936 resultados para Active distribution networks


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The work presented here has focused on the role of cation-chloride cotransporters (CCCs) in (1) the regulation of intracellular chloride concentration within postsynaptic neurons and (2) on the consequent effects on the actions of the neurotransmitter gamma-aminobutyric acid (GABA) mediated by GABAA receptors (GABAARs) during development and in pathophysiological conditions such as epilepsy. In addition, (3) we found that a member of the CCC family, the K-Cl cotransporter isoform 2 (KCC2), has a structural role in the development of dendritic spines during the differentiation of pyramidal neurons. Despite the large number of publications dedicated to regulation of intracellular Cl-, our understanding of the underlying mechanisms is not complete. Experiments on GABA actions under resting steady-state have shown that the effect of GABA shifts from depolarizing to hyperpolarizing during maturation of cortical neurons. However, it remains unclear, whether conclusions from these steady-state measurements can be extrapolated to the highly dynamic situation within an intact and active neuronal network. Indeed, GABAergic signaling in active neuronal networks results in a continuous Cl- load, which must be constantly removed by efficient Cl- extrusion mechanisms. Therefore, it seems plausible to suggest that key parameters are the efficacy and subcellular distribution of Cl- transporters rather than the polarity of steady-state GABA actions. A further related question is: what are the mechanisms of Cl- regulation and homeostasis during pathophysiological conditions such as epilepsy in adults and neonates? Here I present results that were obtained by means of a newly developed method of measurements of the efficacy of a K-Cl cotransport. In Study I, the developmental profile of KCC2 functionality during development was analyzed both in dissociated neuronal cultures and in acute hippocampal slices. A novel method of photolysis of caged GABA in combination with Cl- loading to the somata was used in this study to assess the extrusion efficacy of KCC2. We demonstrated that these two preparations exhibit a different temporal profile of functional KCC2 upregulation. In Study II, we reported an observation of highly distorted dendritic spines in neurons cultured from KCC2-/- embryos. During their development in the culture dish, KCC2-lacking neurons failed to develop mature, mushroom-shaped dendritic spines but instead maintained an immature phenotype of long, branching and extremely motile protrusions. It was shown that the role of KCC2 in spine maturation is not based on its transport activity, but is mediated by interactions with cytoskeletal proteins. Another important player in Cl- regulation, NKCC1 and its role in the induction and maintenance of native Cl- gradients between the axon initial segment (AIS) and soma was the subject of Study III. There we demonstrated that this transporter mediates accumulation of Cl- in the axon initial segment of neocortical and hippocampal principal neurons. The results suggest that the reversal potential of the GABAA response triggered by distinct populations of interneurons show large subcellular variations. Finally, a novel mechanism of fast post-translational upregulation of the membrane-inserted, functionally active KCC2 pool during in-vivo neonatal seizures and epileptiform-like activity in vitro was identified and characterized in Study IV. The seizure-induced KCC2 upregulation may act as an intrinsic antiepileptogenic mechanism.

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The technical developments and advances that have taken place thus far are reviewed in those areas impacting future phased array active aperture radar systems. The areas covered are printed circuit antennas and antenna arrays, GaAs MMIC design and fabrication leading to affordable transmitter-receiver (T-R) modules, and novel hardware and software developments. The use of fiber-optic distribution networks to interconnect the monolithically integrated optical components with the T-R modules is discussed. Beamforming and sidelobe control techniques for active phased array systems are also examined.

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An efficient load flow solution technique is required as a part of the distribution automation (DA) system for taking various control and operations decisions. This paper presents an efficient and robust three phase power flow algorithm for application to radial distribution networks. This method exploits the radial nature of the network and uses forward and backward propagation to calculate branch currents and node voltages. The proposed method has been tested to analyse several practical distribution networks of various voltage levels and also having high R/X ratio. The results for a practical distribution feeder are presented for illustration purposes. The application of the proposed method is also extended to find optimum location for reactive power compensation and network reconfiguration for planning and day-to-day operation of distribution networks.

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The current power grid is on the cusp of modernization due to the emergence of distributed generation and controllable loads, as well as renewable energy. On one hand, distributed and renewable generation is volatile and difficult to dispatch. On the other hand, controllable loads provide significant potential for compensating for the uncertainties. In a future grid where there are thousands or millions of controllable loads and a large portion of the generation comes from volatile sources like wind and solar, distributed control that shifts or reduces the power consumption of electric loads in a reliable and economic way would be highly valuable.

Load control needs to be conducted with network awareness. Otherwise, voltage violations and overloading of circuit devices are likely. To model these effects, network power flows and voltages have to be considered explicitly. However, the physical laws that determine power flows and voltages are nonlinear. Furthermore, while distributed generation and controllable loads are mostly located in distribution networks that are multiphase and radial, most of the power flow studies focus on single-phase networks.

This thesis focuses on distributed load control in multiphase radial distribution networks. In particular, we first study distributed load control without considering network constraints, and then consider network-aware distributed load control.

Distributed implementation of load control is the main challenge if network constraints can be ignored. In this case, we first ignore the uncertainties in renewable generation and load arrivals, and propose a distributed load control algorithm, Algorithm 1, that optimally schedules the deferrable loads to shape the net electricity demand. Deferrable loads refer to loads whose total energy consumption is fixed, but energy usage can be shifted over time in response to network conditions. Algorithm 1 is a distributed gradient decent algorithm, and empirically converges to optimal deferrable load schedules within 15 iterations.

We then extend Algorithm 1 to a real-time setup where deferrable loads arrive over time, and only imprecise predictions about future renewable generation and load are available at the time of decision making. The real-time algorithm Algorithm 2 is based on model-predictive control: Algorithm 2 uses updated predictions on renewable generation as the true values, and computes a pseudo load to simulate future deferrable load. The pseudo load consumes 0 power at the current time step, and its total energy consumption equals the expectation of future deferrable load total energy request.

Network constraints, e.g., transformer loading constraints and voltage regulation constraints, bring significant challenge to the load control problem since power flows and voltages are governed by nonlinear physical laws. Remarkably, distribution networks are usually multiphase and radial. Two approaches are explored to overcome this challenge: one based on convex relaxation and the other that seeks a locally optimal load schedule.

To explore the convex relaxation approach, a novel but equivalent power flow model, the branch flow model, is developed, and a semidefinite programming relaxation, called BFM-SDP, is obtained using the branch flow model. BFM-SDP is mathematically equivalent to a standard convex relaxation proposed in the literature, but numerically is much more stable. Empirical studies show that BFM-SDP is numerically exact for the IEEE 13-, 34-, 37-, 123-bus networks and a real-world 2065-bus network, while the standard convex relaxation is numerically exact for only two of these networks.

Theoretical guarantees on the exactness of convex relaxations are provided for two types of networks: single-phase radial alternative-current (AC) networks, and single-phase mesh direct-current (DC) networks. In particular, for single-phase radial AC networks, we prove that a second-order cone program (SOCP) relaxation is exact if voltage upper bounds are not binding; we also modify the optimal load control problem so that its SOCP relaxation is always exact. For single-phase mesh DC networks, we prove that an SOCP relaxation is exact if 1) voltage upper bounds are not binding, or 2) voltage upper bounds are uniform and power injection lower bounds are strictly negative; we also modify the optimal load control problem so that its SOCP relaxation is always exact.

To seek a locally optimal load schedule, a distributed gradient-decent algorithm, Algorithm 9, is proposed. The suboptimality gap of the algorithm is rigorously characterized and close to 0 for practical networks. Furthermore, unlike the convex relaxation approach, Algorithm 9 ensures a feasible solution. The gradients used in Algorithm 9 are estimated based on a linear approximation of the power flow, which is derived with the following assumptions: 1) line losses are negligible; and 2) voltages are reasonably balanced. Both assumptions are satisfied in practical distribution networks. Empirical results show that Algorithm 9 obtains 70+ times speed up over the convex relaxation approach, at the cost of a suboptimality within numerical precision.

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The direct measurement of in situ respiring bacteria using 5-cyano-2,3-ditolyl tetrazolium chloride (CTC) shows that, especially for Gram-negative bacteria, large numbers of viable but non-culturable (VBNC) bacteria are present in finished water from a conventional water treatment plant, and the regrowth of bacteria along distribution networks can be seen rapidly by using this very sensitive technique. The level of bacterial inactivation with chlorine is much less important than has been previously supposed (based on experiments with non-injured laboratory strains of bacteria and classical culture techniques). Threshold values of VBNC bacteria leaving water treatment plants or regrowing along distribution systems have to be determined for better control of coliform regrowth and health- risks associated with the consumption of drinking water.

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A superconducting fault current limiter (SFCL) in series with a downstream circuit breaker could provide a viable solution to controlling fault current levels in electrical distribution networks. In order to integrate the SFCL into power grids, we need a way to conveniently predict the performance of the SFCL in a given scenario. In this paper, short circuit analysis based on the electromagnetic transient program was used to investigate the operational behavior of the SFCL installed in an electrical distribution grid. System studies show that the SFCL can not only limit the fault current to an acceptable value, but also mitigate the voltage sag. The transient recovery voltage (TRV) could be remarkably damped and improved by the presence of the SFCL after the circuit breaker is opened to clear the fault. © 2007 British Crown Copyright.

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Flow measurement data at the district meter area (DMA) level has the potential for burst detection in the water distribution systems. This work investigates using a polynomial function fitted to the historic flow measurements based on a weighted least-squares method for automatic burst detection in the U.K. water distribution networks. This approach, when used in conjunction with an expectationmaximization (EM) algorithm, can automatically select useful data from the historic flow measurements, which may contain normal and abnormal operating conditions in the distribution network, e.g., water burst. Thus, the model can estimate the normal water flow (nonburst condition), and hence the burst size on the water distribution system can be calculated from the difference between the measured flow and the estimated flow. The distinguishing feature of this method is that the burst detection is fully unsupervised, and the burst events that have occurred in the historic data do not affect the procedure and bias the burst detection algorithm. Experimental validation of the method has been carried out using a series of flushing events that simulate burst conditions to confirm that the simulated burst sizes are capable of being estimated correctly. This method was also applied to eight DMAs with known real burst events, and the results of burst detections are shown to relate to the water company's records of pipeline reparation work. © 2014 American Society of Civil Engineers.

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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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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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The design and development of simulation models and tools for Demand Response (DR) programs are becoming more and more important for adequately taking the maximum advantages of DR programs use. Moreover, a more active consumers’ participation in DR programs can help improving the system reliability and decrease or defer the required investments. DemSi, a DR simulator, designed and implemented by the authors of this paper, allows studying DR actions and schemes in distribution networks. It undertakes the technical validation of the solution using realistic network simulation based on PSCAD. DemSi considers the players involved in DR actions, and the results can be analyzed from each specific player point of view.

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The large increase of Distributed Generation (DG) in Power Systems (PS) and specially in distribution networks makes the management of distribution generation resources an increasingly important issue. Beyond DG, other resources such as storage systems and demand response must be managed in order to obtain more efficient and “green” operation of PS. More players, such as aggregators or Virtual Power Players (VPP), that operate these kinds of resources will be appearing. This paper proposes a new methodology to solve the distribution network short term scheduling problem in the Smart Grid context. This methodology is based on a Genetic Algorithms (GA) approach for energy resource scheduling optimization and on PSCAD software to obtain realistic results for power system simulation. The paper includes a case study with 99 distributed generators, 208 loads and 27 storage units. The GA results for the determination of the economic dispatch considering the generation forecast, storage management and load curtailment in each period (one hour) are compared with the ones obtained with a Mixed Integer Non-Linear Programming (MINLP) approach.

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This paper present a methodology to choose the distribution networks reconfiguration that presents the lower power losses. The proposed methodology is based on statistical failure and repair data of the distribution power system components and uses fuzzy-probabilistic modeling for system component outage parameters. The proposed hybrid method using fuzzy sets and Monte Carlo simulation based on the fuzzyprobabilistic models allows catching both randomness and fuzziness of component outage parameters. A logic programming algorithm is applied, once obtained the system states by Monte Carlo Simulation, to get all possible reconfigurations for each system state. To evaluate the line flows and bus voltages and to identify if there is any overloading, and/or voltage violation an AC load flow has been applied to select the feasible reconfiguration with lower power losses. To illustrate the application of the proposed methodology, the paper includes a case study that considers a 115 buses distribution network.

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Important research effort has been devoted to the topic of optimal planning of distribution systems. The non linear nature of the system, the need to consider a large number of scenarios and the increasing necessity to deal with uncertainties make optimal planning in distribution systems a difficult task. Heuristic techniques approaches have been proposed to deal with these issues, overcoming some of the inherent difficulties of classic methodologies. This paper considers several methodologies used to address planning problems of electrical power distribution networks, namely mixedinteger linear programming (MILP), ant colony algorithms (AC), genetic algorithms (GA), tabu search (TS), branch exchange (BE), simulated annealing (SA) and the Bender´s decomposition deterministic non-linear optimization technique (BD). Adequacy of theses techniques to deal with uncertainties is discussed. The behaviour of each optimization technique is compared from the point of view of the obtained solution and of the methodology performance. The paper presents results of the application of these optimization techniques to a real case of a 10-kV electrical distribution system with 201 nodes that feeds an urban area.

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The use of distribution networks in the current scenario of high penetration of Distributed Generation (DG) is a problem of great importance. In the competitive environment of electricity markets and smart grids, Demand Response (DR) is also gaining notable impact with several benefits for the whole system. The work presented in this paper comprises a methodology able to define the cost allocation in distribution networks considering large integration of DG and DR resources. The proposed methodology is divided into three phases and it is based on an AC Optimal Power Flow (OPF) including the determination of topological distribution factors, and consequent application of the MW-mile method. The application of the proposed tariffs definition methodology is illustrated in a distribution network with 33 buses, 66 DG units, and 32 consumers with DR capacity.

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Tipicamente as redes elétricas de distribuição apresentam uma topologia parcialmente malhada e são exploradas radialmente. A topologia radial é obtida através da abertura das malhas nos locais que otimizam o ponto de operação da rede, através da instalação de aparelhos de corte que operam normalmente abertos. Para além de manterem a topologia radial, estes equipamentos possibilitam também a transferência de cargas entre saídas, aquando da ocorrência de defeitos. As saídas radiais são ainda dotadas de aparelhos de corte que operam normalmente fechados, estes têm como objetivo maximizar a fiabilidade e isolar defeitos, minimizando a área afetada pelos mesmos. Assim, na presente dissertação são desenvolvidos dois algoritmos determinísticos para a localização ótima de aparelhos de corte normalmente abertos e fechados, minimizando a potência ativa de perdas e o custo da energia não distribuída. O algoritmo de localização de aparelhos de corte normalmente abertos visa encontrar a topologia radial ótima que minimiza a potência ativa de perdas. O método é desenvolvido em ambiente Matlab – Tomlab, e é formulado como um problema de programação quadrática inteira mista. A topologia radial ótima é garantida através do cálculo de um trânsito de potências ótimo baseado no modelo DC. A função objetivo é dada pelas perdas por efeito de Joule. Por outro lado o problema é restringido pela primeira lei de Kirchhoff, limites de geração das subestações, limites térmicos dos condutores, trânsito de potência unidirecional e pela condição de radialidade. Os aparelhos de corte normalmente fechados são localizados ao longo das saídas radiais obtidas pelo anterior algoritmo, e permite minimizar o custo da energia não distribuída. No limite é possível localizar um aparelho de corte normalmente fechado em todas as linhas de uma rede de distribuição, sendo esta a solução que minimiza a energia não distribuída. No entanto, tendo em conta que a cada aparelho de corte está associado um investimento, é fundamental encontrar um equilíbrio entre a melhoria de fiabilidade e o investimento. Desta forma, o algoritmo desenvolvido avalia os benefícios obtidos com a instalação de aparelhos de corte normalmente fechados, e retorna o número e a localização dos mesmo que minimiza o custo da energia não distribuída. Os métodos apresentados são testados em duas redes de distribuição reais, exploradas com um nível de tensão de 15 kV e 30 kV, respetivamente. A primeira rede é localizada no distrito do Porto e é caraterizada por uma topologia mista e urbana. A segunda rede é localizada no distrito de Bragança e é caracterizada por uma topologia maioritariamente aérea e rural.