8 resultados para DC voltage droop control

em CentAUR: Central Archive University of Reading - UK


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This work proposes a method to objectively determine the most suitable analogue redesign method for forward type converters under digital voltage mode control. Particular emphasis is placed on determining the method which allows the highest phase margin at the particular switching and crossover frequencies chosen by the designer. It is shown that at high crossover frequencies with respect to switching frequency, controllers designed using backward integration have the largest phase margin; whereas at low crossover frequencies with respect to switching frequency, controllers designed using bilinear integration have the largest phase margins. An accurate model of the power stage is used for simulation, and experimental results from a Buck converter are collected. The performance of the digital controllers is compared to that of the equivalent analogue controller both in simulation and experiment. Excellent correlation between the simulation and experimental results is presented. This work will allow designers to confidently choose the analogue redesign method which yields the greater phase margin for their application.

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This article proposes a systematic approach to determine the most suitable analogue redesign method to be used for forward-type converters under digital voltage mode control. The focus of the method is to achieve the highest phase margin at the particular switching and crossover frequencies chosen by the designer. It is shown that at high crossover frequencies with respect to switching frequency, controllers designed using backward integration have the largest phase margin; whereas at low crossover frequencies with respect to switching frequency, controllers designed using bilinear integration with pre-warping have the largest phase margins. An algorithm has been developed to determine the frequency of the crossing point where the recommended discretisation method changes. An accurate model of the power stage is used for simulation and experimental results from a Buck converter are collected. The performance of the digital controllers is compared to that of the equivalent analogue controller both in simulation and experiment. Excellent closeness between the simulation and experimental results is presented. This work provides a concrete example to allow academics and engineers to systematically choose a discretisation method.

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The Distribution Network Operators (DNOs) role is becoming more difficult as electric vehicles and electric heating penetrate the network, increasing the demand. As a result it becomes harder for the distribution networks infrastructure to remain within its operating constraints. Energy storage is a potential alternative to conventional network reinforcement such as upgrading cables and transformers. The research presented here in this paper shows that due to the volatile nature of the LV network, the control approach used for energy storage has a significant impact on performance. This paper presents and compares control methodologies for energy storage where the objective is to get the greatest possible peak demand reduction across the day from a pre-specified storage device. The results presented show the benefits and detriments of specific types of control on a storage device connected to a single phase of an LV network, using aggregated demand profiles based on real smart meter data from individual homes. The research demonstrates an important relationship between how predictable an aggregation is and the best control methodology required to achieve the objective.

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-Aminobutyric acid type A (GABAA) receptors, a family of Cl-permeable ion channels, mediate fast synaptic inhibition as postsynaptically enriched receptors for -aminobutyric acid at GABAergic synapses. Here we describe an alternative type of inhibition mediated byGABAA receptors present on neocortical glutamatergic nerve terminals and examine the underlying signaling mechanism(s). By monitoring the activity of the presynaptic CaM kinase II/synapsin I signaling pathway in isolated nerve terminals, we demonstrate that GABAA receptor activation correlated with an increase in basal intraterminal [Ca2]i. Interestingly, this activation of GABAA receptors resulted in a reduction of subsequent depolarization-evoked Ca2 influx, which thereby led to an inhibition of glutamate release. To investigate how the observed GABAA receptor-mediated modulation operates, we determined the sensitivity of this process to the Na-K-2Cl cotransporter 1 antagonist bumetanide, as well as substitution of Ca2 with Ba2, or Ca2/calmodulin inhibition by W7. All of these treatments abolished the modulation by GABAA receptors. Application of selective antagonists of voltage-gated Ca2 channels (VGCCs) revealed that the GABAA receptor-mediated modulation of glutamate release required the specific activity of L- and R-type VGCCs. Crucially, the inhibition of release by these receptors was abolished in terminals isolated from R-type VGCC knock-out mice. Together, our results indicate that a functional coupling between nerve terminal GABAA receptors and L- or R-type VGCCs is mediated by Ca2/calmodulin-dependent signaling. This mechanism provides a GABA-mediated control of glutamatergic synaptic activity by a direct inhibition of glutamate release.

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Control by voltage drop DC. Contrôle par chute de potentiel de courant alternatif. Control by voltage drop AC.

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Smooth trajectories are essential for safe interaction in between human and a haptic interface. Different methods and strategies have been introduced to create such smooth trajectories. This paper studies the creation of human-like movements in haptic interfaces, based on the study of human arm motion. These motions are intended to retrain the upper limb movements of patients that lose manipulation functions following stroke. We present a model that uses higher degree polynomials to define a trajectory and control the robot arm to achieve minimum jerk movements. It also studies different methods that can be driven from polynomials to create more realistic human-like movements for therapeutic purposes.

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Reinforcing the Low Voltage (LV) distribution network will become essential to ensure it remains within its operating constraints as demand on the network increases. The deployment of energy storage in the distribution network provides an alternative to conventional reinforcement. This paper presents a control methodology for energy storage to reduce peak demand in a distribution network based on day-ahead demand forecasts and historical demand data. The control methodology pre-processes the forecast data prior to a planning phase to build in resilience to the inevitable errors between the forecasted and actual demand. The algorithm uses no real time adjustment so has an economical advantage over traditional storage control algorithms. Results show that peak demand on a single phase of a feeder can be reduced even when there are differences between the forecasted and the actual demand. In particular, results are presented that demonstrate when the algorithm is applied to a large number of single phase demand aggregations that it is possible to identify which of these aggregations are the most suitable candidates for the control methodology.