Efficient Placement of Fault Indicators in an Actual Distribution System Using Evolutionary Computing

This paper proposes an evolutionary computing strategy to solve the problem of fault indicator (FI) placement in primary distribution feeders. More specifically, a genetic algorithm (GA) is employed to search for an efficient configuration of FIs, located at the best positions on the main feeder of a real-life distribution system. Thus, the problem is modeled as one of optimization, aimed at improving the distribution reliability indices, while, at the same time, finding the least expensive solution. Based on actual data, the results confirm the efficiency of the GA approach to the FI placement problem.

Inconsistent-tolerant base revision through Argument Theory Change

Reasoning and change over inconsistent knowledge bases (KBs) is of utmost relevance in areas like medicine and law. Argumentation may bring the possibility to cope with both problems. Firstly, by constructing an argumentation framework (AF) from the inconsistent KB, we can decide whether to accept or reject a certain claim through the interplay among arguments and counterarguments. Secondly, by handling dynamics of arguments of the AF, we might deal with the dynamics of knowledge of the underlying inconsistent KB. Dynamics of arguments has recently attracted attention and although some approaches have been proposed, a full axiomatization within the theory of belief revision was still missing. A revision arises when we want the argumentation semantics to accept an argument. Argument Theory Change (ATC) encloses the revision operators that modify the AF by analyzing dialectical trees-arguments as nodes and attacks as edges-as the adopted argumentation semantics. In this article, we present a simple approach to ATC based on propositional KBs. This allows to manage change of inconsistent KBs by relying upon classical belief revision, although contrary to it, consistency restoration of the KB is avoided. Subsequently, a set of rationality postulates adapted to argumentation is given, and finally, the proposed model of change is related to the postulates through the corresponding representation theorem. Though we focus on propositional logic, the results can be easily extended to more expressive formalisms such as first-order logic and description logics, to handle evolution of ontologies.

Coffee is highly tolerant to cadmium, nickel and zinc: Plant and soil nutritional status, metal distribution and bean yield

Sewage sludge has been used to fertilize coffee, increasing the risk of metal contamination in this crop. The aim of this work was to study the effects of Cd, Zn and Ni in adult coffee plants growing under field conditions. Seven-year-old coffee plants growing in the field received one of three;loses of Cd, Zn or Ni: 15,45 and 90 g Cd plant(-1); 35, 105 and 210 g Ni plant(-1); and 100, 300 and 600 g Zn plant(-1), with all three metals in the form of sulphate salts. After three months, we noticed good penetration of the three metals into the soil, especially in the first 50 cm, which is the region where most coffee plant roots are concentrated. Leaf concentrations of K, Ca, Mg, S, B, Cu, Fe and Mn were nor affected. N levels did not change with the application of Ni or Zn but were reduced with either 45 or 90 g Cd plant(-1). Foliar P concentrations decreased with the addition of 45 and 90 g Cd plant(-1) and 600 g Zn plant(-1). Zn levels in leaves were not affected by the application of Cd or Ni. The highest concentrations. of Zn were found in branches (30-230 mg kg(-1)), leaves (7-35 mg kg(-1)) and beam (4-6.5 mg kg(-1)); Ni was found in leaves (4-45 mg kg(-1)), branches (3-18 mg kg(-1)) and beans (1-5 mg kg(-1)); and Cd was found in branches (0-6.2 mg kg(-1)) and beans (0-1.5 mg kg(-1)) but was absent in leaves. The mean yield of two harvests was not affected by Ni, but it decreased at the highest dose of Zn (600 g plant(-1)) and the two higher doses of Cd (45 and 90 g plant(-1)). Plants died when treated with the highest dose of Cd and showed symptoms of toxicity with the highest dose of Zn. Nevertheless, based on the amounts of metal used and the results obtained, we conclude that coffee plants are highly tolerant to the three metals tested. Moreover, even at high doses, there was very little transport to the beans, which is the part consumed by humans. (C) 2011 Elsevier B.V. All rights reserved.

EFFICIENT FAULT LOCATION IN UNDERGROUND DISTRIBUTION SYSTEMS THROUGH OPTIMUM-PATH FOREST

In this article we propose an efficient and accurate method for fault location in underground distribution systems by means of an Optimum-Path Forest (OPF) classifier. We applied the time domains reflectometry method for signal acquisition, which was further analyzed by OPF and several other well-known pattern recognition techniques. The results indicated that OPF and support vector machines outperformed artificial neural networks and a Bayesian classifier, but OPF was much more efficient than all classifiers for training, and the second fastest for classification.

Multi-objective evolutionary algorithm for single and multiple fault service restoration in large-scale distribution systems

Network reconfiguration for service restoration (SR) in distribution systems is a complex optimization problem. For large-scale distribution systems, it is computationally hard to find adequate SR plans in real time since the problem is combinatorial and non-linear, involving several constraints and objectives. Two Multi-Objective Evolutionary Algorithms that use Node-Depth Encoding (NDE) have proved able to efficiently generate adequate SR plans for large distribution systems: (i) one of them is the hybridization of the Non-Dominated Sorting Genetic Algorithm-II (NSGA-II) with NDE, named NSGA-N; (ii) the other is a Multi-Objective Evolutionary Algorithm based on subpopulation tables that uses NDE, named MEAN. Further challenges are faced now, i.e. the design of SR plans for larger systems as good as those for relatively smaller ones and for multiple faults as good as those for one fault (single fault). In order to tackle both challenges, this paper proposes a method that results from the combination of NSGA-N, MEAN and a new heuristic. Such a heuristic focuses on the application of NDE operators to alarming network zones according to technical constraints. The method generates similar quality SR plans in distribution systems of significantly different sizes (from 3860 to 30,880 buses). Moreover, the number of switching operations required to implement the SR plans generated by the proposed method increases in a moderate way with the number of faults.