49 resultados para Generalized inverse Gaussian distribution


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This paper presents a methodology for distribution networks reconfiguration in outage presence in order to choose the reconfiguration that presents the lower power losses. The methodology is based on statistical failure and repair data of the distribution power system components and uses fuzzy-probabilistic modelling for system component outage parameters. Fuzzy membership functions of system component outage parameters are obtained by statistical records. A hybrid method of fuzzy set and Monte Carlo simulation based on the fuzzy-probabilistic models allows catching both randomness and fuzziness of component outage parameters. Once obtained the system states by Monte Carlo simulation, a logical programming algorithm is applied to get all possible reconfigurations for every system state. In order to evaluate the line flows and bus voltages and to identify if there is any overloading, and/or voltage violation a distribution power flow has been applied to select the feasible reconfiguration with lower power losses. To illustrate the application of the proposed methodology to a practical case, the paper includes a case study that considers a real distribution network.

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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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In this paper is presented a Game Theory based methodology to allocate transmission costs, considering cooperation and competition between producers. As original contribution, it finds the degree of participation on the additional costs according to the demand behavior. A comparative study was carried out between the obtained results using Nucleolus balance and Shapley Value, with other techniques such as Averages Allocation method and the Generalized Generation Distribution Factors method (GGDF). As example, a six nodes network was used for the simulations. The results demonstrate the ability to find adequate solutions on open access environment to the networks.

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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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Currently, power systems (PS) already accommodate a substantial penetration of distributed generation (DG) and operate in competitive environments. In the future, as the result of the liberalisation and political regulations, PS will have to deal with large-scale integration of DG and other distributed energy resources (DER), such as storage and provide market agents to ensure a flexible and secure operation. This cannot be done with the traditional PS operational tools used today like the quite restricted information systems Supervisory Control and Data Acquisition (SCADA) [1]. The trend to use the local generation in the active operation of the power system requires new solutions for data management system. The relevant standards have been developed separately in the last few years so there is a need to unify them in order to receive a common and interoperable solution. For the distribution operation the CIM models described in the IEC 61968/70 are especially relevant. In Europe dispersed and renewable energy resources (D&RER) are mostly operated without remote control mechanisms and feed the maximal amount of available power into the grid. To improve the network operation performance the idea of virtual power plants (VPP) will become a reality. In the future power generation of D&RER will be scheduled with a high accuracy. In order to realize VPP decentralized energy management, communication facilities are needed that have standardized interfaces and protocols. IEC 61850 is suitable to serve as a general standard for all communication tasks in power systems [2]. The paper deals with international activities and experiences in the implementation of a new data management and communication concept in the distribution system. The difficulties in the coordination of the inconsistent developed in parallel communication and data management standards - are first addressed in the paper. The upcoming unification work taking into account the growing role of D&RER in the PS is shown. It is possible to overcome the lag in current practical experiences using new tools for creating and maintenance the CIM data and simulation of the IEC 61850 protocol – the prototype of which is presented in the paper –. The origin and the accuracy of the data requirements depend on the data use (e.g. operation or planning) so some remarks concerning the definition of the digital interface incorporated in the merging unit idea from the power utility point of view are presented in the paper too. To summarize some required future work has been identified.

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Energy Resources Management can play a very relevant role in future power systems in SmartGrid context, with high penetration of distributed generation and storage systems. This paper deals with the importance of resources management in incident situation. The system to consider a high penetration of distributed generation, demand response, storage units and network reconfiguration. A case study evidences the advantages of using a flexible SCADA to control the energy resources in incident situation.

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For some years now, translation theorist and educator Anthony Pym has been trying to establish a dialogue between the academic tradition he comes from and the world of the language industries into which he is meant to introduce his students: in other words, between the Translation Studies discipline and the localisation sector. This rapprochement is also the stated aim of his new book The Moving Text (p. 159). Rather than collect and synthesise what was previously dispersed over several articles, Pym has rewritten his material completely, both literally and conceptually, all in the light of the more than three decades of research he has conducted into the field of cross--cultural communication. The theoretical arguments are ably supported by a few short but telling and well-exploited examples.

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Traffic emissions and tobacco smoke are considered two main sources of polycyclic aromatic hydrocarbons (PAHs) in indoor and outdoor air. In this study, the impact of these sources on the level of fine particulate matter (PM2.5) and on the distribution of 15 PAHs regarded as priority pollutants by the US-EPA on PM2.5 were evaluated and compared. Outdoor and indoor PM2.5 samples were collected during winter 2008 in Oporto city in Portugal, for sampling periods of 12 and 24 hours, respectively. The outdoor PM2.5 were sampled at one site directly influenced by traffic emissions and the indoor PM2.5 samples were collected at one home directly influenced by tobacco smoke and another one without smoke. A methodology based on microwave-assisted extraction and liquid chromatography with fluorescence detection was applied for the efficient PAHs determination in indoor and outdoor PM2.5. PAHs in indoor PM2.5 concentrations were significantly influenced by the presence of traffic and tobacco smoking emissions. The mean of ΣPAHs in the outdoor traffic PM2.5 was not significantly different from the value attained in the indoor without smoking site. The tobacco smoke increased significantly PAHs concentrations on average about 1000 times more, when compared with the outdoor profile samples suggesting that tobacco smoking may be the most important source of indoor PAHs pollution.

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Future distribution systems will have to deal with an intensive penetration of distributed energy resources ensuring reliable and secure operation according to the smart grid paradigm. SCADA (Supervisory Control and Data Acquisition) is an essential infrastructure for this evolution. This paper proposes a new conceptual design of an intelligent SCADA with a decentralized, flexible, and intelligent approach, adaptive to the context (context awareness). This SCADA model is used to support the energy resource management undertaken by a distribution network operator (DNO). Resource management considers all the involved costs, power flows, and electricity prices, allowing the use of network reconfiguration and load curtailment. Locational Marginal Prices (LMP) are evaluated and used in specific situations to apply Demand Response (DR) programs on a global or a local basis. The paper includes a case study using a 114 bus distribution network and load demand based on real data.

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This study compared the ground reaction forces (GRF) and plantar pressures between unloaded and occasional loaded gait. The GRF and plantar pressures of 60 participants were recorded during unloaded gait and occasional loaded gait (wearing a backpack that raised their body mass index to 30); this load criterion was adopted because is considered potentially harmful in permanent loaded gait (obese people). The results indicate an overall increase (absolute values) of GRF and plantar pressures during occasional loaded gait (p < 0.05); also, higher normalized (by total weight) values in the medial midfoot and toes, and lower values in the lateral rearfoot region were observed. During loaded gait the magnitude of the vertical GRF (impact and thrust maximum) decreased and the shear forces increased more than did the proportion of the load (normalized values). These data suggest a different pattern of GRF and plantar pressure distribution during occasional loaded compared to unloaded gait.

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Phenolic acids are ubiquitous antioxidants accounting for approximately one third of the phenolic compounds in our diet. Their importance was supported by epidemiological studies that suggest an inverse relationship between dietary intake of phenolic antioxidants and the occurrence of diseases, such as cancer and neurodegenerative disorders. However, until now, most of natural antioxidants have limited therapeutic success a fact that could be related with their limited distribution throughout the body and with the inherent difficulties to attain the target sites. The development of phenolic antioxidants based on a hybrid concept and structurally based on natural hydroxybenzoic (gallic acid) and hydroxycinnamic (caffeic acid) scaffolds seems to be a suitable solution to surpass the mentioned drawbacks. Galloylecinnamic hybrids were synthesized and their antioxidant activity as well as partition coefficients and redox potentials evaluated. The structureepropertyeactivity relationship (SPAR) study revealed the existence of a correlation between the redox potentials and antioxidant activity. The galloylecinnamic acid hybrid stands out as the best antioxidant supplementing the effect of a blend of gallic acid plus caffeic acid endorsing the hypothesis that the whole is greater than the sum of the parts. In addition, some hybrid compounds possess an appropriate lipophilicity allowing their application as chain-breaking antioxidant in biomembranes or other type of lipidic systems. Their predicted ADME properties are also in accordance with the general requirements for drug-like compounds. Accordingly, these phenolic hybrids can be seen as potential antioxidants for tackling the oxidative status linked to the neurodegenerative, inflammatory or cancer processes.

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Composition is a practice of key importance in software engineering. When real-time applications are composed it is necessary that their timing properties (such as meeting the deadlines) are guaranteed. The composition is performed by establishing an interface between the application and the physical platform. Such an interface does typically contain information about the amount of computing capacity needed by the application. In multiprocessor platforms, the interface should also present information about the degree of parallelism. Recently there have been quite a few interface proposals. However, they are either too complex to be handled or too pessimistic.In this paper we propose the Generalized Multiprocessor Periodic Resource model (GMPR) that is strictly superior to the MPR model without requiring a too detailed description. We describe a method to generate the interface from the application specification. All these methods have been implemented in Matlab routines that are publicly available.

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A new operationalmatrix of fractional integration of arbitrary order for generalized Laguerre polynomials is derived.The fractional integration is described in the Riemann-Liouville sense.This operational matrix is applied together with generalized Laguerre tau method for solving general linearmultitermfractional differential equations (FDEs).Themethod has the advantage of obtaining the solution in terms of the generalized Laguerre parameter. In addition, only a small dimension of generalized Laguerre operational matrix is needed to obtain a satisfactory result. Illustrative examples reveal that the proposedmethod is very effective and convenient for linear multiterm FDEs on a semi-infinite interval.

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An approach for the analysis of uncertainty propagation in reliability-based design optimization of composite laminate structures is presented. Using the Uniform Design Method (UDM), a set of design points is generated over a domain centered on the mean reference values of the random variables. A methodology based on inverse optimal design of composite structures to achieve a specified reliability level is proposed, and the corresponding maximum load is outlined as a function of ply angle. Using the generated UDM design points as input/output patterns, an Artificial Neural Network (ANN) is developed based on an evolutionary learning process. Then, a Monte Carlo simulation using ANN development is performed to simulate the behavior of the critical Tsai number, structural reliability index, and their relative sensitivities as a function of the ply angle of laminates. The results are generated for uniformly distributed random variables on a domain centered on mean values. The statistical analysis of the results enables the study of the variability of the reliability index and its sensitivity relative to the ply angle. Numerical examples showing the utility of the approach for robust design of angle-ply laminates are presented.