Increase of the Delivered Power Probability in Distribution Networks using Pareto DC Programming

A methodology to increase the probability of delivering power to any load point through the identification of new investments in distribution network components is proposed in this paper. The method minimizes the investment cost as well as the cost of energy not supplied in the network. A DC optimization model based on mixed integer non-linear programming is developed considering the Pareto front technique in order to identify the adequate investments in distribution networks components which allow increasing the probability of delivering power for any customer in the distribution system at the minimum possible cost for the system operator, while minimizing the energy not supplied cost. Thus, a multi-objective problem is formulated. To illustrate the application of the proposed methodology, the paper includes a case study which considers a 180 bus distribution network

Winâ Foy : functional object-oriented programming language

This thesis will introduce a new strongly typed programming language utilizing Self types, named Win--*Foy, along with a suitable user interface designed specifically to highlight language features. The need for such a programming language is based on deficiencies found in programming languages that support both Self types and subtyping. Subtyping is a concept that is taken for granted by most software engineers programming in object-oriented languages. Subtyping supports subsumption but it does not support the inheritance of binary methods. Binary methods contain an argument of type Self, the same type as the object itself, in a contravariant position, i.e. as a parameter. There are several arguments in favour of introducing Self types into a programming language (11. This rationale led to the development of a relation that has become known as matching [4, 5). The matching relation does not support subsumption, however, it does support the inheritance of binary methods. Two forms of matching have been proposed (lJ. Specifically, these relations are known as higher-order matching and I-bound matching. Previous research on these relations indicates that the higher-order matching relation is both reflexive and transitive whereas the f-bound matching is reflexive but not transitive (7]. The higher-order matching relation provides significant flexibility regarding inheritance of methods that utilize or return values of the same type. This flexibility, in certain situations, can restrict the programmer from defining specific classes and methods which are based on constant values [21J. For this reason, the type This is used as a second reference to the type of the object that cannot, contrary to Self, be specialized in subclasses. F-bound matching allows a programmer to define a function that will work for all types of A', a subtype of an upper bound function of type A, with the result type being dependent on A'. The use of parametric polymorphism in f-bound matching provides a connection to subtyping in object-oriented languages. This thesis will contain two main sections. Firstly, significant details concerning deficiencies of the subtype relation and the need to introduce higher-order and f-bound matching relations into programming languages will be explored. Secondly, a new programming language named Win--*Foy Functional Object-Oriented Programming Language has been created, along with a suitable user interface, in order to facilitate experimentation by programmers regarding the matching relation. The construction of the programming language and the user interface will be explained in detail.

Surface acidity/basicity and catalytic activity of mixed oxides of Zr, La and Al

The surface acidity/basicity of binary oxides of Zr and La and the ternary oxides of Zr, La and Al are reported. The data have been correlated with their catalytic activity towards liquid phase reduction of cyclohexanone.

Optimization-Based Robotic Manipulation for Safe Interaction with Human Operators

This thesis investigates a method for human-robot interaction (HRI) in order to uphold productivity of industrial robots like minimization of the shortest operation time, while ensuring human safety like collision avoidance. For solving such problems an online motion planning approach for robotic manipulators with HRI has been proposed. The approach is based on model predictive control (MPC) with embedded mixed integer programming. The planning strategies of the robotic manipulators mainly considered in the thesis are directly performed in the workspace for easy obstacle representation. The non-convex optimization problem is approximated by a mixed-integer program (MIP). It is further effectively reformulated such that the number of binary variables and the number of feasible integer solutions are drastically decreased. Safety-relevant regions, which are potentially occupied by the human operators, can be generated online by a proposed method based on hidden Markov models. In contrast to previous approaches, which derive predictions based on probability density functions in the form of single points, such as most likely or expected human positions, the proposed method computes safety-relevant subsets of the workspace as a region which is possibly occupied by the human at future instances of time. The method is further enhanced by combining reachability analysis to increase the prediction accuracy. These safety-relevant regions can subsequently serve as safety constraints when the motion is planned by optimization. This way one arrives at motion plans that are safe, i.e. plans that avoid collision with a probability not less than a predefined threshold. The developed methods have been successfully applied to a developed demonstrator, where an industrial robot works in the same space as a human operator. The task of the industrial robot is to drive its end-effector according to a nominal sequence of grippingmotion-releasing operations while no collision with a human arm occurs.

Approximate Gauss-Newton methods for nonlinear least squares problems

The Gauss–Newton algorithm is an iterative method regularly used for solving nonlinear least squares problems. It is particularly well suited to the treatment of very large scale variational data assimilation problems that arise in atmosphere and ocean forecasting. The procedure consists of a sequence of linear least squares approximations to the nonlinear problem, each of which is solved by an “inner” direct or iterative process. In comparison with Newton’s method and its variants, the algorithm is attractive because it does not require the evaluation of second-order derivatives in the Hessian of the objective function. In practice the exact Gauss–Newton method is too expensive to apply operationally in meteorological forecasting, and various approximations are made in order to reduce computational costs and to solve the problems in real time. Here we investigate the effects on the convergence of the Gauss–Newton method of two types of approximation used commonly in data assimilation. First, we examine “truncated” Gauss–Newton methods where the inner linear least squares problem is not solved exactly, and second, we examine “perturbed” Gauss–Newton methods where the true linearized inner problem is approximated by a simplified, or perturbed, linear least squares problem. We give conditions ensuring that the truncated and perturbed Gauss–Newton methods converge and also derive rates of convergence for the iterations. The results are illustrated by a simple numerical example. A practical application to the problem of data assimilation in a typical meteorological system is presented.

Characterization and identification of mixed-metal phosphates in soils: the application, of Raman spectroscopy

The development of protocols for the identification of metal phosphates in phosphate-treated, metal-contaminated soils is a necessary yet problematical step in the validation of remediation schemes involving immobilization of metals as phosphate phases. The potential for Raman spectroscopy to be applied to the identification of these phosphates in soils has yet to be fully explored. With this in mind, a range of synthetic mixed-metal hydroxylapatites has been characterized and added to soils at known concentrations for analysis using both bulk X-ray powder diffraction (XRD) and Raman spectroscopy. Mixed-metal hydroxylapatites in the binary series Ca-Cd, Ca-Pb, Ca-Sr and Cd-Pb synthesized in the presence of acetate and carbonate ions, were characterized using a range of analytical techniques including XRD, analytical scanning electron microscopy (SEM), infrared spectroscopy (IR), inductively coupled plasma-atomic emission spectrometry (ICP-AES) and Raman spectroscopy. Only the Ca-Cd series displays complete solid solution, although under the synthesis conditions of this study the Cd-5(PO4)(3)OH end member could not be synthesized as a pure phase. Within the Ca-Cd series the cell parameters, IR active modes and Raman active bands vary linearly as a function of Cd content. X-ray diffraction and extended X-ray absorption fine structure spectroscopy (EXAFS) suggest that the Cd is distributed across both the Ca(1) and Ca(2) sites, even at low Cd concentrations. In order to explore the likely detection limits for mixed-metal phosphates in soils for XRD and Raman spectroscopy, soils doped with mixed-metal hydroxylapatites at concentrations of 5, 1 and 0.5 wt.% were then studied. X-ray diffraction could not confirm unambiguously the presence or identity of mixed-metal phosphates in soils at concentrations below 5 wt.%. Raman spectroscopy proved a far more sensitive method for the identification of mixed-metal hydroxylapatites in soils, which could positively identify the presence of such phases in soils at all the dopant concentrations used in this study. Moreover, Raman spectroscopy could also provide an accurate assessment of the degree of chemical substitution in the hydroxylapatites even when present in soils at concentrations as low as 0.1%.

A practical approach to a multi-level analysis with a sparse binary outcome within a large surgical trial

Objectives: To assess the potential source of variation that surgeon may add to patient outcome in a clinical trial of surgical procedures. Methods: Two large (n = 1380) parallel multicentre randomized surgical trials were undertaken to compare laparoscopically assisted hysterectomy with conventional methods of abdominal and vaginal hysterectomy; involving 43 surgeons. The primary end point of the trial was the occurrence of at least one major complication. Patients were nested within surgeons giving the data set a hierarchical structure. A total of 10% of patients had at least one major complication, that is, a sparse binary outcome variable. A linear mixed logistic regression model (with logit link function) was used to model the probability of a major complication, with surgeon fitted as a random effect. Models were fitted using the method of maximum likelihood in SAS((R)). Results: There were many convergence problems. These were resolved using a variety of approaches including; treating all effects as fixed for the initial model building; modelling the variance of a parameter on a logarithmic scale and centring of continuous covariates. The initial model building process indicated no significant 'type of operation' across surgeon interaction effect in either trial, the 'type of operation' term was highly significant in the abdominal trial, and the 'surgeon' term was not significant in either trial. Conclusions: The analysis did not find a surgeon effect but it is difficult to conclude that there was not a difference between surgeons. The statistical test may have lacked sufficient power, the variance estimates were small with large standard errors, indicating that the precision of the variance estimates may be questionable.

Structural and equilibrium studies on mixed ligand complexes of Co(II), Ni(II), Cu(II) and Zn(II) with N-(2-benzimidazolyl)methyliminodiacetic acid and typical N,N donor ligands

Mixed ligand complexes: [Co(L)(bipy)] (.) 3H(2)O (1), [Ni(L)(phen)] (.) H2O (2), [Cu(L)(phen)] (.) 3H(2)O (3) and [Zn(L)(bipy)] (.) 3H(2)O (4), where L2- = two -COOH deprotonated dianion of N-(2-benzimidazolyl)methyliminodiacetic acid (H(2)bzimida, hereafter, H,L), bipy = 2,2' bipyridine and phen = 1,10-phenanthroline have been isolated and characterized by elemental analysis, spectral and magnetic measurements and thermal studies. Single crystal X-ray diffraction studies show octahedral geometry for 1, 2 and 4 and square pyramidal geometry for 3. Equilibrium studies in aqueous solution (ionic strength I = 10(-1) mol dm(-3) (NaNO3), at 25 +/- 1 degrees C) using different molar proportions of M(II):H2L:B, where M = Co, Ni, Cu and Zn and B = phen, bipy and en (ethylene diamine), however, provides evidence of formation of mononuclear and binuclear binary and mixed ligand complexes: M(L), M(H-1L)(-), M(B)(2+), M(L)(B), M(H-1L)(B)(-), M-2(H-1L)(OH), (B)M(H-1L)M(B)(+), where H-1L3- represents two -COOH and the benzimidazole NI-H deprotonated quadridentate (O-, N, O-, N), or, quinquedentate (O-, N, O-, N, N-) function of the coordinated ligand H,L. Binuclear mixed ligand complex formation equilibria: M(L)(B) + M(B)(2+) = (B)M(H-1L)M(B)(+) + H+ is favoured with higher pi-acidity of the B ligands. For Co(II), Ni(II) and Cu(II), these equilibria are accompanied by blue shift of the electronic absorption maxima of M(II) ions, as a negatively charged bridging benzimidazolate moiety provides stronger ligand field than a neutral one. Solution stability of the mixed ligand complexes are in the expected order: Co(II) < Ni(II) < Cu(II) > Zn(II). The Delta logK(M) values are less negetive than their statistical values, indicating favoured formation of the mixed ligand complexes over the binary ones. (c) 2005 Elsevier B.V. All rights reserved.

Equilibrium studies on mixed ligand complex formation of Co(II), Ni(II), Cu(II) and Zn(II) with N-(2-hydroxybenzyl)-L-histidine (H(2)hb-L-his) and typical N,N donor ligands: Crystal structure of [Ni(hb-L-his)(bipyridine)]center dot H2O complex

Equilibrium study on complex formation of Co(II), Ni(II), Cu(II) and Zn(II), hereafter M(II), with the quadridentate (O-, N, O-, N) donor ligand, N-(2-hydroxybenzyl)-L-histidine (H(2)hb-L-his, hereafter H2L), in the absence and in the presence of typical (N, N) donor bidentate ligands, 1,10 phenanthroline(phen), 2, 2'-bipyridine(bipy), ethylenediamine(en), hereafter B, in aqueous solution at 25 +/- 1 degrees C was done at a fixed ionic strength, I = 0.1 mol dm(-3) (NaNO3) by combined pH-metric, UV-Vis and EPR measurements provide evidence for the formation of mononuclear and dinuclear binary and mixed ligand complexes of the types: M(L), M(L)(2)(2-), M-2(L)(2+), M-2(H-1L)(+), M(L)(B), (B)M(H-1L)M(B)(+). The imidazole moiety of the ligand is found to act as a bridging bidentate ligand in the dinuclear M-2(L)(2+), M-2(H-1L)(+) and (B)M(H-1L)M(B)(+) complexes, using its N-3 atom and N1-H deprotonated moiety. Stability constants of the complexes provide evidence of discrimination of Cu(II) from the other M(II) ions by this ligand. Solid complexes: [Ni(L)(H2O)(2)] (1), [Cu(L)(H2O)] (2), and [Ni(L)(bipy)] (.) H2O (3) have been isolated and characterized by various physicochemical studies. Single crystal X-ray diffraction of the ternary complex, 3, shows an octahedral [(O-,N,N,O-)(N,N)] geometry with extensive pi-pi stacking of the aromatic rings and H-bonding with imidazole (N1-H), secondary amino N-atom, the lattice H2O molecule, and the carboxylate and phenolate O-atoms. (c) 2006 Elsevier B.V. All rights reserved.

Application of neural network to hybrid systems with binary inputs

Boolean input systems are in common used in the electric industry. Power supplies include such systems and the power converter represents these. For instance, in power electronics, the control variable are the switching ON and OFF of components as thyristors or transistors. The purpose of this paper is to use neural network (NN) to control continuous systems with Boolean inputs. This method is based on classification of system variations associated with input configurations. The classical supervised backpropagation algorithm is used to train the networks. The training of the artificial neural network and the control of Boolean input systems are presented. The design procedure of control systems is implemented on a nonlinear system. We apply those results to control an electrical system composed of an induction machine and its power converter.

Dynamic integrated system optimization and parameter estimation for discrete time optimal control of nonlinear systems

An algorithm for solving nonlinear discrete time optimal control problems with model-reality differences is presented. The technique uses Dynamic Integrated System Optimization and Parameter Estimation (DISOPE), which achieves the correct optimal solution in spite of deficiencies in the mathematical model employed in the optimization procedure. A version of the algorithm with a linear-quadratic model-based problem, implemented in the C+ + programming language, is developed and applied to illustrative simulation examples. An analysis of the optimality and convergence properties of the algorithm is also presented.

Mixed copper, silver, and gold cyanides, (MxM′1–x)CN: tailoring chain structures to influence physical properties

Binary mixed-metal variants of the one-dimensional MCN compounds (M = Cu, Ag, and Au) have been prepared and characterized using powder X-ray diffraction, vibrational spectroscopy, and total neutron diffraction. A solid solution with the AgCN structure exists in the (CuxAg1–x)CN system over the range (0 ≤ x ≤ 1). Line phases with compositions (Cu1/2Au1/2)CN, (Cu7/12Au5/12)CN, (Cu2/3Au1/3)CN, and (Ag1/2Au1/2)CN, all of which have the AuCN structure, are found in the gold-containing systems. Infrared and Raman spectroscopies show that complete ordering of the type [M–C≡N–M′–N≡C−]n occurs only in (Cu1/2Au1/2)CN and (Ag1/2Au1/2)CN. The sense of the cyanide bonding was determined by total neutron diffraction to be [Ag–NC–Au–CN−]n in (Ag1/2Au1/2)CN and [Cu–NC–Au–CN−]n in (Cu1/2Au1/2)CN. In contrast, in (Cu0.50Ag0.50)CN, metal ordering is incomplete, and strict alternation of metals does not occur. However, there is a distinct preference (85%) for the N end of the cyanide ligand to be bonded to copper and for Ag–CN–Cu links to predominate. Contrary to expectation, aurophilic bonding does not appear to be the controlling factor which leads to (Cu1/2Au1/2)CN and (Ag1/2Au1/2)CN adopting the AuCN structure. The diffuse reflectance, photoluminescence, and 1-D negative thermal expansion (NTE) behaviors of all three systems are reported and compared with those of the parent cyanide compounds. The photophysical properties are strongly influenced both by the composition of the individual chains and by how such chains pack together. The NTE behavior is also controlled by structure type: the gold-containing mixed-metal cyanides with the AuCN structure show the smallest contraction along the chain length on heating.

A spectral view of nonlinear fluxes and stationary-transient interaction in the atmosphere

Nonlinear spectral transfers of kinetic energy and enstrophy, and stationary-transient interaction, are studied using global FGGE data for January 1979. It is found that the spectral transfers arise primarily from a combination, in roughly equal measure, of pure transient and mixed stationary-transient interactions. The pure transient interactions are associated with a transient eddy field which is approximately locally homogeneous and isotropic, and they appear to be consistently understood within the context of two-dimensional homogeneous turbulence. Theory based on spatial wale separation concepts suggests that the mixed interactions may be understood physically, to a first approximation, as a process of shear-induced spectral transfer of transient enstrophy along lines of constant zonal wavenumber. This essentially conservative enstrophy transfer generally involves highly nonlocal stationary-transient energy conversions. The observational analysis demonstrates that the shear-induced transient enstrophy transfer is mainly associated with intermediate-scale (zonal wavenumber m > 3) transients and is primarily to smaller (meridional) scales, so that the transient flow acts as a source of stationary energy. In quantitative terms, this transient-eddy rectification corresponds to a forcing timescale in the stationary energy budget which is of the same order of magnitude as most estimates of the damping timescale in simple stationary-wave models (5 to 15 days). Moreover, the nonlinear interactions involved are highly nonlocal and cover a wide range of transient scales of motion.

Bayesian nonlinear regression models with scale mixtures of skew-normal distributions: Estimation and case influence diagnostics

The purpose of this paper is to develop a Bayesian analysis for nonlinear regression models under scale mixtures of skew-normal distributions. This novel class of models provides a useful generalization of the symmetrical nonlinear regression models since the error distributions cover both skewness and heavy-tailed distributions such as the skew-t, skew-slash and the skew-contaminated normal distributions. The main advantage of these class of distributions is that they have a nice hierarchical representation that allows the implementation of Markov chain Monte Carlo (MCMC) methods to simulate samples from the joint posterior distribution. In order to examine the robust aspects of this flexible class, against outlying and influential observations, we present a Bayesian case deletion influence diagnostics based on the Kullback-Leibler divergence. Further, some discussions on the model selection criteria are given. The newly developed procedures are illustrated considering two simulations study, and a real data previously analyzed under normal and skew-normal nonlinear regression models. (C) 2010 Elsevier B.V. All rights reserved.

Improved testing inference in mixed linear models

Mixed linear models are commonly used in repeated measures studies. They account for the dependence amongst observations obtained from the same experimental unit. Often, the number of observations is small, and it is thus important to use inference strategies that incorporate small sample corrections. In this paper, we develop modified versions of the likelihood ratio test for fixed effects inference in mixed linear models. In particular, we derive a Bartlett correction to such a test, and also to a test obtained from a modified profile likelihood function. Our results generalize those in [Zucker, D.M., Lieberman, O., Manor, O., 2000. Improved small sample inference in the mixed linear model: Bartlett correction and adjusted likelihood. Journal of the Royal Statistical Society B, 62,827-838] by allowing the parameter of interest to be vector-valued. Additionally, our Bartlett corrections allow for random effects nonlinear covariance matrix structure. We report simulation results which show that the proposed tests display superior finite sample behavior relative to the standard likelihood ratio test. An application is also presented and discussed. (C) 2008 Elsevier B.V. All rights reserved.