838 resultados para network congestion control
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This paper proposes a new distributed coordination approach to make load leveling, using Energy Storage Units (ESUs) in LV network. The proposed distributed control strategy is based on consensus algorithm which shares the required active power equally among the ESUs with respect to their rating. To show the effectiveness of the proposed approach, a typical radial LV network is simulated as a case study.
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Voltage rise and drop are the main power quality challenges in Low Voltage (LV) network with Renewable Energy (RE) generators. This paper proposes a new voltage support strategy based on coordination of multiple Distribution Static Synchronous Compensators (DSTATCOMs) using consensus algorithm. The study focuses on LV network with PV as the RE source for customers. The proposed approach applied to a typical residential LV network and its advantages are shown comparing with other voltage control strategies.
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A novel intelligent online demand side management system is proposed for peak load management. The method also regulates the network voltage, balances the power in three phases and coordinates the battery storage discharge within the network. This method uses low cost controllers with low bandwidth two-way communication installed in costumers' premises and at distribution transformers to manage the peak load while maximizing customer satisfaction. A multi-objective decision making process is proposed to select the load(s) to be delayed or controlled. The efficacy of the proposed control system is verified through an event-based developed simulation in Matlab.
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To minimise the number of load sheddings in a microgrid (MG) during autonomous operation, islanded neighbour MGs can be interconnected if they are on a self-healing network and an extra generation capacity is available in the distributed energy resources (DER) of one of the MGs. In this way, the total load in the system of interconnected MGs can be shared by all the DERs within those MGs. However, for this purpose, carefully designed self-healing and supply restoration control algorithm, protection systems and communication infrastructure are required at the network and MG levels. In this study, first, a hierarchical control structure is discussed for interconnecting the neighbour autonomous MGs where the introduced primary control level is the main focus of this study. Through the developed primary control level, this study demonstrates how the parallel DERs in the system of multiple interconnected autonomous MGs can properly share the load of the system. This controller is designed such that the converter-interfaced DERs operate in a voltage-controlled mode following a decentralised power sharing algorithm based on droop control. DER converters are controlled based on a per-phase technique instead of a conventional direct-quadratic transformation technique. In addition, linear quadratic regulator-based state feedback controllers, which are more stable than conventional proportional integrator controllers, are utilised to prevent instability and weak dynamic performances of the DERs when autonomous MGs are interconnected. The efficacy of the primary control level of the DERs in the system of multiple interconnected autonomous MGs is validated through the PSCAD/EMTDC simulations considering detailed dynamic models of DERs and converters.
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This special issue of Networking Science focuses on Next Generation Network (NGN) that enables the deployment of access independent services over converged fixed and mobile networks. NGN is a packet-based network and uses the Internet protocol (IP) to transport the various types of traffic (voice, video, data and signalling). NGN facilitates easy adoption of distributed computing applications by providing high speed connectivity in a converged networked environment. It also makes end user devices and applications highly intelligent and efficient by empowering them with programmability and remote configuration options. However, there are a number of important challenges in provisioning next generation network technologies in a converged communication environment. Some preliminary challenges include those that relate to QoS, switching and routing, management and control, and security which must be addressed on an urgent or emergency basis. The consideration of architectural issues in the design and pro- vision of secure services for NGN deserves special attention and hence is the main theme of this special issue.
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Ramp signalling is an access control for motorways, in which a traffic signal is placed at on-ramps to regulate the rate of vehicles entering the motorway and thus to preserve the motorway capacity. In general, ramp signalling algorithms fall into two categories: local control and coordinated control by their effective scope. Coordinated ramp signalling strategies make use of measurements from the entire motorway network to operate individual ramp signals for the optimal performances at the network level. This study proposes a multi-hierarchical strategy for coordinated ramp signalling. The strategy is structured in two layers. At the higher layer with a longer update interval, coordination group is assembled and disassembled based on the location of high-risk breakdown flow. At the lower layer with a shorter update interval, individual ramps are hired to serve the coordination and are also released based on the prevailing congestion level on the ramp. This strategy is modelled and applied to the northbound Pacific Motorway micro-simulation platform (AIMSUN). The simulation results show an effective congestion mitigation of the proposed strategy.
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The Macroscopic Fundamental Diagram (MFD) relates space-mean density and flow, and the existence with dynamic features was confirmed in congested urban network in downtown Yokohama with real data set. Since the MFD represents the area-wide network traffic performances, studies on perimeter control strategies and an area traffic state estimation utilizing the MFD concept has been reported. However, limited works have been reported on real world example from signalised arterial network. This paper fuses data from multiple sources (Bluetooth, Loops and Signals) and presents a framework for the development of the MFD for Brisbane, Australia. Existence of the MFD in Brisbane arterial network is confirmed. Different MFDs (from whole network and several sub regions) are evaluated to discover the spatial partitioning for network performance representation. The findings confirmed the usefulness of appropriate network partitioning for traffic monitoring and incident detections. The discussion addressed future research directions.
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Numerous initiatives have been employed around the world in order to address rising greenhouse gas (GHG) emissions originating from the transport sector. These measures include: travel demand management (congestion‐charging), increased fuel taxes, alternative fuel subsidies and low‐emission vehicle (LEV) rebates. Incentivizing the purchase of LEVs has been one of the more prevalent approaches in attempting to tackle this global issue. LEVs, whilst having the advantage of lower emissions and, in some cases, more efficient fuel consumption, also bring the downsides of increased purchase cost, reduced convenience of vehicle fuelling, and operational uncertainty. To stimulate demand in the face of these challenges, various incentive‐based policies, such as toll exemptions, have been used by national and local governments to encourage the purchase of these types of vehicles. In order to address rising GHG emissions in Stockholm, and in line with the Swedish Government’s ambition to operate a fossil free fleet by 2030, a number of policies were implemented targeting the transport sector. Foremost amongst these was the combination of a congestion charge – initiated to discourage emissions‐intensive travel – and an exemption from this charge for some LEVs, established to encourage a transition towards a ‘green’ vehicle fleet. Although both policies shared the aim of reducing GHG emissions, the exemption for LEVs carried the risk of diminishing the effectiveness of the congestion charging scheme. As the number of vehicle owners choosing to transition to an eligible LEV increased, the congestion‐reduction effectiveness of the charging scheme weakened. In fact, policy makers quickly recognized this potential issue and consequently phased out the LEV exemption less than 18 months after its introduction (1). Several studies have investigated the demand for LEVs through stated‐preference (SP) surveys across multiple countries, including: Denmark (2), Germany (3, 4), UK (5), Canada (6), USA (7, 8) and Australia (9). Although each of these studies differed in approach, all involved SP surveys where differing characteristics between various types of vehicles, including LEVs, were presented to respondents and these respondents in turn made hypothetical decisions about which vehicle they would be most likely to purchase. Although these studies revealed a number of interesting findings in regards to the potential demand for LEVs, they relied on SP data. In contrast, this paper employs an approach where LEV choice is modelled by taking a retrospective view and by using revealed preference (RP) data. By examining the revealed preferences of vehicle owners in Stockholm, this study overcomes one of the principal limitations of SP data, namely that stated preferences may not in fact reflect individuals’ actual choices, such as when cost, time, and inconvenience factors are real rather than hypothetical. This paper’s RP approach involves modelling the characteristics of individuals who purchased new LEVs, whilst estimating the effect of the congestion charging exemption upon choice probabilities and subsequent aggregate demand. The paper contributes to the current literature by examining the effectiveness of a toll exemption under revealed preference conditions, and by assessing the total effect of the policy based on key indicators for policy makers, including: vehicle owner home location, commuting patterns, number of children, age, gender and income. Extended Abstract Submission for Kuhmo Nectar Conference 2014 2 The two main research questions motivating this study were: Which individuals chose to purchase a new LEV in Stockholm in 2008?; and, How did the congestion charging exemption affect the aggregate demand for new LEVs in Stockholm in 2008? In order to answer these research questions the analysis was split into two stages. Firstly, a multinomial logit (MNL) model was used to identify which demographic characteristics were most significantly related to the purchase of an LEV over a conventional vehicle. The three most significant variables were found to be: intra‐cordon residency (positive); commuting across the cordon (positive); and distance of residence from the cordon (negative). In order to estimate the effect of the exemption policy on vehicle purchase choice, the model included variables to control for geographic differences in preferences, based on the location of the vehicle owners’ homes and workplaces in relation to the congestion‐charging cordon boundary. These variables included one indicator representing commutes across the cordon and another indicator representing intra‐cordon residency. The effect of the exemption policy on the probability of purchasing LEVs was estimated in the second stage of the analysis by focusing on the groups of vehicle owners that were most likely to have been affected by the policy i.e. those commuting across the cordon boundary (in both directions). Given the inclusion of the indicator variable representing commutes across the cordon, it is assumed that the estimated coefficient of this variable captures the effect of the exemption policy on the utility of choosing to purchase an exempt LEV for these two groups of vehicle owners. The intra‐cordon residency indicator variable also controls for differences between the two groups, based upon direction of travel across the cordon boundary. A counter‐hypothesis to this assumption is that the coefficient of the variable representing commuting across the cordon boundary instead only captures geo‐demographic differences that lead to variations in LEV ownership across the different groups of vehicle owners in relation to the cordon boundary. In order to address this counter‐hypothesis, an additional analysis was performed on data from a city with a similar geodemographic pattern to Stockholm, Gothenburg ‐ Sweden’s second largest city. The results of this analysis provided evidence to support the argument that the coefficient of the variable representing commutes across the cordon was capturing the effect of the exemption policy. Based upon this framework, the predicted vehicle type shares were calculated using the estimated coefficients of the MNL model and compared with predicted vehicle type shares from a simulated scenario where the exemption policy was inactive. This simulated scenario was constructed by setting the coefficient for the variable representing commutes across the cordon boundary to zero for all observations to remove the utility benefit of the exemption policy. Overall, the procedure of this second stage of the analysis led to results showing that the exemption had a substantial effect upon the probability of purchasing and aggregate demand for exempt LEVs in Stockholm during 2008. By making use of unique evidence of revealed preferences of LEV owners, this study identifies the common characteristics of new LEV owners and estimates the effect of Stockholm's congestion charging exemption upon the demand for new LEVs during 2008. It was found that the variables that had the greatest effect upon the choice of purchasing an exempt LEV included intra‐cordon residency (positive), distance of home from the cordon (negative), and commuting across the cordon (positive). It was also determined that owners under the age of 30 years preferred non‐exempt LEVs (low CO2 LEVs), whilst those over the age of 30 years preferred electric vehicles. In terms of electric vehicles, it was apparent that those individuals living within the city had the highest propensity towards purchasing this vehicle type. A negative relationship between choosing an electric vehicle and the distance of an individuals’ residency from the cordon was also evident. Overall, the congestion charging exemption was found to have increased the share of exempt LEVs in Stockholm by 1.9%, with, as expected, a much stronger effect on those commuting across the boundary, with those living inside the cordon having a 13.1% increase, and those owners living outside the cordon having a 5.0% increase. This increase in demand corresponded to an additional 538 (+/‐ 93; 95% C.I.) new exempt LEVs purchased in Stockholm during 2008 (out of a total of 5 427; 9.9%). Policy makers can take note that an incentive‐based policy can increase the demand for LEVs and appears to be an appropriate approach to adopt when attempting to reduce transport emissions through encouraging a transition towards a ‘green’ vehicle fleet.
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Since the revisions to the International Health Regulations (IHR) in 2005, much attention has been turned to how states, particularly developing states, will address core capacity requirements. The question often examined is how states with poor health systems can strengthen their capacity to identify and verify public health emergencies of international concern. A core capacity requirement is that by 2012 states will have a surveillance and response network that operates from the local community to the national level. Much emphasis has turned to the health system capacity required for this task. In this article, I seek to understand the political capacity to perform this task. This article considers how the world's two most populous states,1 1. For the purposes of this paper, I use the word ‘state’ as a shorthand for the nation-state of China and India, or member state as used by the United Nations. View all notes China and India, have sought to communicate outbreak events in times of crisis and calm. I consider what this reporting performance tells us of their capacity to meet their IHR obligations given the two countries differing political institutions.
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Realizing the promise of molecularly targeted inhibitors for cancer therapy will require a new level of knowledge about how a drug target is wired into the control circuitry of a complex cellular network. Here we review general homeostatic principles of cellular networks that enable the cell to be resilient in the face of molecular perturbations, while at the same time being sensitive to subtle input signals. Insights into such mechanisms may facilitate the development of combination therapies that take advantage of the cellular control circuitry, with the aim of achieving higher efficacy at a lower drug dosage and with a reduced probability of drug-resistance development.
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Cancer is a disease of signal transduction in which the dysregulation of the network of intracellular and extracellular signaling cascades is sufficient to thwart the cells finely-tuned biochemical control mechanisms. A keen interest in the mathematical modeling of cell signaling networks and the regulation of signal transduction has emerged in recent years, and has produced a glimmer of insight into the sophisticated feedback control and network regulation operating within cells. In this review, we present an overview of published theoretical studies on the control aspects of signal transduction, emphasizing the role and importance of mechanisms such as ‘ultrasensitivity’ and feedback loops. We emphasize that these exquisite and often subtle control strategies represent the key to orchestrating ‘simple’ signaling behaviors within the complex intracellular network, while regulating the trade-off between sensitivity and robustness to internal and external perturbations. Through a consideration of these apparent paradoxes, we explore how the basic homeostasis of the intracellular signaling network, in the face of carcinogenesis, can lead to neoplastic progression rather than cell death. A simple mathematical model is presented, furnishing a vivid illustration of how ‘control-oriented’ models of the deranged signaling networks in cancer cells may enucleate improved treatment strategies, including patient-tailored combination therapies, with the potential for reduced toxicity and more robust and potent antitumor activity.
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The fields of molecular biology and cell biology are being flooded with complex genomic and proteomic datasets of large dimensions. We now recognize that each molecule in the cell and tissue can no longer be viewed as an isolated entity. Instead, each molecule must be considered as one member of an interacting network. Consequently, there is an urgent need for mathematical models to understand the behavior of cell signaling networks in health and in disease.
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Recurrent congestion caused by high commuter traffic is an irritation to motorway users. Ramp metering (RM) is the most effective motorway control means (M Papageorgiou & Kotsialos, 2002) for significantly reducing motorway congestion. However, given field constraints (e.g. limited ramp space and maximum ramp waiting time), RM cannot eliminate recurrent congestion during the increased long peak hours. This paper, therefore, focuses on rapid congestion recovery to further improve RM systems: that is, to quickly clear congestion in recovery periods. The feasibility of using RM for recovery is analyzed, and a zone recovery strategy (ZRS) for RM is proposed. Note that this study assumes no incident and demand management involved, i.e. no re-routing behavior and strategy considered. This strategy is modeled, calibrated and tested in the northbound model of the Pacific Motorway, Brisbane, Australia in a micro-simulation environment for recurrent congestion scenario, and evaluation results have justified its effectiveness.
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Large arrays and networks of carbon nanotubes, both single- and multi-walled, feature many superior properties which offer excellent opportunities for various modern applications ranging from nanoelectronics, supercapacitors, photovoltaic cells, energy storage and conversation devices, to gas- and biosensors, nanomechanical and biomedical devices etc. At present, arrays and networks of carbon nanotubes are mainly fabricated from the pre-fabricated separated nanotubes by solution-based techniques. However, the intrinsic structure of the nanotubes (mainly, the level of the structural defects) which are required for the best performance in the nanotube-based applications, are often damaged during the array/network fabrication by surfactants, chemicals, and sonication involved in the process. As a result, the performance of the functional devices may be significantly degraded. In contrast, directly synthesized nanotube arrays/networks can preclude the adverse effects of the solution-based process and largely preserve the excellent properties of the pristine nanotubes. Owing to its advantages of scale-up production and precise positioning of the grown nanotubes, catalytic and catalyst-free chemical vapor depositions (CVD), as well as plasma-enhanced chemical vapor deposition (PECVD) are the methods most promising for the direct synthesis of the nanotubes.
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Effective control of morphology and electrical connectivity of networks of single-walled carbon nanotubes (SWCNTs) by using rough, nanoporous silica supports of Fe catalyst nanoparticles in catalytic chemical vapor deposition is demonstrated experimentally. The very high quality of the nanotubes is evidenced by the G-to-D Raman peak ratios (>50) within the range of the highest known ratios. Transitions from separated nanotubes on smooth SiO2 surface to densely interconnected networks on the nanoporous SiO2 are accompanied by an almost two-order of magnitude increase of the nanotube density. These transitions herald the hardly detectable onset of the nanoscale connectivity and are confirmed by the microanalysis and electrical measurements. The achieved effective nanotube interconnection leads to the dramatic, almost three-orders of magnitude decrease of the SWCNT network resistivity compared to networks of similar density produced by wet chemistry-based assembly of preformed nanotubes. The growth model, supported by multiscale, multiphase modeling of SWCNT nucleation reveals multiple constructive roles of the porous catalyst support in facilitating the catalyst saturation and SWCNT nucleation, consistent with the observed higher density of longer nanotubes. The associated mechanisms are related to the unique surface conditions (roughness, wettability, and reduced catalyst coalescence) on the porous SiO2 and the increased carbon supply through the supporting porous structure. This approach is promising for the direct integration of SWCNT networks into Si-based nanodevice platforms and multiple applications ranging from nanoelectronics and energy conversion to bio- and environmental sensing.