113 resultados para Network Cost Allocation

em University of Queensland eSpace - Australia


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This paper proposes a transmission and wheeling pricing method based on the monetary flow tracing along power flow paths: the monetary flow-monetary path method. Active and reactive power flows are converted into monetary flows by using nodal prices. The method introduces a uniform measurement for transmission service usages by active and reactive powers. Because monetary flows are related to the nodal prices, the impacts of generators and loads on operation constraints and the interactive impacts between active and reactive powers can be considered. Total transmission service cost is separated into more practical line-related costs and system-wide cost, and can be flexibly distributed between generators and loads. The method is able to reconcile transmission service cost fairly and to optimize transmission system operation and development. The case study on the IEEE 30 bus test system shows that the proposed pricing method is effective in creating economic signals towards the efficient use and operation of the transmission system. (c) 2005 Elsevier B.V. All rights reserved.

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This paper critically assesses several loss allocation methods based on the type of competition each method promotes. This understanding assists in determining which method will promote more efficient network operations when implemented in deregulated electricity industries. The methods addressed in this paper include the pro rata [1], proportional sharing [2], loss formula [3], incremental [4], and a new method proposed by the authors of this paper, which is loop-based [5]. These methods are tested on a modified Nordic 32-bus network, where different case studies of different operating points are investigated. The varying results obtained for each allocation method at different operating points make it possible to distinguish methods that promote unhealthy competition from those that encourage better system operation.

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Objective: To assess from a health sector perspective the incremental cost-effectiveness of cognitive behavioural therapy (CBT) and selective serotonin reuptake inhibitors (SSRIs) for the treatment of major depressive disorder (MDD) in children and adolescents, compared to 'current practice'. Method: The health benefit is measured as a reduction in disability-adjusted life years (DALYs), based on effect size calculations from meta-analysis of randomised controlled trials. An assessment on second stage filter criteria ('equity'; 'strength of evidence', 'feasibility' and 'acceptability to stakeholders') is also undertaken to incorporate additional factors that impact on resource allocation decisions. Costs and benefits are tracked for the duration of a new episode of MDD arising in eligible children (age 6-17 years) in the Australian population in the year 2000. Simulation-modelling techniques are used to present a 95% uncertainty interval (UI) around the cost-effectiveness ratios. Results: Compared to current practice, CBT by public psychologists is the most cost-effective intervention for MDD in children and adolescents at A$9000 per DALY saved (95% UI A$3900 to A$24 000). SSRIs and CBT by other providers are less cost-effective but likely to be less than A$50 000 per DALY saved (> 80% chance). CBT is more effective than SSRIs in children and adolescents, resulting in a greater total health benefit (DALYs saved) than could be achieved with SSRIs. Issues that require attention for the CBT intervention include equity concerns, ensuring an adequate workforce, funding arrangements and acceptability to various stakeholders. Conclusions: Cognitive behavioural therapy provided by a public psychologist is the most effective and cost-effective option for the first-line treatment of MDD in children and adolescents. However, this option is not currently accessible by all patients and will require change in policy to allow more widespread uptake. It will also require 'start-up' costs and attention to ensuring an adequate workforce.

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Objective: To analyze from a health sector perspective the cost-effectiveness of dexamphetamine (DEX) and methylphenidate (MPH) interventions to treat childhood attention deficit hyperactivity disorder (ADHD), compared to current practice. Method: Children eligible for the interventions are those aged between 4 and 17 years in 2000, who had ADHD and were seeking care for emotional or behavioural problems, but were not receiving stimulant medication. To determine health benefit, a meta-analysis of randomized controlled trials was performed for DEX and MPH, and the effect sizes were translated into utility values. An assessment on second stage filter criteria ('equity', 'strength of evidence', 'feasibility' and 'acceptability to stakeholders') is also undertaken to incorporate additional factors that impact on resource allocation decisions. Simulation modelling techniques are used to present a 95% uncertainty interval (UI) around the incremental cost-effectiveness ratio (ICER), which is calculated in cost (in A$) per DALY averted. Results: The ICER for DEX is A$4100/DALY saved (95% UI: negative to A$14 000) and for MPH is A$15 000/DALY saved (95% UI: A$9100-22 000). DEX is more costly than MPH for the government, but much less costly for the patient. Conclusions: MPH and DEX are cost-effective interventions for childhood ADHD. DEX is more cost-effective than MPH, although if MPH were listed at a lower price on the Pharmaceutical Benefits Scheme it would become more cost-effective. Increased uptake of stimulants for ADHD would require policy change. However, the medication of children and wider availability of stimulants may concern parents and the community.

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Objective: To assess from a health sector perspective the incremental cost-effectiveness of interventions for generalized anxiety disorder (cognitive behavioural therapy [CBT] and serotonin and noradrenaline reuptake inhibitors [SNRIs]) and panic disorder (CBT, selective serotonin reuptake inhibitors [SSRIs] and tricyclic antidepressants [TCAs]). Method: The health benefit is measured as a reduction in disability-adjusted life years (DALYs), based on effect size calculations from meta-analyses of randomised controlled trials. An assessment on second stage filters ('equity', 'strength of evidence', 'feasibility' and 'acceptability to stakeholders') is also undertaken to incorporate additional factors that impact on resource allocation decisions. Costs and benefits are calculated for a period of one year for the eligible population (prevalent cases of generalized anxiety disorder/panic disorder identified in the National Survey of Mental Health and Wellbeing, extrapolated to the Australian population in the year 2000 for those aged 18 years and older). Simulation modelling techniques are used to present 95% uncertainty intervals (UI) around the incremental cost-effectiveness ratios (ICERs). Results: Compared to current practice, CBT by a psychologist on a public salary is the most cost-effective intervention for both generalized anxiety disorder (A$6900/DALY saved; 95% UI A$4000 to A$12 000) and panic disorder (A$6800/DALY saved; 95% UI A$2900 to A$15 000). Cognitive behavioural therapy results in a greater total health benefit than the drug interventions for both anxiety disorders, although equity and feasibility concerns for CBT interventions are also greater. Conclusions: Cognitive behavioural therapy is the most effective and cost-effective intervention for generalized anxiety disorder and panic disorder. However, its implementation would require policy change to enable more widespread access to a sufficient number of trained therapists for the treatment of anxiety disorders.

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Low-cost UHF-band p-i-n diodes are used to develop high-performance L-band series and parallel switches. To stop the rectification of large RF, signals, the diodes are biased at a large reverse-bias voltage. Parasitic elements of the diodes are tuned out using LC circuits in biasing circuits without increasing the size of the switches. (C) 2002 John Wiley Sons, Inc.

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This article presents Monte Carlo techniques for estimating network reliability. For highly reliable networks, techniques based on graph evolution models provide very good performance. However, they are known to have significant simulation cost. An existing hybrid scheme (based on partitioning the time space) is available to speed up the simulations; however, there are difficulties with optimizing the important parameter associated with this scheme. To overcome these difficulties, a new hybrid scheme (based on partitioning the edge set) is proposed in this article. The proposed scheme shows orders of magnitude improvement of performance over the existing techniques in certain classes of network. It also provides reliability bounds with little overhead.

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The Swinfen Charitable Trust has used email for some years as a low-cost telemedicine medium to provide consultant support for doctors in developing countries. A scalable, automatic message-routing system was constructed which automates many of the tasks involved in message handling. During the first 12 months of its use, 1510 messages were processed automatically. There were 128 referrals from 18 hospitals in nine countries. Of these 128 queries, 89 (70%) were replied to within 72 h; the median delay was 1.1 day. The 39 unanswered queries were sent to backup specialists for reply and 36 of them (92%) were replied to within 72 h. In the remaining three cases, a second-line (backup) specialist was required. The referrals were handled by 54 volunteer specialists from a panel of over 70. Two system operators, located 10 time zones apart, managed the system. The median time from receipt of a new referral to its allocation to a specialist was 0.2 days (interquartile range, IQR, 0.1-0.8). The median interval between receipt of a new referral and first reply was 2.6 days (IQR 0.8-5.9). Automatic message handling solves many of the problems of manual email telemedicine systems and represents a potentially scalable way of doing low-cost telemedicine in the developing world.

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Identifying water wastage in forms of leaks in a water distribution network of any city becomes essential as droughts are presenting serious threats to few major cities. In this paper, we propose a deployment of sensor network for monitoring water flow in any water distribution network. We cover the issues related with designing such a dedicated sensor network by considering types of sensors required, sensors' functionality, data collection, and providing computation serving as leak detection mechanism. The main focus of this paper is on appropriate network segmentation that provides the base for hierarchical approach to pipes' failure detection. We show a method for sensors allocation to the network in order to facilitate effective pipes monitoring. In general, the identified computational problem belongs to hard problems. The paper shows a heuristic method to build effective hierarchy of the network segmentation.

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A new methodology is proposed for the analysis of generation capacity investment in a deregulated market environment. This methodology proposes to make the investment appraisal using a probabilistic framework. The probabilistic production simulation (PPC) algorithm is used to compute the expected energy generated, taking into account system load variations and plant forced outage rates, while the Monte Carlo approach has been applied to model the electricity price variability seen in a realistic network. The model is able to capture the price and hence the profitability uncertainties for generator companies. Seasonal variation in the electricity prices and the system demand are independently modeled. The method is validated on IEEE RTS system, augmented with realistic market and plant data, by using it to compare the financial viability of several generator investments applying either conventional or directly connected generator (powerformer) technologies. The significance of the results is assessed using several financial risk measures.

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Email has been used for some years as a low-cost telemedicine medium to provide support for developing countries. However, all operations have been relatively small scale and fairly labour intensive to administer. A scalable, automatic message-routing system was constructed which automates many of the tasks. During a four-month study period in 2002, 485 messages were processed automatically. There were 31 referrals from eight hospitals in three countries. These referrals were handled by 25 volunteer specialists from a panel of 42. Two system operators, located 10 time zones apart, managed the system. The median time from receipt of a new referral to its allocation to a specialist was 1.0 days (interquartile range 0.7-2.4). The median interval between allocation and first reply was 0.7 days (interquartile range 0.3-2.3). Automatic message handling solves many of the problems of manual email telemedicine systems and represents a potentially scalable way of doing low-cost telemedicine in the developing world.

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Quasi-birth-and-death (QBD) processes with infinite “phase spaces” can exhibit unusual and interesting behavior. One of the simplest examples of such a process is the two-node tandem Jackson network, with the “phase” giving the state of the first queue and the “level” giving the state of the second queue. In this paper, we undertake an extensive analysis of the properties of this QBD. In particular, we investigate the spectral properties of Neuts’s R-matrix and show that the decay rate of the stationary distribution of the “level” process is not always equal to the convergence norm of R. In fact, we show that we can obtain any decay rate from a certain range by controlling only the transition structure at level zero, which is independent of R. We also consider the sequence of tandem queues that is constructed by restricting the waiting room of the first queue to some finite capacity, and then allowing this capacity to increase to infinity. We show that the decay rates for the finite truncations converge to a value, which is not necessarily the decay rate in the infinite waiting room case. Finally, we show that the probability that the process hits level n before level 0 given that it starts in level 1 decays at a rate which is not necessarily the same as the decay rate for the stationary distribution.