18 resultados para transmission cost allocation

em QUB Research Portal - Research Directory and Institutional Repository for Queen's University Belfast


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This study presents a new method for determining the transmission network usage by loads and generators, which can then be used for transmission cost/loss allocation in an explainable and justifiable manner. The proposed method is based on solid physical grounds and circuit theory. It relies on dividing the currents through the network into two components; the first one is attributed to power flows from generators to loads, whereas the second one is because of the generators only. Unlike almost all the available methods, the proposed method is assumption free and hence it is more accurate than similar methods even those having some physical basis. The proposed method is validated through a transformer analogy, and theoretical derivations. The method is verified through application to the IEEE 30 bus system and the IEEE 118 test system. The results obtained verified many desirable features of the proposed method. Being more accurate in determining the network usage, in an explainable transparent manner, and in giving accurate cost signals, indicating the best locations to add loads and generation, are among the many desirable features.

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This paper presents a new method for transmission loss allocation. The method is based on tracing the complex power flow through the network and determining the share of each load on the flow and losses through each line. Transmission losses are taken into consideration during power flow tracing. Unbundling line losses is carried out using an equation, which has a physical basis, and considers the coupling between active and reactive power flows as well as the cross effects of active and reactive power on active and reactive losses. A tracing algorithm which can be considered direct to a good extent, as there is no need for exhaustive search to determine the flow paths as these are determined in a systematic way during the course of tracing. Results of application of the proposed method are also presented.

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This paper presents a new method for transmission loss allocation in a deregulated electrical power market. The proposed method is based on physical flow through transmission lines. The contributions of individual loads to the line flows are used as basis for allocating transmission losses to different loads. With minimum assumptions, that sound to be reasonable and cannot be rejected, a novel loss allocation formula is derived. The assumptions made are: a number of currents sharing a transmission line distribute themselves over the cross section in the same manner; that distribution causes the minimum possible power loss. Application of the proposed method is straightforward. It requires only a solved power flow and any simple algorithm for power flow tracing. Both active and reactive powers are considered in the loss allocation procedure. Results of application show the accuracy of the proposed method compared with the commonly used procedures.

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A new method is presented for transmission loss allocation based on the separation of transmission loss caused by load and the loss due to circulating currents between generators. The theoretical basis for and derivation of the loss formulae are presented using simple systems. The concept is then extended to a general power system using the Ybus model. Details of the application of the proposed method to a typical power system are presented along with results from the IEEE 30 bus test system. The results from both the small system and the standard IEEE test system demonstrate the validity of the proposed method.

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We consider the problem of secure transmission in two-hop amplify-and-forward untrusted relay networks. We analyze the ergodic secrecy capacity (ESC) and present compact expressions for the ESC in the high signal-to-noise ratio regime. We also examine the impact of large scale antenna arrays at either the source or the destination. For large antenna arrays at the source, we confirm that the ESC is solely determined by the channel between the relay and the destination. For very large antenna arrays at the destination, we confirm that the ESC is solely determined by the channel between the source and the relay.

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This study proposes an approach to optimally allocate multiple types of flexible AC transmission system (FACTS) devices in market-based power systems with wind generation. The main objective is to maximise profit by minimising device investment cost, and the system's operating cost considering both normal conditions and possible contingencies. The proposed method accurately evaluates the long-term costs and benefits gained by FACTS devices (FDs) installation to solve a large-scale optimisation problem. The objective implies maximising social welfare as well as minimising compensations paid for generation re-scheduling and load shedding. Many technical operation constraints and uncertainties are included in problem formulation. The overall problem is solved using both particle swarm optimisations for attaining optimal FDs allocation as main problem and optimal power flow as sub-optimisation problem. The effectiveness of the proposed approach is demonstrated on modified IEEE 14-bus test system and IEEE 118-bus test system.

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We develop and apply a valuation methodology to calculate the cost of sustainability capital, and, eventually, sustainable value creation of companies. Sustainable development posits that decisions must take into account all forms of capital rather than just economic capital. We develop a methodology that allows calculation of the costs that are associated with the use of different forms of capital. Our methodology borrows the idea from financial economics that the return on capital has to cover the cost of capital. Capital costs are determined as opportunity costs, that is, the forgone returns that would have been created by alternative investments. We apply and extend the logic of opportunity costs to the valuation not only of economic capital but also of other forms of capital. This allows (a) integrated analysis of use of different forms of capital based on a value-based aggregation of different forms of capital, (b) determination of the opportunity cost of a bundle of different forms of capital used in a company, called cost of sustainability capital, (c) calculation of sustainability efficiency of companies, and (d) calculation of sustainable value creation, that is, the value above the cost of sustainability capital. By expanding the well-established logic of the valuation of economic capital in financial markets to cover other forms of capital, we provide a methodology that allows determination of the most efficient allocation of sustainability capital for sustainable value creation in companies. We demonstrate the practicability of the methodology by the valuation of the sustainability performance of British Petroleum (BP).

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For a digital echo canceller it is desirable to reduce the adaptation time, during which the transmission of useful data is not possible. LMS is a non-optimal algorithm in this case as the signals involved are statistically non-Gaussian. Walach and Widrow (IEEE Trans. Inform. Theory 30 (2) (March 1984) 275-283) investigated the use of a power of 4, while other research established algorithms with arbitrary integer (Pei and Tseng, IEEE J. Selected Areas Commun. 12(9)(December 1994) 1540-1547) or non-quadratic power (Shah and Cowan, IEE.Proc.-Vis. Image Signal Process. 142 (3) (June 1995) 187-191). This paper suggests that continuous and automatic, adaptation of the error exponent gives a more satisfactory result. The family of cost function adaptation (CFA) stochastic gradient algorithm proposed allows an increase in convergence rate and, an improvement of residual error. As special case the staircase CFA algorithm is first presented, then the smooth CFA is developed. Details of implementations are also discussed. Results of simulation are provided to show the properties of the proposed family of algorithms. (C) 2000 Elsevier Science B.V. All rights reserved.

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Continuing achievements in hardware technology are bringing ubiquitous computing closer to reality. The notion of a connected, interactive and autonomous environment is common to all sensor networks, biosystems and radio frequency identification (RFID) devices, and the emergence of significant deployments and sophisticated applications can be expected. However, as more information is collected and transmitted, security issues will become vital for such a fully connected environment. In this study the authors consider adding security features to low-cost devices such as RFID tags. In particular, the authors consider the implementation of a digital signature architecture that can be used for device authentication, to prevent tag cloning, and for data authentication to prevent transmission forgery. The scheme is built around the signature variant of the cryptoGPS identification scheme and the SHA-1 hash function. When implemented on 130 nm CMOS the full design uses 7494 gates and consumes 4.72 mu W of power, making it smaller and more power efficient than previous low-cost digital signature designs. The study also presents a low-cost SHA-1 hardware architecture which is the smallest standardised hash function design to date.

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Cooperative MIMO (Multiple Input–Multiple Output) allows multiple nodes share their antennas to emulate antenna arrays and transmit or receive cooperatively. It has the ability to increase the capacity for future wireless communication systems and it is particularly suited for ad hoc networks. In this study, based on the transmission procedure of a typical cooperative MIMO system, we first analyze the capacity of single-hop cooperative MIMO systems, and then we derive the optimal resource allocation strategy to maximize the end-to-end capacity in multi-hop cooperative MIMO systems. The study shows three implications. First, only when the intra-cluster channel is better than the inter-cluster channel, cooperative MIMO results in a capacity increment. Second, for a given scenario there is an optimal number of cooperative nodes. For instance, in our study an optimal deployment of three cooperative nodes achieve a capacity increment of 2 bps/Hz when compared with direct transmission. Third, an optimal resource allocation strategy plays a significant role in maximizing end-to-end capacity in multi-hop cooperative MIMO systems. Numerical results show that when optimal resource allocation is applied we achieve more than 20% end-to-end capacity increment in average when compared with an equal resource allocation strategy.

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Background: Increasing emphasis is being placed on the economics of health care service delivery - including home-based palliative care. Aim: This paper analyzes resource utilization and costs of a shared-care demonstration project in rural Ontario (Canada) from the public health care system's perspective. Design: To provide enhanced end-of-life care, the shared-care approach ensured exchange of expertise and knowledge and coordination of services in line with the understood goals of care. Resource utilization and costs were tracked over the 15 month study period from January 2005 to March 2006. Results: Of the 95 study participants (average age 71 years), 83 had a cancer diagnosis (87%); the non-cancer diagnoses (12 patients, 13%) included mainly advanced heart diseases and COPD. Community Care Access Centre and Enhanced Palliative Care Team-based homemaking and specialized nursing services were the most frequented offerings, followed by equipment/transportation services and palliative care consults for pain and symptom management. Total costs for all patient-related services (in 2007 CAN) were 1,625,658.07 - or 17,112.19 per patient/117.95 per patient day. Conclusion: While higher than expenditures previously reported for a cancer-only population in an urban Ontario setting, the costs were still within the parameters of the US Medicare Hospice Benefits, on a par with the per diem funding assigned for long-term care homes and lower than both average alternate level of care and hospital costs within the Province of Ontario. The study results may assist service planners in the appropriate allocation of resources and service packaging to meet the complex needs of palliative care populations. © 2012 The Author(s).

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This article introduces a resource allocation solution capable of handling mixed media applications within the constraints of a 60 GHz wireless network. The challenges of multimedia wireless transmission include high bandwidth requirements, delay intolerance and wireless channel availability. A new Channel Time Allocation Particle Swarm Optimization (CTA-PSO) is proposed to solve the network utility maximization (NUM) resource allocation problem. CTA-PSO optimizes the time allocated to each device in the network in order to maximize the Quality of Service (QoS) experienced by each user. CTA-PSO introduces network-linked swarm size, an increased diversity function and a learning method based on the personal best, Pbest, results of the swarm. These additional developments to the PSO produce improved convergence speed with respect to Adaptive PSO while maintaining the QoS improvement of the NUM. Specifically, CTA-PSO supports applications described by both convex and non-convex utility functions. The multimedia resource allocation solution presented in this article provides a practical solution for real-time wireless networks.

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Abstract—Power capping is an essential function for efficient power budgeting and cost management on modern server systems. Contemporary server processors operate under power caps by using dynamic voltage and frequency scaling (DVFS). However, these processors are often deployed in non-uniform memory
access (NUMA) architectures, where thread allocation between cores may significantly affect performance and power consumption. This paper proposes a method which maximizes performance under power caps on NUMA systems by dynamically optimizing two knobs: DVFS and thread allocation. The method selects the optimal combination of the two knobs with models based on artificial neural network (ANN) that captures the nonlinear effect of thread allocation on performance. We implement
the proposed method as a runtime system and evaluate it with twelve multithreaded benchmarks on a real AMD Opteron based NUMA system. The evaluation results show that our method outperforms a naive technique optimizing only DVFS by up to
67.1%, under a power cap.