29 resultados para Distribution Networks

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


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Heat pumps can provide domestic heating at a cost that is competitive with oil heating in particular. If the electricity supply contains a significant amount of renewable generation, a move from fossil fuel heating to heat pumps can reduce greenhouse gas emissions. The inherent thermal storage of heat pump installations can also provide the electricity supplier with valuable flexibility. The increase in heat pump installations in the UK and Europe in the last few years poses a challenge for low-voltage networks, due to the use of induction motors to drive the pump compressors. The induction motor load tends to depress voltage, especially on starting. The paper includes experimental results, dynamic load modelling, comparison of experimental results and simulation results for various levels of heat pump deployment. The simulations are based on a generic test network designed to capture the main characteristics of UK distribution system practice. The simulations employ DIgSlILENT to facilitate dynamic simulations that focus on starting current, voltage variations, active power, reactive power and switching transients.

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As one of the most successfully commercialized distributed energy resources, the long-term effects of microturbines (MTs) on the distribution network has not been fully investigated due to the complex thermo-fluid-mechanical energy conversion processes. This is further complicated by the fact that the parameter and internal data of MTs are not always available to the electric utility, due to different ownerships and confidentiality concerns. To address this issue, a general modeling approach for MTs is proposed in this paper, which allows for the long-term simulation of the distribution network with multiple MTs. First, the feasibility of deriving a simplified MT model for long-term dynamic analysis of the distribution network is discussed, based on the physical understanding of dynamic processes that occurred within MTs. Then a three-stage identification method is developed in order to obtain a piecewise MT model and predict electro-mechanical system behaviors with saturation. Next, assisted with the electric power flow calculation tool, a fast simulation methodology is proposed to evaluate the long-term impact of multiple MTs on the distribution network. Finally, the model is verified by using Capstone C30 microturbine experiments, and further applied to the dynamic simulation of a modified IEEE 37-node test feeder with promising results.

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This paper develops an integrated optimal power flow (OPF) tool for distribution networks in two spatial scales. In the local scale, the distribution network, the natural gas network, and the heat system are coordinated as a microgrid. In the urban scale, the impact of natural gas network is considered as constraints for the distribution network operation. The proposed approach incorporates unbalance three-phase electrical systems, natural gas systems, and combined cooling, heating, and power systems. The interactions among the above three energy systems are described by energy hub model combined with components capacity constraints. In order to efficiently accommodate the nonlinear constraint optimization problem, particle swarm optimization algorithm is employed to set the control variables in the OPF problem. Numerical studies indicate that by using the OPF method, the distribution network can be economically operated. Also, the tie-line power can be effectively managed.

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In this paper we consider charging strategies that mitigate the impact of domestic charging of EVs on low-voltage distribution networks and which seek to reduce peak power by responding to time-ofday pricing. The strategies are based on the distributed Additive Increase and Multiplicative Decrease (AIMD) charging algorithms proposed in [5]. The strategies are evaluated using simulations conducted on a custom OpenDSS-Matlab platform for a typical low voltage residential feeder network. Results show that by using AIMD based smart charging 50% EV penetration can be accommodated on our test network, compared to only 10% with uncontrolled charging, without needing to reinforce existing network infrastructure. © Springer-Verlag Berlin Heidelberg 2013.

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Future power systems are expected to integrate large-scale stochastic and intermittent generation and load due to reduced use of fossil fuel resources, including renewable energy sources (RES) and electric vehicles (EV). Inclusion of such resources poses challenges for the dynamic stability of synchronous transmission and distribution networks, not least in terms of generation where system inertia may not be wholly governed by large-scale generation but displaced by small-scale and localised generation. Energy storage systems (ESS) can limit the impact of dispersed and distributed generation by offering supporting reserve while accommodating large-scale EV connection; the latter (load) also participating in storage provision. In this paper, a local energy storage system (LESS) is proposed. The structure, requirement and optimal sizing of the LESS are discussed. Three operating modes are detailed, including: 1) storage pack management; 2) normal operation; and 3) contingency operation. The proposed LESS scheme is evaluated using simulation studies based on data obtained from the Northern Ireland regional and residential network.

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Synchronous islanded operation involves continuously holding an islanded power network in virtual synchronism with the main power system to aid paralleling and avoid potentially damaging out-of-synchronism reclosure. This requires phase control of the generators in the island and the transmission of a reference signal from a secure location on the main power system. Global positioning system (GPS) time-synchronized phasor measurements transmitted via an Internet protocol (IP) are used for the reference signal. However, while offering low cost and a readily available solution for distribution networks, IP communications have variable latency and are susceptible to packet loss, which can make time-critical control applications difficult. This paper investigates the ability of the phase-control system to tolerate communications latency. Phasor measurement conditioning algorithms that can tolerate latency are used in the phase-control loop of a 50-kVA diesel generator. © 2010 IEEE.

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Raman spectroscopy with far-red excitation has been investigated as a simple and rapid technique for composition profiling of seized ecstasy (MDMA, N-methyl-3,4-methylenedioxyamphetamine) tablets. The spectra obtained are rich in vibrational bands and allow the active drug and excipient used to bulk the tablets to be identified. Relative band heights can be used to determine drug/excipient ratios and the degree of hydration of the drug while the fact that 50 tablets per hour can be analysed allows large numbers of spectra to be recorded. The ability of Raman spectroscopy to distinguish between ecstasy tablets on the basis of their chemical composition is illustrated here by a sample set of 400 tablets taken from a large seizure of > 50000 tablets that were found in eight large bags. The tablets are all similar in appearance and carry the same logo. Conventional analysis by GC-MS showed they contained MDMA. Initial Raman studies of samples from each of the eight bags showed that despite some tablet-to-tablet variation within each bag the contents could be classified on the basis of the excipients used. The tablets in five of the bags were sorbitol-based, two were cellulose-based and one bag contained tablets with a glucose excipient. More extensive analysis of 50 tablets from each of a representative series of sample bags gave distribution profiles that showed the contents of each bag were approximately normally distributed about a mean value, rather than being mixtures of several discrete types. Two of the sorbitol-containing sample sets were indistinguishable while a third was similar but not identical to these, in that it contained the same excipient and MDMA with the same degree of hydration but had a slightly different MDMA/sorbitol ratio. The cellulose-based samples were badly manufactured and showed considerable tablet-to-tablet variation in their drug/excipient ratio while the glucose-based tablets had a tight distribution in their drug/excipient ratios. The degree of hydration in the MDMA feedstocks used to manufacture the cellulose-, glucose- and sorbitol-based tablets were all different from each other. This study, because it centres on a single seizure of physically similar tablets with the same active drug, highlights the fact that simple physical descriptions coupled with active drug content do not in themselves fully characterize the nature of the seized materials. There is considerable variation in the composition of the tablets within this single seizure and the fact that this variation can be detected from Raman spectra demonstrates that the potential benefits of obtaining highly detailed spectra can indeed translate into information that is not readily available from other methods but would be useful for tracing of drug distribution networks.

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The development of appropriate Electric Vehicle (EV) charging strategies has been identified as an effective way to accommodate an increasing number of EVs on Low Voltage (LV) distribution networks. Most research studies to date assume that future charging facilities will be capable of regulating charge rates continuously, while very few papers consider the more realistic situation of EV chargers that support only on-off charging functionality. In this work, a distributed charging algorithm applicable to on-off based charging systems is presented. Then, a modified version of the algorithm is proposed to incorporate real power system constraints. Both algorithms are compared with uncontrolled and centralized charging strategies from the perspective of both utilities and customers. © 2013 IEEE.

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Moving from combustion engine to electric vehicle (EV)-based transport is recognized as having a major role to play in reducing pollution, combating climate change and improving energy security. However, the introduction of EVs poses major challenges for power system operation. With increasing penetration of EVs, uncontrolled coincident charging may overload the grid and substantially increase peak power requirements. Developing smart grid technologies and appropriate charging strategies to support the role out of EVs is therefore a high priority. In this paper, we investigate the effectiveness of distributed additive increase and multiplicative decrease (AIMD) charging algorithms, as proposed by Stu¨dli et al. in 2012, at mitigating the impact of domestic charging of EVs on low-voltage distribution networks. In particular, a number of enhancements to the basic AIMD implementation are introduced to enable local power system infrastructure and voltage level constraints to be taken into account and to reduce peak power requirements. The enhanced AIMD EV charging strategies are evaluated using power system simulations for a typical low-voltage residential feeder network in Ireland. Results show that by using the proposed AIMD-based smart charging algorithms, 50% EV penetration can be accommodated, compared with only 10% with uncontrolled charging, without exceeding network infrastructure constraints.

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Cyber-physical systems tightly integrate physical processes and information and communication technologies. As today’s critical infrastructures, e.g., the power grid or water distribution networks, are complex cyber-physical systems, ensuring their safety and security becomes of paramount importance. Traditional safety analysis methods, such as HAZOP, are ill-suited to assess these systems. Furthermore, cybersecurity vulnerabilities are often not considered critical, because their effects on the physical processes are not fully understood. In this work, we present STPA-SafeSec, a novel analysis methodology for both safety and security. Its results show the dependencies between cybersecurity vulnerabilities and system safety. Using this information, the most effective mitigation strategies to ensure safety and security of the system can be readily identified. We apply STPA-SafeSec to a use case in the power grid domain, and highlight its benefits.

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In this letter, we investigate the distribution of the phase component of the complex received signal observed in practical experiments using body area networks. Two phase distributions, the recently proposed kappa-mu and eta-mu probability densities, which together encompass the most widely used fading models, namely Semi-Gaussian, Rayleigh, Hoyt, Rice, and Nakagami-m, have been compared with measurement data. The kappa-mu distribution has been found to provide the best fit over a range of on-body links, while the user was mobile. The experiments were carried out in two dissimilar indoor environments at opposite ends of the multipath spectrum. It has also been found that the uniform phase distribution has not arisen in anyone of the experiments.

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Smart Grids are characterized by the application of information communication technology (ICT) to solve electrical energy challenges. Electric power networks span large geographical areas, thus a necessary component of many Smart Grid applications is a wide area network (WAN). For the Smart Grid to be successful, utilities must be confident that the communications infrastructure is secure. This paper describes how a WAN can be deployed using WiMAX radio technology to provide high bandwidth communications to areas not commonly served by utility communications, such as generators embedded in the distribution network. A planning exercise is described, using Northern Ireland as a case study. The suitability of the technology for real-time applications is assessed using experimentally obtained latency data.

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Traditionally, the Internet provides only a “best-effort” service, treating all packets going to the same destination equally. However, providing differentiated services for different users based on their quality requirements is increasingly becoming a demanding issue. For this, routers need to have the capability to distinguish and isolate traffic belonging to different flows. This ability to determine the flow each packet belongs to is called packet classification. Technology vendors are reluctant to support algorithmic solutions for classification due to their non-deterministic performance. Although CAMs are favoured by technology vendors due to their deterministic high lookup rates, they suffer from the problems of high power dissipation and high silicon cost. This paper provides a new algorithmic-architectural solution for packet classification that mixes CAMs with algorithms based on multi-level cutting the classification space into smaller spaces. The provided solution utilizes the geometrical distribution of rules in the classification space. It provides the deterministic performance of CAMs, support for dynamic updates, and added flexibility for system designers.