Application for fault location in electrical power distribution systems

Fault location has been studied deeply for transmission lines due to its importance in power systems. Nowadays the problem of fault location on distribution systems is receiving special attention mainly because of the power quality regulations. In this context, this paper presents an application software developed in Matlabtrade that automatically calculates the location of a fault in a distribution power system, starting from voltages and currents measured at the line terminal and the model of the distribution power system data. The application is based on a N-ary tree structure, which is suitable to be used in this application due to the highly branched and the non- homogeneity nature of the distribution systems, and has been developed for single-phase, two-phase, two-phase-to-ground, and three-phase faults. The implemented application is tested by using fault data in a real electrical distribution power system

Estimation of zero-sequence impedance of undergrounds cables for single-phase fault location in distribution systems with electric arc

This paper focus on the problem of locating single-phase faults in mixed distribution electric systems, with overhead lines and underground cables, using voltage and current measurements at the sending-end and sequence model of the network. Since calculating series impedance for underground cables is not as simple as in the case of overhead lines, the paper proposes a methodology to obtain an estimation of zero-sequence impedance of underground cables starting from previous single-faults occurred in the system, in which an electric arc occurred at the fault location. For this reason, the signal is previously pretreated to eliminate its peaks voltage and the analysis can be done working with a signal as close as a sinus wave as possible

Moderating effects of management control systems and innovation on performance. Simple methods for correcting the effects of measurement error for interaction effects in small samples

In the accounting literature, interaction or moderating effects are usually assessed by means of OLS regression and summated rating scales are constructed to reduce measurement error bias. Structural equation models and two-stage least squares regression could be used to completely eliminate this bias, but large samples are needed. Partial Least Squares are appropriate for small samples but do not correct measurement error bias. In this article, disattenuated regression is discussed as a small sample alternative and is illustrated on data of Bisbe and Otley (in press) that examine the interaction effect of innovation and style of use of budgets on performance. Sizeable differences emerge between OLS and disattenuated regression

Interacting software-agents to support a kind of expert supervision systems

Expert supervision systems are software applications specially designed to automate process monitoring. The goal is to reduce the dependency on human operators to assure the correct operation of a process including faulty situations. Construction of this kind of application involves an important task of design and development in order to represent and to manipulate process data and behaviour at different degrees of abstraction for interfacing with data acquisition systems connected to the process. This is an open problem that becomes more complex with the number of variables, parameters and relations to account for the complexity of the process. Multiple specialised modules tuned to solve simpler tasks that operate under a co-ordination provide a solution. A modular architecture based on concepts of software agents, taking advantage of the integration of diverse knowledge-based techniques, is proposed for this purpose. The components (software agents, communication mechanisms and perception/action mechanisms) are based on ICa (Intelligent Control architecture), software middleware supporting the build-up of applications with software agent features

Fault diagnosis by refining the parameter uncertainty space of nonlinear dynamic systems

This paper deals with fault detection and isolation problems for nonlinear dynamic systems. Both problems are stated as constraint satisfaction problems (CSP) and solved using consistency techniques. The main contribution is the isolation method based on consistency techniques and uncertainty space refining of interval parameters. The major advantage of this method is that the isolation speed is fast even taking into account uncertainty in parameters, measurements, and model errors. Interval calculations bring independence from the assumption of monotony considered by several approaches for fault isolation which are based on observers. An application to a well known alcoholic fermentation process model is presented

Nuclear relaxation contribution to static and dynamic (infinite frequency approximation) nonlinear optical properties by means of electrical property expansions: Application to HF, CH4, CF4, and SF6

Electrical property derivative expressions are presented for the nuclear relaxation contribution to static and dynamic (infinite frequency approximation) nonlinear optical properties. For CF4 and SF6, as opposed to HF and CH4, a term that is quadratic in the vibrational anharmonicity (and not previously evaluated for any molecule) makes an important contribution to the static second vibrational hyperpolarizability of CF4 and SF6. A comparison between calculated and experimental values for the difference between the (anisotropic) Kerr effect and electric field induced second-harmonic generation shows that, at the Hartree-Fock level, the nuclear relaxation/infinite frequency approximation gives the correct trend (in the series CH4, CF4, SF6) but is of the order of 50% too small

A proposal for the diagnosis of uncertain dynamic systems based on interval models

The performance of a model-based diagnosis system could be affected by several uncertainty sources, such as,model errors,uncertainty in measurements, and disturbances. This uncertainty can be handled by mean of interval models.The aim of this thesis is to propose a methodology for fault detection, isolation and identification based on interval models. The methodology includes some algorithms to obtain in an automatic way the symbolic expression of the residual generators enhancing the structural isolability of the faults, in order to design the fault detection tests. These algorithms are based on the structural model of the system. The stages of fault detection, isolation, and identification are stated as constraint satisfaction problems in continuous domains and solved by means of interval based consistency techniques. The qualitative fault isolation is enhanced by a reasoning in which the signs of the symptoms are derived from analytical redundancy relations or bond graph models of the system. An initial and empirical analysis regarding the differences between interval-based and statistical-based techniques is presented in this thesis. The performance and efficiency of the contributions are illustrated through several application examples, covering different levels of complexity.

Integrated management of urban wastewater systems: a model-based approach

The main objective pursued in this thesis targets the development and systematization of a methodology that allows addressing management problems in the dynamic operation of Urban Wastewater Systems. The proposed methodology will suggest operational strategies that can improve the overall performance of the system under certain problematic situations through a model-based approach. The proposed methodology has three main steps: The first step includes the characterization and modeling of the case-study, the definition of scenarios, the evaluation criteria and the operational settings that can be manipulated to improve the system’s performance. In the second step, Monte Carlo simulations are launched to evaluate how the system performs for a wide range of operational settings combinations, and a global sensitivity analysis is conducted to rank the most influential operational settings. Finally, the third step consists on a screening methodology applying a multi-criteria analysis to select the best combinations of operational settings.

Improvement of strategies for the management of fire blight (Erwinia amylovora). Evaluation and optimization of physical and chemical control methods, and use of decision support systems

El foc bacterià és una malaltia que afecta a plantes de la família de la rosàcies, causada pel bacteri Erwinia amylovora. El seu rang d'hostes inclou arbres fruiters, com la perera, la pomera o el codonyer, i plantes ornamentals de gran interès comercial i econòmic. Actualment, la malaltia s'ha dispersat i es troba àmpliament distribuïda en totes les zones de clima temperat del món. A Espanya, on la malaltia no és endèmica, el foc bacterià es va detectar per primer cop al 1995 al nord del país (Euskadi) i posteriorment, han aparegut varis focus en altres localitzacions, que han estat convenientment eradicats. El control del foc bacterià, és molt poc efectiu en plantes afectades per la malaltia, de manera que es basa en mesures encaminades a evitar la dispersió del patogen, i la introducció de la malaltia en regions no endèmiques. En aquest treball, la termoteràpia ha estat avaluada com a mètode d'eradicació d'E. amylovora de material vegetal de propagació asimptomàtic. S'ha demostrat que la termoteràpia és un mètode viable d'eradicar E. amylovora de material de propagació. Gairebé totes les espècies i varietats de rosàcies mantingudes en condicions d'humitat sobrevivien 7 hores a 45 ºC i més de 3 hores a 50 ºC, mentre que més d'1 hora d'exposició a 50 ºC amb calor seca produïa danys en el material vegetal i reduïa la brotació. Tractaments de 60 min a 45 ºC o 30 min a 50 ºC van ser suficients per reduir la població epífita d'E. amylovora a nivells no detectables (5 x 102 ufc g-1 p.f.) en branques de perera. Els derivats dels fosfonats i el benzotiadiazol són efectius en el control del foc bacterià en perera i pomera, tant en condicions de laboratori, com d'hivernacle i camp. Els inductors de defensa de les plantes redueixen els nivells de malaltia fins al 40-60%. Els intervals de temps mínims per aconseguir el millor control de la malaltia van ser 5 dies pel fosetil-Al, i 7 dies per l'etefon i el benzotiadiazol, i les dosis òptimes pel fosetil-Al i el benzotiadiazol van ser 3.72 g HPO32- L-1 i 150 mg i.a. L-1, respectivament. Es millora l'eficàcia del fosetil-Al i del benzotiadiazol en el control del foc bacterià, quan es combinen amb els antibiòtics a la meitat de la dosi d'aquests últims. Tot i que l'estratègia de barrejar productes és més pràctica i fàcil de dur a terme a camp, que l'estratègia de combinar productes, el millor nivell de control de la malaltia s'aconsegueix amb l'estratègia de combinar productes. Es va analitzar a nivell histològic i ultrastructural l'efecte del benzotiadiazol i dels fosfonats en la interacció Erwinia amylovora-perera. Ni el benzotiadiazol, ni el fosetil-Al, ni l'etefon van induir canvis estructurals en els teixits de perera 7 dies després de la seva aplicació. No obstant, després de la inoculació d'E. amylovora es va observar en plantes tractades amb fosetil-Al i etefon una desorganització estructural cel·lular, mentre que en les plantes tractades amb benzotiadiazol aquestes alteracions tissulars van ser retardades. S'han avaluat dos models (Maryblyt, Cougarblight) en un camp a Espanya afectat per la malaltia, per determinar la precisió de les prediccions. Es van utilitzar dos models per elaborar el mapa de risc, el BRS-Powell combinat i el BIS95 modificat. Els resultats van mostrar dos zones amb elevat i baix risc de la malaltia. Maryblyt i Cougarblight són dos models de fàcil ús, tot i que la seva implementació en programes de maneig de la malaltia requereix que siguin avaluats i validats per un període de temps més llarg i en àrees on la malaltia hi estigui present.