policy and sustainable development policies are closely integrated. Present policy and planning agencies do not reflect this integration and energy and population policies in Australia have largely developed independently and whether the outcome is sustainable is largely a matter of chance. A genuinely sustainable population policy recognises the inter-dependence between population and energy policies and it is essential that this is reflected in integrated policy and planning agencies

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Vertical vegetation is vegetation growing on, or adjacent to, the unused sunlit exterior surfaces of buildings in cities. Vertical vegetation can improve the energy efficiency of the building on which it is installed mainly by insulating, shading and transpiring moisture from foliage and substrate. Several design parameters may affect the extent of the vertical vegetation's improvement of energy performance. Examples are choice of vegetation, growing medium geometry, north/south aspect and others. The purpose of this study is to quantitatively map out the contribution of several parameters to energy savings in a subtropical setting. The method is thermal simulation based on EnergyPlus configured to reflect the special characteristics of vertical vegetation. Thermal simulation results show that yearly cooling energy savings can reach 25% with realistic design choices in subtropical environments. Heating energy savings are negligible. The most important parameter is the aspect of walls covered by vegetation. Vertical vegetation covering walls facing north (south for the northern hemisphere) will result in the highest energy savings. In making plant selections, the most significant parameter is Leaf Area Index (LAI). Plants with larger LAI, preferably LAI>4, contribute to greater savings whereas vertical vegetation with LAI<2 can actually consume energy. The choice of growing media and its thickness influence both heating and cooling energy consumption. Change of growing medium thickness from 6cm to 8cm causes dramatic increase in energy savings from 2% to 18%. For cooling, it is best to use a growing material with high water retention, due to the importance of evapotranspiration for cooling. Similarly, for increased savings in cooling energy, sufficient irrigation is required. Insufficient irrigation results in the vertical vegetation requiring more energy to cool the building. To conclude, the choice of design parameters for vertical vegetation is crucial in making sure that it contributes to energy savings rather than energy consumption. Optimal design decisions can create a dramatic sustainability enhancement for the built environment in subtropical climates.

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Improving energy efficiency has become increasingly important in data centers in recent years to reduce the rapidly growing tremendous amounts of electricity consumption. The power dissipation of the physical servers is the root cause of power usage of other systems, such as cooling systems. Many efforts have been made to make data centers more energy efficient. One of them is to minimize the total power consumption of these servers in a data center through virtual machine consolidation, which is implemented by virtual machine placement. The placement problem is often modeled as a bin packing problem. Due to the NP-hard nature of the problem, heuristic solutions such as First Fit and Best Fit algorithms have been often used and have generally good results. However, their performance leaves room for further improvement. In this paper we propose a Simulated Annealing based algorithm, which aims at further improvement from any feasible placement. This is the first published attempt of using SA to solve the VM placement problem to optimize the power consumption. Experimental results show that this SA algorithm can generate better results, saving up to 25 percentage more energy than First Fit Decreasing in an acceptable time frame.

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Server consolidation using virtualization technology has become an important technology to improve the energy efficiency of data centers. Virtual machine placement is the key in the server consolidation. In the past few years, many approaches to the virtual machine placement have been proposed. However, existing virtual machine placement approaches to the virtual machine placement problem consider the energy consumption by physical machines in a data center only, but do not consider the energy consumption in communication network in the data center. However, the energy consumption in the communication network in a data center is not trivial, and therefore should be considered in the virtual machine placement in order to make the data center more energy-efficient. In this paper, we propose a genetic algorithm for a new virtual machine placement problem that considers the energy consumption in both the servers and the communication network in the data center. Experimental results show that the genetic algorithm performs well when tackling test problems of different kinds, and scales up well when the problem size increases.

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This paper reviews electricity consumption feedback literature to explore the potential of electricity feedback to affect residential consumers’ electricity usage patterns. The review highlights a substantial amount of literature covering the debate over the effectiveness of different feedback criteria to residential customer acceptance and overall conservation and peak demand reduction. Researchers studying the effects of feedback on everyday energy use have observed substantial variation in effect size, both within and between studies. Although researchers still continue to question the types of feedback that are most effective in encouraging conservation and peak load reduction, some trends have emerged. These include that feedback be received as quickly as possible to the time of consumption; be related to a standard; be clear and meaningful and where possible both direct and indirect feedback be customised to the customer. In general, the literature finds that feedback can reduce electricity consumption in homes by 5 to 20 per cent, but that significant gaps remain in our knowledge of the effectiveness and cost benefit of feedback.

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GPS is a commonly used and convenient technology for determining absolute position in outdoor environments, but its high power consumption leads to rapid battery depletion in mobile devices. An obvious solution is to duty cycle the GPS module, which prolongs the device lifetime at the cost of increased position uncertainty while the GPS is off. This article addresses the trade-off between energy consumption and localization performance in a mobile sensor network application. The focus is on augmenting GPS location with more energy-efficient location sensors to bound position estimate uncertainty while GPS is off. Empirical GPS and radio contact data from a large-scale animal tracking deployment is used to model node mobility, radio performance, and GPS. Because GPS takes a considerable, and variable, time after powering up before it delivers a good position measurement, we model the GPS behaviour through empirical measurements of two GPS modules. These models are then used to explore duty cycling strategies for maintaining position uncertainty within specified bounds. We then explore the benefits of using short-range radio contact logging alongside GPS as an energy-inexpensive means of lowering uncertainty while the GPS is off, and we propose strategies that use RSSI ranging and GPS back-offs to further reduce energy consumption. Results show that our combined strategies can cut node energy consumption by one third while still meeting application-specific positioning criteria.

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Energy efficiency of buildings is attracting significant attention from the research community as the world is moving towards sustainable buildings design. Energy efficient approaches are measures or ways to improve the energy performance and energy efficiency of buildings. This study surveyed various energy-efficient approaches for commercial building and identifies Envelope Thermal Transfer Value (ETTV) and Green applications (Living wall, Green facade and Green roof) as most important and effective methods. An in-depth investigation was carried out on these energy-efficient approaches. It has been found that no ETTV model has been developed for sub-tropical climate of Australia. Moreover, existing ETTV equations developed for other countries do not take roof heat gain into consideration. Furthermore, the relationship of ETTV and different Green applications have not been investigated extensively in any literature, and the energy performance of commercial buildings in the presence of Living wall, Green facade and Green roof has not been investigated in the sub-tropical climate of Australia. The study has been conducted in two phases. First, the study develops the new formulation, coefficient and bench mark value of ETTV in the presence of external shading devices. In the new formulation, roof heat gain has been included in the integrated heat gain model made of ETTV. In the 2nd stage, the study presents the relationship of thermal and energy performance of (a) Living wall and ETTV (b) Green facade and ETTV (c) Combination of Living wall, Green facade and ETTV (d) Combination of Living wall, Green Roof and ETTV in new formulations. Finally, the study demonstrates the amount of energy that can be saved annually from different combinations of Green applications, i.e., Living wall, Green facade; combination of Living wall and Green facade; combination of Living wall and Green roof. The estimations are supported by experimental values obtained from extensive experiments of Living walls and Green roofs.

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Since the first oil crisis in 1974, economic reasons placed energy saving among the top priorities in most industrialised countries. In the decades that followed, another, equally strong driver for energy saving emerged: climate change caused by anthropogenic emissions, a large fraction of which result from energy generation. Intrinsically linked to energy consumption and its related emissions is another problem: indoor air quality. City dwellers in industrialised nations spend over 90% of their time indoors and exposure to indoor pollutants contributes to ~2.6% of global burden of disease and nearly 2 million premature deaths per year1. Changing climate conditions, together with human expectations of comfortable thermal conditions, elevates building energy requirements for heating, cooling, lighting and the use of other electrical equipment. We believe that these changes elicit a need to understand the nexus between energy consumption and its consequent impact on indoor air quality in urban buildings. In our opinion the key questions are how energy consumption is distributed between different building services, and how the resulting pollution affects indoor air quality. The energy-pollution nexus has clearly been identified in qualitative terms; however the quantification of such a nexus to derive emissions or concentrations per unit energy consumption is still weak, inconclusive and requires forward thinking. Of course, various aspects of energy consumption and indoor air quality have been studied in detail separately, but in-depth, integrated studies of the energy-pollution nexus are hard to come by. We argue that such studies could be instrumental in providing sustainable solutions to maintain the trade-off between the energy efficiency of buildings and acceptable levels of air pollution for healthy living.

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Electricity cost has become a major expense for running data centers and server consolidation using virtualization technology has been used as an important technology to improve the energy efficiency of data centers. In this research, a genetic algorithm and a simulation-annealing algorithm are proposed for the static virtual machine placement problem that considers the energy consumption in both the servers and the communication network, and a trading algorithm is proposed for dynamic virtual machine placement. Experimental results have shown that the proposed methods are more energy efficient than existing solutions.

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Energy auditing is an effective but costly approach for reducing the long-term energy consumption of buildings. When well-executed, energy loss can be quickly identified in the building structure and its subsystems. This then presents opportunities for improving energy efficiency. We present a low-cost, portable technology called "HeatWave" which allows non-experts to generate detailed 3D surface temperature models for energy auditing. This handheld 3D thermography system consists of two commercially available imaging sensors and a set of software algorithms which can be run on a laptop. The 3D model can be visualized in real-time by the operator so that they can monitor their degree of coverage as the sensors are used to capture data. In addition, results can be analyzed offline using the proposed "Spectra" multispectral visualization toolbox. The presence of surface temperature data in the generated 3D model enables the operator to easily identify and measure thermal irregularities such as thermal bridges, insulation leaks, moisture build-up and HVAC faults. Moreover, 3D models generated from subsequent audits of the same environment can be automatically compared to detect temporal changes in conditions and energy use over time.