Controle inteligente de pressão para uma rede sem reservatório de abastecimento urbano de água

The sanitation companies from Brazil has a great challenge for the XXI century: seek to mitigate the rate of physical waste (water, chemicals and electricity) and financial waste caused by inefficient operating systems drinking water supply, considering that currently we already face, in some cases, the scarcity of water resources. The supply systems are increasingly complex as they seek to minimize waste and at the same time better serve the growing number of users. However, this technological change is to reduce the complexity of the challenges posed by the need to include users with higher quality and efficiency in services. A major challenge for companies of water supplies is to provide a good quality service contemplating reducing expenditure on electricity. In this situation we developed a research by a method that seeks to control the pressure of the distribution systems that do not have the tank in your setup and the water comes out of the well directly to the distribution system. The method of pressure control (intelligent control) uses fuzzy logic to eliminate the waste of electricity and the leaks from the production of pumps that inject directly into the distribution system, which causes waste of energy when the consumption of households is reduced causing the saturation of the distribution system. This study was conducted at Green Club II condominium, located in the city of Parnamirim, state of Rio Grande do Norte, in order to study the pressure behavior of the output of the pump that injects water directly into the distribution system. The study was only possible because of the need we had to find a solution to some leaks in the existing distribution system and the extensions of the respective condominium residences, which sparked interest in developing a job in order to carry out the experiments contained in this research

A novel approach to robust parameter estimation using neurofuzzy systems

A novel approach for solving robust parameter estimation problems is presented for processes with unknown-but-bounded errors and uncertainties. An artificial neural network is developed to calculate a membership set for model parameters. Techniques of fuzzy logic control lead the network to its equilibrium points. Simulated examples are presented as an illustration of the proposed technique. The result represent a significant improvement over previously proposed methods. (C) 1999 IMACS/Elsevier B.V. B.V. All rights reserved.

Electrical load forecasting formulation by a fast neural network

The objective of this work is to develop a methodology for electric load forecasting based on a neural network. Here, backpropagation algorithm is used with an adaptive process that based on fuzzy logic and using a decaying exponential function to avoid instability in the convergence process. This methodology results in fast training, when compared to the conventional formulation of backpropagation algorithm. The results are presented using data from a Brazilian Electric Company, and shows a very good performance for the proposal objective.

Aplicação preliminar do método QRAM para avaliação de riscos para segurança ocupacional na construção civil

A segurança ocupacional é imprescindível na indústria da construção civil e a análise e avaliação de riscos para a segurança ocupacional (AARSO) é o primeiro e fundamental passo para alcançá-la, baseado na definição e implementação de programas de prevenção. A AARSO é um processo complexo, que implica a consideração e análise de muitos parâmetros quantitativos e/ou qualitativos que são difíceis de quantificar. As metodologias AARSO utilizadas na indústria da construção civil são baseadas em informação sujeita a incerteza (sendo tratada por técnicas probabilísticas e/ou estatísticas), difusa, imprecisa e/ou incompleta. Isso implica algumas limitações, como, por exemplo, obrigar os analistas a estimar parâmetros ou efetuar comparações com outros canteiros de obras (o que afasta do sistema real em estudo). O objetivo inicial deste estudo foi efetuar a pré-validação de um método AARSO, o QRAM, em duas cidades brasileiras, de médio e grande porte.

Paraconsistent Autonomous Mobile Robot Emmy III

This work presents some improvements regarding to the autonomous mobile robot Emmy based on Paraconsistent Annotated Evidential Logic ET. A discussion on navigation system is presented.

Control automatico de un sistema electrico mediante logica difusa

Substitution of fuzzy logic control in an electrical system normally controlled by proportional-integral frequency was studied and analyzed. A linear model of an electrical system, the concepts which govern the theory of fuzzy logic, and the application of this theory to systems control, are briefly presented. The methodology of fuzzy logic was then applied to develop a model for an electrical energy system. The results of the simulation demonstrated that fuzzy logic control eliminated the area frequency error and permitted that only the area experiencing an increase in charge responds to this variation. Based on the results, it is concluded that control based on fuzzy logic is simple, is easy to maintain, is of low cost, and can be used to substitute traditional velocity controllers.

A fast electric load forecasting using neural networks

The objective of this work is the development of a methodology for electric load forecasting based on a neural network. Here, it is used Backpropagation algorithm with an adaptive process based on fuzzy logic. This methodology results in fast training, when compared to the conventional formulation of Backpropagation algorithm. Results are presented using data from a Brazilian Electric Company and the performance is very good for the proposal objective.

Using artificial intelligence for the control of medium voltage substations

This paper introduces a method for the supervision and control of devices in electric substations using fuzzy logic and artificial neural networks. An automatic knowledge acquisition process is included which allows the on-line processing of operator actions and the extraction of control rules to replace gradually the human operator. Some experimental results obtained by the application of the implemented software in a simulated environment with random signal generators are presented.

Chaos induced by turbulent and erratic functions

Let (X, d) be a compact metric space and f: X → X a continuous function and consider the hyperspace (K(X), H) of all nonempty compact subsets of X endowed with the Hausdorff metric induced by d. Let f̄: K(X) → K (X) be defined by f̄(A) = {f(a)/a ∈ A} the natural extension of f to K(X), then the aim of this work is to study the dynamics of f when f is turbulent (erratic, respectively) and its relationships.

Pricing of reactive power support provided by distributed generators in transmission systems

Distributed Generation, microgrid technologies, two-way communication systems, and demand response programs are issues that are being studied in recent years within the concept of smart grids. At some level of enough penetration, the Distributed Generators (DGs) can provide benefits for sub-transmission and transmission systems through the so-called ancillary services. This work is focused on the ancillary service of reactive power support provided by DGs, specifically Wind Turbine Generators (WTGs), with high level of impact on transmission systems. The main objective of this work is to propose an optimization methodology to price this service by determining the costs in which a DG incurs when it loses sales opportunity of active power, i.e, by determining the Loss of Opportunity Costs (LOC). LOC occur when more reactive power is required than available, and the active power generation has to be reduced in order to increase the reactive power capacity. In the optimization process, three objectives are considered: active power generation costs of DGs, voltage stability margin of the system, and losses in the lines of the network. Uncertainties of WTGs are reduced solving multi-objective optimal power flows in multiple probabilistic scenarios constructed by Monte Carlo simulations, and modeling the time series associated with the active power generation of each WTG via Fuzzy Logic and Markov Chains. The proposed methodology was tested using the IEEE 14 bus test system with two WTGs installed. © 2011 IEEE.

Short-term planning of electric power distribution networks using multiobjective genetic algorithim

The high active and reactive power level demanded by the distribution systems, the growth of consuming centers, and the long lines of the distribution systems result in voltage variations in the busses compromising the quality of energy supplied. To ensure the energy quality supplied in the distribution system short-term planning, some devices and actions are used to implement an effective control of voltage, reactive power, and power factor of the network. Among these devices and actions are the voltage regulators (VRs) and capacitor banks (CBs), as well as exchanging the conductors sizes of distribution lines. This paper presents a methodology based on the Non-Dominated Sorting Genetic Algorithm (NSGA-II) for optimized allocation of VRs, CBs, and exchange of conductors in radial distribution systems. The Multiobjective Genetic Algorithm (MGA) is aided by an inference process developed using fuzzy logic, which applies specialized knowledge to achieve the reduction of the search space for the allocation of CBs and VRs.

Implementation of an AC model for transmission expansion planning considering reliability constraints

In this paper, a hybrid heuristic methodology that employs fuzzy logic for solving the AC transmission network expansion planning (AC-TEP) problem is presented. An enhanced constructive heuristic algorithm aimed at obtaining a significant quality solution for such complicated problems considering contingency is proposed. In order to indicate the severity of the contingency, 2 performance indices, namely the line flow performance index and voltage performance index, are calculated. An interior point method is applied as a nonlinear programming solver to handle such nonconvex optimization problems, while the objective function includes the costs of the new transmission lines as well as the real power losses. The performance of the proposed method is examined by applying it to the well-known Garver system for different cases. The simulation studies and result analysis demonstrate that the proposed method provides a promising way to find an optimal plan. Obtaining the best quality solution shows the capability and the viability of the proposed algorithm in AC-TEP. © Tübi̇tak..

Cellular automata-based spatial dynamic modeling for analyzing urban land use change

This paper analyzes land use change in Rio Claro City and its surroundings, located in the southeastern state of Sao Paulo, in the period from 1988 to 1995, using air-borne digital imagery and a cellular automata model. The simulation experiment was carried out in the Dinamica EGO platform and the results revealed a constrained urban sprawl, resulting from both the densification of residential areas implemented in previous years and the economic recession that led to an internal financial crisis in Brazil during the early 1990s. The simulation outputs were validated using a multi-resolution procedure based on a fuzzy similarity index and showed a satisfactory fitness in relation to the historical reference data. © 2013 IEEE.

Construção,modelagem e controle de um pêndulo invertido com CLP e software scada

Pós-graduação em Engenharia Elétrica - FEIS

Sistema inteligente híbrido intercomunicativo para detecção de perdas comerciais

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)