An approach based on neural networks for identification of fault sections in radial distribution systems

The main objective involved with this paper consists of presenting the results obtained from the application of artificial neural networks and statistical tools in the automatic identification and classification process of faults in electric power distribution systems. The developed techniques to treat the proposed problem have used, in an integrated way, several approaches that can contribute to the successful detection process of faults, aiming that it is carried out in a reliable and safe way. The compilations of the results obtained from practical experiments accomplished in a pilot radial distribution feeder have demonstrated that the developed techniques provide accurate results, identifying and classifying efficiently the several occurrences of faults observed in the feeder.

Artificial immune systems applied to optimal capacitor placement in radial distribution networks

The capacitor placement problem for radial distribution networks aims to determine capacitor types, sizes, locations and control scheme. This is a combinatorial problem that can be formulated as a mixed integer nonlinear program. The paper presents an algorithm inspired in artificial immune systems and developed for this specific problem. A good performance was obtained through experimental tests applied to known systems. © 2006 IEEE.

Optimal allocation of capacitors in radial distribution systems with distributed generation

This paper presents a mixed-integer linear programming approach to solving the optimal fixed/switched capacitors allocation (OCA) problem in radial distribution systems with distributed generation. The use of a mixed-integer linear formulation guarantees convergence to optimality using existing optimization software. The results of one test system and one real distribution system are presented in order to show the accuracy as well as the efficiency of the proposed solution technique. © 2011 IEEE.

A mixed-integer LP model for the optimal allocation of voltage regulators and capacitors in radial distribution systems

This paper presents a mixed-integer linear programming model to solve the problem of allocating voltage regulators and fixed or switched capacitors (VRCs) in radial distribution systems. The use of a mixed-integer linear model guarantees convergence to optimality using existing optimization software. In the proposed model, the steady-state operation of the radial distribution system is modeled through linear expressions. The results of one test system and one real distribution system are presented in order to show the accuracy as well as the efficiency of the proposed solution technique. An heuristic to obtain the Pareto front for the multiobjective VRCs allocation problem is also presented. © 2012 Elsevier Ltd. All rights reserved.

Bilevel approach for optimal location and contract pricing of distributed generation in radial distribution systems using mixed-integer linear programming

In this study, a novel approach for the optimal location and contract pricing of distributed generation (DG) is presented. Such an approach is designed for a market environment in which the distribution company (DisCo) can buy energy either from the wholesale energy market or from the DG units within its network. The location and contract pricing of DG is determined by the interaction between the DisCo and the owner of the distributed generators. The DisCo intends to minimise the payments incurred in meeting the expected demand, whereas the owner of the DG intends to maximise the profits obtained from the energy sold to the DisCo. This two-agent relationship is modelled in a bilevel scheme. The upper-level optimisation is for determining the allocation and contract prices of the DG units, whereas the lower-level optimisation is for modelling the reaction of the DisCo. The bilevel programming problem is turned into an equivalent single-level mixed-integer linear optimisation problem using duality properties, which is then solved using commercially available software. Results show the robustness and efficiency of the proposed model compared with other existing models. As regards to contract pricing, the proposed approach allowed to find better solutions than those reported in previous works. © The Institution of Engineering and Technology 2013.

Measurement of the muon charge asymmetry in inclusive pp -> W plus X production at root s=7 TeV and an improved determination of light parton distribution functions

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Constraints on parton distribution functions and extraction of the strong coupling constant from the inclusive jet cross section in pp collisions at root s=7TeV

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Performance and radial distribution profiles of a variable flow rate sprinkler developed for precision irrigation

Variable rate sprinklers (VRS) have been developed to promote localized water application of irrigated areas. In Precision Irrigation, VRS permits better control of flow adjustment and, at the same time, provides satisfactory radial distribution profiles for various pressures and flow rates are really necessary. The objective of this work was to evaluate the performance and radial distribution profiles of a developed VRS which varies the nozzle cross sectional area by moving a pin in or out using a stepper motor. Field tests were performed under different conditions of service pressure, rotation angles imposed on the pin and flow rate which resulted in maximal water throw radiuses ranging from 7.30 to 10.38 m. In the experiments in which the service pressure remained constant, the maximal throw radius varied from 7.96 to 8.91 m. Averages were used of repetitions performed under conditions without wind or with winds less than 1.3 m s-1. The VRS with the four stream deflector resulted in greater water application throw radius compared to the six stream deflector. However, the six stream deflector had greater precipitation intensities, as well as better distribution. Thus, selection of the deflector to be utilized should be based on project requirements, respecting the difference in the obtained results. With a small opening of the nozzle, the VRS produced small water droplets that visually presented applicability for foliar chemigation. Regarding the comparison between the estimated and observed flow rates, the stepper motor produced excellent results.

dGEMRIC and subsequent T1 mapping of the hip at 1.5 Tesla: normative data on zonal and radial distribution in asymptomatic volunteers

To characterize the zonal distribution of three-dimensional (3D) T1 mapping in the hip joint of asymptomatic adult volunteers.

Evaluation of radial distribution of cartilage degeneration and necessity of pre-contrast measurements using radial dGEMRIC in adults with acetabular dysplasia

Background The purpose of the present study was to investigate the radial distribution patterns of cartilage degeneration in dysplastic hips at different stages of secondary osteoarthritis (OA) by using radial delayed gadolinium-enhanced magnetic resonance imaging of cartilage (dGEMRIC), and to assess whether pre-contrast measurements are necessary. Methods Thirty-five hips in 21 subjects (mean age ± SD, 27.6 ± 10.8 years) with acetabular dysplasia (lateral CE angle < 25°) were studied. Severity of OA was assessed on radiographs using Tönnis grading. Pre- (T1pre) and post-contrast T1 (T1Gd) values were measured at 7 sub-regions on radial reformatted slices acquired from a 3-dimensional (3D) T1 mapping sequence using a 1.5 T MR scanner. Values of radial T1pre, T1Gd and ΔR1 (1/T1Gd - 1/T1pre) of subgroups with different severity of OA were compared to those of the subgroup without OA using nonparametric tests, and bivariate linear Pearson correlations between radial T1Gd and ΔR1 were analyzed for each subgroup. Results Compared to the subgroup without OA, the subgroup with mild OA was observed with a significant decrease in T1Gd in the anterosuperior to superior sub-regions (mean, 476 ~ 507 ms, p = 0.026 ~ 0.042) and a significant increase in ΔR1 in the anterosuperior to superoposterior and posterior sub-regions (mean, 0.93 ~ 1.37 s-1, p = 0.012 ~ 0.042). The subgroup with moderate to severe OA was observed with a significant overall decrease in T1Gd (mean, 404 ~ 452 ms, p = 0.001 ~ 0.020) and an increase in ΔR1 (mean, 1.17 ~1.69 s-1, p = 0.001 ~ 0.020). High correlations were observed between radial T1Gd and ΔR1 for all subgroups (r = −0.869 ~ −0.944, p < 0.001). Conclusions Radial dGEMRIC without pre-contrast measurements is useful for evaluating different patterns of cartilage degeneration in the entire hip joint of patients with hip dysplasia, particularly for those in early stages of secondary OA.

DISTRIBUTION FUNCTIONS, MEAN SQUARED ERRORS, AND CONFIDENCE LIMITS FOR RIDGE REGRESSION ESTIMATORS

A large number of ridge regression estimators have been proposed and used with little knowledge of their true distributions. Because of this lack of knowledge, these estimators cannot be used to test hypotheses or to form confidence intervals.^ This paper presents a basic technique for deriving the exact distribution functions for a class of generalized ridge estimators. The technique is applied to five prominent generalized ridge estimators. Graphs of the resulting distribution functions are presented. The actual behavior of these estimators is found to be considerably different than the behavior which is generally assumed for ridge estimators.^ This paper also uses the derived distributions to examine the mean squared error properties of the estimators. A technique for developing confidence intervals based on the generalized ridge estimators is also presented. ^

An adaptive algorithm for clustering cumulative probability distribution functions using the Kolmogorov–Smirnov two-sample test

This paper proposes an adaptive algorithm for clustering cumulative probability distribution functions (c.p.d.f.) of a continuous random variable, observed in different populations, into the minimum homogeneous clusters, making no parametric assumptions about the c.p.d.f.’s. The distance function for clustering c.p.d.f.’s that is proposed is based on the Kolmogorov–Smirnov two sample statistic. This test is able to detect differences in position, dispersion or shape of the c.p.d.f.’s. In our context, this statistic allows us to cluster the recorded data with a homogeneity criterion based on the whole distribution of each data set, and to decide whether it is necessary to add more clusters or not. In this sense, the proposed algorithm is adaptive as it automatically increases the number of clusters only as necessary; therefore, there is no need to fix in advance the number of clusters. The output of the algorithm are the common c.p.d.f. of all observed data in the cluster (the centroid) and, for each cluster, the Kolmogorov–Smirnov statistic between the centroid and the most distant c.p.d.f. The proposed algorithm has been used for a large data set of solar global irradiation spectra distributions. The results obtained enable to reduce all the information of more than 270,000 c.p.d.f.’s in only 6 different clusters that correspond to 6 different c.p.d.f.’s.

On-line learning in radial basis functions networks

An analytic investigation of the average case learning and generalization properties of Radial Basis Function Networks (RBFs) is presented, utilising on-line gradient descent as the learning rule. The analytic method employed allows both the calculation of generalization error and the examination of the internal dynamics of the network. The generalization error and internal dynamics are then used to examine the role of the learning rate and the specialization of the hidden units, which gives insight into decreasing the time required for training. The realizable and over-realizable cases are studied in detail; the phase of learning in which the hidden units are unspecialized (symmetric phase) and the phase in which asymptotic convergence occurs are analyzed, and their typical properties found. Finally, simulations are performed which strongly confirm the analytic results.

Characterization of time-resolved laser differential phase using 3D complementary cumulative distribution functions

An experimental method for characterizing the time-resolved phase noise of a fast switching tunable laser is discussed. The method experimentally determines a complementary cumulative distribution function of the laser's differential phase as a function of time after a switching event. A time resolved bit error rate of differential quadrature phase shift keying formatted data, calculated using the phase noise measurements, was fitted to an experimental time-resolved bit error rate measurement using a field programmable gate array, finding a good agreement between the time-resolved bit error rates.

Enhancing SPH using moving least-squares and radial basis functions

In this paper we consider two sources of enhancement for the meshfree Lagrangian particle method smoothed particle hydrodynamics (SPH) by improving the accuracy of the particle approximation. Namely, we will consider shape functions constructed using: moving least-squares approximation (MLS); radial basis functions (RBF). Using MLS approximation is appealing because polynomial consistency of the particle approximation can be enforced. RBFs further appeal as they allow one to dispense with the smoothing-length - the parameter in the SPH method which governs the number of particles within the support of the shape function. Currently, only ad hoc methods for choosing the smoothing-length exist. We ensure that any enhancement retains the conservative and meshfree nature of SPH. In doing so, we derive a new set of variationally-consistent hydrodynamic equations. Finally, we demonstrate the performance of the new equations on the Sod shock tube problem.