126 resultados para Peak demand

em Queensland University of Technology - ePrints Archive


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The aim of this work is to develop a Demand-Side-Response (DSR) model, which assists electricity end-users to be engaged in mitigating peak demands on the electricity network in Eastern and Southern Australia. The proposed innovative model will comprise a technical set-up of a programmable internet relay, a router, solid state switches in addition to the suitable software to control electricity demand at user's premises. The software on appropriate multimedia tool (CD Rom) will be curtailing/shifting electric loads to the most appropriate time of the day following the implemented economic model, which is designed to be maximizing financial benefits to electricity consumers. Additionally the model is targeting a national electrical load be spread-out evenly throughout the year in order to satisfy best economic performance for electricity generation, transmission and distribution. The model is applicable in region managed by the Australian Energy Management Operator (AEMO) covering states of Eastern-, Southern-Australia and Tasmania.

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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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More evenly spread demand for public transport throughout a day can reduce transit service provider‟s total asset and labour costs. A plausible peak spreading strategy is to increase peak fare and/or to reduce off-peak fare. This paper reviews relevant empirical studies for urban rail systems, as rail transit plays a key role in Australian urban passenger transport and experiences severe peak loading variability. The literature is categorised into four groups: a) passenger opinions on willingness to change time for travel, b) valuations of displacement time using stated preference technique, c) simulations of peak spreading based on trip scheduling models, and: d) real-world cases of peak spreading using differential fare. Policy prescription is advised to take into account impacts of traveller‟s time flexibility and joint effects of mode shifting and peak spreading. Although focusing on urban rail, arguments in this paper are relevant to public transport in general with values to researchers and practitioners.

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Provision of network infrastructure to meet rising network peak demand is increasing the cost of electricity. Addressing this demand is a major imperative for Australian electricity agencies. The network peak demand model reported in this paper provides a quantified decision support tool and a means of understanding the key influences and impacts on network peak demand. An investigation of the system factors impacting residential consumers’ peak demand for electricity was undertaken in Queensland, Australia. Technical factors, such as the customers’ location, housing construction and appliances, were combined with social factors, such as household demographics, culture, trust and knowledge, and Change Management Options (CMOs) such as tariffs, price,managed supply, etc., in a conceptual ‘map’ of the system. A Bayesian network was used to quantify the model and provide insights into the major influential factors and their interactions. The model was also used to examine the reduction in network peak demand with different market-based and government interventions in various customer locations of interest and investigate the relative importance of instituting programs that build trust and knowledge through well designed customer-industry engagement activities. The Bayesian network was implemented via a spreadsheet with a tick box interface. The model combined available data from industry-specific and public sources with relevant expert opinion. The results revealed that the most effective intervention strategies involve combining particular CMOs with associated education and engagement activities. The model demonstrated the importance of designing interventions that take into account the interactions of the various elements of the socio-technical system. The options that provided the greatest impact on peak demand were Off-Peak Tariffs and Managed Supply and increases in the price of electricity. The impact in peak demand reduction differed for each of the locations and highlighted that household numbers, demographics as well as the different climates were significant factors. It presented possible network peak demand reductions which would delay any upgrade of networks, resulting in savings for Queensland utilities and ultimately for households. The use of this systems approach using Bayesian networks to assist the management of peak demand in different modelled locations in Queensland provided insights about the most important elements in the system and the intervention strategies that could be tailored to the targeted customer segments.

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The aims of this project is to develop demand side response model which assists electricity consumers who are exposed to the market price through aggregator to manage the air-conditioning peak electricity demand. The main contribution of this research is to show how consumers can optimise the energy cost caused by the air-conditioning load considering the electricity market price and network overload. The model is tested with selected characteristics of the room, Queensland electricity market data from Australian Energy Market Operator and data from the Bureau of Statistics on temperatures in Brisbane, during weekdays on hot days from 2011 - 2012.

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Depleting fossil fuel resources and increased accumulation of greenhouse gas emissions are increasingly making electrical vehicles (EV) attractive option for the transportation sector. However uncontrolled random charging and discharging of EVs may aggravate the problems of an already stressed system during the peak demand and cause voltage problems during low demand. This paper develops a demand side response scheme for properly integrating EVs in the Electrical Network. The scheme enacted upon information on electricity market conditions regularly released by the Australian Energy Market Operator (AEMO) on the internet. The scheme adopts Internet relays and solid state switches to cycle charging and discharging of EVs. Due to the pending time-of-use and real-price programs, financial benefits will represent driving incentives to consumers to implement the scheme. A wide-scale dissemination of the scheme is expected to mitigate excessive peaks on the electrical network with all associated technical, economic and social benefits.

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The growing demand of air-conditioning is one of the largest contributors to Australia’s overall electricity consumption. This has started to create peak load supply problems for some electricity utilities particularly in Queensland. This research aimed to develop consumer demand side response model to assist electricity consumers to mitigate peak demand on the electrical network. The model developed demand side response model to allow consumers to manage and control air conditioning for every period, it is called intelligent control. This research investigates optimal response of end-user toward electricity price for several cases in the near future, such as: no spike, spike and probability spike price cases. The results indicate the potential of the scheme to achieve energy savings, reducing electricity bills (costs) to the consumer and targeting best economic performance for electrical generation distribution and transmission.

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Technologies such as smart meters and electricity feedback are becoming an increasingly compelling focus for HCI researchers in light of rising power prices and peak demand. We argue, however, that a pre-occupation with the goal of demand management has limited the scope of design for these technologies. In this paper we present our work-in-progress investigating the potential value of socially sharing electricity information as a means of broadening the scope of design for these devices. This paper outlines some preliminary findings gathered from a design workshop and a series of qualitative interviews with householders in Brisbane, Australia, regarding their attitudes towards electricity feedback and sharing consumption information. Preliminary findings suggest that; (1) the social sharing of electricity feedback information has the potential to be of value in better informing consumption decisions, however; (2) the potential for sharing may be constrained by attitudes towards privacy, trust and the possibility of misinformation being shared. We conclude by outlining ideas for our future research on this topic and invite comments on these ideas.

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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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This paper proposes a reward based demand response algorithm for residential customers to shave network peaks. Customer survey information is used to calculate various criteria indices reflecting their priority and flexibility. Criteria indices and sensitivity based house ranking is used for appropriate load selection in the feeder for demand response. Customer Rewards (CR) are paid based on load shift and voltage improvement due to load adjustment. The proposed algorithm can be deployed in residential distribution networks using a two-level hierarchical control scheme. Realistic residential load model consisting of non-controllable and controllable appliances is considered in this study. The effectiveness of the proposed demand response scheme on the annual load growth of the feeder is also investigated. Simulation results show that reduced peak demand, improved network voltage performance, and customer satisfaction can be achieved.

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Background Radiographic examinations of the ankle are important in the clinical management of ankle injuries in hospital emergency departments. National (Australian) Emergency Access Targets (NEAT) stipulate that 90 percent of presentations should leave the emergency department within 4 hours. For a radiological report to have clinical usefulness and relevance to clinical teams treating patients with ankle injuries in emergency departments, the report would need to be prepared and available to the clinical team within the NEAT 4 hour timeframe; before the patient has left the emergency department. However, little is known about the demand profile of ankle injuries requiring radiographic examination or time until radiological reports are available for this clinical group in Australian public hospital emergency settings. Methods This study utilised a prospective cohort of consecutive cases of ankle examinations from patients (n=437) with suspected traumatic ankle injuries presenting to the emergency department of a tertiary hospital facility. Time stamps from the hospital Picture Archiving and Communication System were used to record the timing of three processing milestones for each patient's radiographic examination; the time of image acquisition, time of a provisional radiological report being made available for viewing by referring clinical teams, and time of final verification of radiological report. Results Radiological reports and all three time stamps were available for 431 (98.6%) cases and were included in analysis. The total time between image acquisition and final radiological report verification exceeded 4?hours for 404 (92.5%) cases. The peak demand for radiographic examination of ankles was on weekend days, and in the afternoon and evening. The majority of examinations were provisionally reported and verified during weekday daytime shift hours. Conclusions Provisional or final radiological reports were frequently not available within 4 hours of image acquisition among this sample. Effective and cost-efficient strategies to improve the support provided to referring clinical teams from medical imaging departments may enhance emergency care interventions for people presenting to emergency departments with ankle injuries; particularly those with imaging findings that may be challenging for junior clinical staff to interpret without a definitive radiological report.

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Utilities worldwide are focused on supplying peak electricity demand reliably and cost effectively, requiring a thorough understanding of all the factors influencing residential electricity use at peak times. An electricity demand reduction project based on comprehensive residential consumer engagement was established within an Australian community in 2008, and by 2011, peak demand had decreased to below pre-intervention levels. This paper applied field data discovered through qualitative in-depth interviews of 22 residential households at the community to a Bayesian Network complex system model to examine whether the system model could explain successful peak demand reduction in the case study location. The knowledge and understanding acquired through insights into the major influential factors and the potential impact of changes to these factors on peak demand would underpin demand reduction intervention strategies for a wider target group.

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Peak electricity demand requires substantial investment to update transmission, distribution and generation infrastructure. A successful community peak demand reduction project was examined to identify residential consumer motivational and contextual factors involved in their decision to adopt/not adopt interventions. Energy professionals actively worked to achieve community 'peer' membership and by becoming a trusted information source, facilitated voluntary home energy assessment requests from over 80% of the residential community. By combining and tailoring interventions to the specific needs and motivations of individual householders and the community, interventions promoting energy conservation and efficiency can be effective in achieving sustained reduction in peak demand.

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Cool roof coatings have a beneficial impact on reducing the heat load of a range of building types, resulting in reduced cooling energy loads. This study seeks to understand the extent to which cool roof coatings could be used as a residential demand side management (DSM) strategy for retrofitting existing housing in a constrained network area in tropical Australia where peak electrical demand is heavily influenced by residential cooling loads. In particular this study seeks to determine whether simulation software used for building regulation purposes can provide networks with the ‘impact certainty’ required by their DSM principles. The building simulation method is supported by a field experiment. Both numerical and experimental data confirm reductions in total consumption (kWh) and energy demand (kW). The nature of the regulated simulation software, combined with the diverse nature of residential buildings and their patterns of occupancy, however, mean that simulated results cannot be extrapolated to quantify benefits to a broader distribution network. The study suggests that building data gained from regulatory simulations could be a useful guide for potential impacts of widespread application of cool roof coatings in this region. The practical realization of these positive impacts, however, would require changes to the current business model for the evaluation of DSM strategies. The study provides seven key recommendations that encourage distribution networks to think beyond their infrastructure boundaries, recognising that the broader energy system also includes buildings, appliances and people.

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Introduction: The purpose of this study was to assess the capacity of a written intervention, in this case a patient information brochure, to improve patient satisfaction during an Emergency Department (ED) visit. For the purpose of measuring the effect of the intervention the ED journey was conceptualised as a series of distinct areas of service comprising waiting time, service by the triage nurse, care from doctors and nurses and information giving Background of study: Research into patient satisfaction has become a widespread activity endorsed by both governments and hospital administrations. The literature on ED patient satisfaction has consistently indicated three primary areas of patient dissatisfaction: waiting time, nursing care and communication. Recent developments in the literature on patient satisfaction studies however have highlighted the relationship between patients. expectations of a service encounter and their consequent assessment of the experience as dissatisfying or satisfying. Disconfirmation theory posits that the degree to which expectations are confirmed will affect subsequent levels of satisfaction. The conceptual framework utilised in this study is Coye.s (2004) model of disconfirmation. Coye while reiterating satisfaction is a consequence of the degree expectations are either confirmed or disconfirmed also posits that expectations can be modified by interventions. Coye.s work conceptualises these interventions as intra encounter experiences (cues) which function to adjust expectations. Coye suggests some cues are unintended and may have a negative impact which also reinforces the value of planned cues intended to meet or exceed consumer expectations. Consequently the brochure can be characterized as a potentially positive cue, encouraging the patient to understand processes and to orient them in what can be a confronting environment. Only a limited number of studies have examined the effect of written interventions within an ED. No studies could be located which have tested the effect of ED interventions using a conceptual framework which relates the effect of the degree to which expectations are confirmed or disconfirmed in terms of satisfaction with services. Method: Two studies were conducted. Study One used qualitative methods to explore patients. expectations of the ED from the perspective of both patients and health care professionals. Study One was used in part to direct the development of the intervention (brochure) in Study Two. The brochure was an intervention designed to modify patients. expectations thus increasing their satisfaction with the provision of ED service. As there was no existing tools to measure ED patients. expectations and satisfaction a new tool was also developed based on the findings and the literature of Study One. Study Two used a non-randomised, quasi-experimental approach using a non-equivalent post-test only comparison group design used to investigate the effect of the patient education brochure (Stommel and Wills, 2004). The brochure was disseminated to one of two study groups (the intervention group). The effect of the brochure was assessed by comparing the data obtained from both the intervention and control group. These two groups consisted of 150 participants each. It was expected that any differences in the relevant domains selected for examination would indicate the effect of the brochure both on expectation and potentially satisfaction. Results: Study One revealed several areas of common ground between patients and nurses in terms of relevant content for the written intervention, including the need for information on the triage system and waiting times. Areas of difference were also found with patients emphasizing communication issues, whereas focus group members expressed concern that patients were often unable to assimilate verbal information. The findings suggested the potential utility of written material to reinforce verbal communication particularly in terms of the triage process and other ED protocols. This material was synthesized within the final version of the written intervention. Overall the results of Study Two indicated no significant differences between the two groups. The intervention group did indicate a significant number of participants who viewed the brochure of having changed their expectations. The effect of the brochure may have been obscured by a lack of parity between the two groups as the control group presented with statistically significantly higher levels of acuity and experienced significantly shorter waiting times. In terms of disconfirmation theory this would suggest expectations that had been met or exceeded. The results confirmed the correlation of expectations with satisfaction. Several domains also indicated age as a significant predictor with older patients tending to score higher satisfaction results. Other significant predictors of satisfaction established were waiting time and care from nurses, reinforcing the combination of efficient service and positive interpersonal experiences as being valued by patients. Conclusions: Information presented in written form appears to benefit a significant number of ED users in terms of orientation and explaining systems and procedures. The degree to which these effects may interact with other dimensions of satisfaction however is likely to be limited. Waiting time and interpersonal behaviours from staff also provide influential cues in determining satisfaction. Written material is likely to be one element in a series of coordinated strategies to improve patient satisfaction during periods of peak demand.