Closed loop stability of measure-driven impulsive control systems

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Fault identification in distribution lines using intelligent systems and statistical methods

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 distribution feeder have demonstrated that the developed techniques provide accurate results, identifying and classifying efficiently the several occurrences of faults observed in the feeder. © 2006 IEEE.

Voltage regulator modeling for the three-phase power flow in distribution networks

In this paper a three-phase power flow for electrical distribution systems considering different models of voltage regulators is presented. A voltage regulator (VR) is an equipment that maintains the voltage level in a predefined value in a distribution line in spite of the load variations within its nominal power. Three different types of connections are analyzed: 1) wye-connected regulators, 2) open delta-connected regulators and 3) closed delta-connected regulators. To calculate the power flow, the three-phase backward/forward sweep algorithm is used. The methodology is tested on the IEEE 34 bus distribution system. ©2008 IEEE.

A proposal for reliability evaluation of components on electric power distribution system integrating probabilistic models and fuzzy inference systems

The system reliability depends on the reliability of its components itself. Therefore, it is necessary a methodology capable of inferring the state of functionality of these components to establish reliable indices of quality. Allocation models for maintenance and protective devices, among others, have been used in order to improve the quality and availability of services on electric power distribution systems. This paper proposes a methodology for assessing the reliability of distribution system components in an integrated way, using probabilistic models and fuzzy inference systems to infer about the operation probability of each component. © 2012 IEEE.

Multi-objective analysis of impacts of distributed generation placement on the operational characteristics of networks for distribution system planning

Recent advances in energy technology generation and new directions in electricity regulation have made distributed generation (DG) more widespread, with consequent significant impacts on the operational characteristics of distribution networks. For this reason, new methods for identifying such impacts are needed, together with research and development of new tools and resources to maintain and facilitate continued expansion towards DG. This paper presents a study aimed at determining appropriate DG sites for distribution systems. The main considerations which determine DG sites are also presented, together with an account of the advantages gained from correct DG placement. The paper intends to define some quantitative and qualitative parameters evaluated by Digsilent (R), GARP3 (R) and DSA-GD software. A multi-objective approach based on the Bellman-Zadeh algorithm and fuzzy logic is used to determine appropriate DG sites. The study also aims to find acceptable DG locations both for distribution system feeders, as well as for nodes inside a given feeder. (C) 2010 Elsevier Ltd. All rights reserved.

Node-Depth Encoding and Multiobjective Evolutionary Algorithm Applied to Large-Scale Distribution System Reconfiguration

The power loss reduction in distribution systems (DSs) is a nonlinear and multiobjective problem. Service restoration in DSs is even computationally hard since it additionally requires a solution in real-time. Both DS problems are computationally complex. For large-scale networks, the usual problem formulation has thousands of constraint equations. The node-depth encoding (NDE) enables a modeling of DSs problems that eliminates several constraint equations from the usual formulation, making the problem solution simpler. On the other hand, a multiobjective evolutionary algorithm (EA) based on subpopulation tables adequately models several objectives and constraints, enabling a better exploration of the search space. The combination of the multiobjective EA with NDE (MEAN) results in the proposed approach for solving DSs problems for large-scale networks. Simulation results have shown the MEAN is able to find adequate restoration plans for a real DS with 3860 buses and 632 switches in a running time of 0.68 s. Moreover, the MEAN has shown a sublinear running time in function of the system size. Tests with networks ranging from 632 to 5166 switches indicate that the MEAN can find network configurations corresponding to a power loss reduction of 27.64% for very large networks requiring relatively low running time.

Real-Time Voltage Regulation in Power Distribution System Using Fuzzy Control

Two different fuzzy approaches to voltage control in electric power distribution systems are introduced in this paper. The real-time controller in each case would act on power transformers equipped with under-load tap changers. Learning systems are employed to turn the voltage-control relays into adaptive devices. The scope of this study has been limited to the power distribution substation, and the voltage measurements and control actions are carried out on the secondary bus. The capacity of fuzzy systems to handle approximate data, together with their unique ability to interpret qualitative information, make it possible to design voltage-control strategies that satisfy the requirements of the Brazilian regulatory bodies and the real concerns of the electric power distribution companies. Fuzzy control systems based on these two strategies have been implemented and the test results were highly satisfactory.

Hybrid Method to Assess Sensitive Process Interruption Costs Due to Faults in Electric Power Distribution Networks

This paper shows a new hybrid method for risk assessment regarding interruptions in sensitive processes due to faults in electric power distribution systems. This method determines indices related to long duration interruptions and short duration voltage variations (SDVV), such as voltage sags and swells in each customer supplied by the distribution network. Frequency of such occurrences and their impact on customer processes are determined for each bus and classified according to their corresponding magnitude and duration. The method is based on information regarding network configuration, system parameters and protective devices. It randomly generates a number of fault scenarios in order to assess risk areas regarding long duration interruptions and voltage sags and swells in an especially inventive way, including frequency of events according to their magnitude and duration. Based on sensitivity curves, the method determines frequency indices regarding disruption in customer processes that represent equipment malfunction and possible process interruptions due to voltage sags and swells. Such approach allows for the assessment of the annual costs associated with each one of the evaluated power quality indices.

Reconfiguration of distribution networks to minimize loss and disruption costs using genetic algorithms

In this paper a computational implementation of an evolutionary algorithm (EA) is shown in order to tackle the problem of reconfiguring radial distribution systems. The developed module considers power quality indices such as long duration interruptions and customer process disruptions due to voltage sags, by using the Monte Carlo simulation method. Power quality costs are modeled into the mathematical problem formulation, which are added to the cost of network losses. As for the EA codification proposed, a decimal representation is used. The EA operators, namely selection, recombination and mutation, which are considered for the reconfiguration algorithm, are herein analyzed. A number of selection procedures are analyzed, namely tournament, elitism and a mixed technique using both elitism and tournament. The recombination operator was developed by considering a chromosome structure representation that maps the network branches and system radiality, and another structure that takes into account the network topology and feasibility of network operation to exchange genetic material. The topologies regarding the initial population are randomly produced so as radial configurations are produced through the Prim and Kruskal algorithms that rapidly build minimum spanning trees. (C) 2009 Elsevier B.V. All rights reserved.

Practical and economic advantages of choice feeding systems for laying poultry

Poultry can be managed under different feeding systems, depending on the husbandry skills and the feed available. These systems include the following: (1) a complete dry feed offered as a mash ad libitum; (2) the same feed offered as pellets or crumbles ad libitum; (3) a complete feed with added whole grain; (4) a complete wet feed given once or twice a day; (5) a complete feed offered on a restricted basis; (6) choice feeding. Of all these, an interesting alternative to offering complete diets is choice feeding which can be applied on both a small or large commercial scale. Under choice feeding or free-choice feeding birds are usually offered a choice between three types of feedstuffs: (a) an energy source (e.g. maize, rice bran, sorghum or wheat); (b) a protein source (e.g. soyabean meal, meat meal, fish meal or coconut meal) plus vitamins and minerals and (c), in the case of laying hens, calcium in granular form (i.e. oyster-shell grit). This system differs from the modern commercial practice of offering a complete diet comprising energy and protein sources, ground and mixed together. Under the complete diet system, birds are mainly only able to exercise their appetite for energy. When the environmental temperature varies, the birds either over- or under-consume protein and calcium. The basic principle behind practising choice feeding with laying hens is that individual hens are able to select from the various feed ingredients on offer and compose their own diet, according to their actual needs and production capacity. A choice-feeding system is of particular importance to small poultry producers in developing countries, such as Indonesia, because it can substantially reduce the cost of feed. The system is flexible and can be constructed in such a way that the various needs of a flock of different breeds, including village chickens, under different climates can be met. The system also offers a more effective way to use home-produced grain, such as maize, and by-products, such as rice bran, in developing countries. Because oyster-shell grit is readily available in developing countries at lower cost than limestone, the use of cheaper oyster-shell grit can further benefit small-holders in these countries. These benefits apart, simpler equipment suffices when designing and building a feed mixer on the farm, and transport costs are lower. If whole (unground) grain is used, the intake of which is accompanied by increased efficiency of feed utilisation, the costs of grinding, mixing and many of the handling procedures associated with mash and pellet preparation are eliminated. The choice feedstuffs can all be offered in the current feed distribution systems, either by mixing the ingredients first or by using a bulk bin divided into three compartments.

Optimization techniques for power distribution planning with uncertainties: a comparative study

Important research effort has been devoted to the topic of optimal planning of distribution systems. The non linear nature of the system, the need to consider a large number of scenarios and the increasing necessity to deal with uncertainties make optimal planning in distribution systems a difficult task. Heuristic techniques approaches have been proposed to deal with these issues, overcoming some of the inherent difficulties of classic methodologies. This paper considers several methodologies used to address planning problems of electrical power distribution networks, namely mixedinteger linear programming (MILP), ant colony algorithms (AC), genetic algorithms (GA), tabu search (TS), branch exchange (BE), simulated annealing (SA) and the Bender´s decomposition deterministic non-linear optimization technique (BD). Adequacy of theses techniques to deal with uncertainties is discussed. The behaviour of each optimization technique is compared from the point of view of the obtained solution and of the methodology performance. The paper presents results of the application of these optimization techniques to a real case of a 10-kV electrical distribution system with 201 nodes that feeds an urban area.

Distribution system operation supported by contextual energy resource management based on intelligent SCADA

Future distribution systems will have to deal with an intensive penetration of distributed energy resources ensuring reliable and secure operation according to the smart grid paradigm. SCADA (Supervisory Control and Data Acquisition) is an essential infrastructure for this evolution. This paper proposes a new conceptual design of an intelligent SCADA with a decentralized, flexible, and intelligent approach, adaptive to the context (context awareness). This SCADA model is used to support the energy resource management undertaken by a distribution network operator (DNO). Resource management considers all the involved costs, power flows, and electricity prices, allowing the use of network reconfiguration and load curtailment. Locational Marginal Prices (LMP) are evaluated and used in specific situations to apply Demand Response (DR) programs on a global or a local basis. The paper includes a case study using a 114 bus distribution network and load demand based on real data.

Design of future distribution grids

Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores

Filamentous fungi in free water and biofilms from Brazilian drinking water systems

In some regions of Brazil, especially where the water is scarce, drinking water is stored in water storage tanks. This practice gives the consumer the guarantee of available water. The water storage conditions such as the exposure to hot weather when the tanks are on rooftops allow the development of microorganisms and microbial biofilms which can deteriorate the water quality and increase the risk to human health [1,2]. This study describes the filamentous fungi (FF) detected in free water and biofilms in drinking water storage tanks in Recife - Pernambuco, Brazil. Five sampling times in triplicate were performed at two distinct points. Colony-forming units (CFU) of FF fungi were determined with 0.45 µm filtration membranes using peptone glucose rose Bengal agar (PGRBA). From the 30 samples analysed a total of 1136 CFU were obtained. The water biofilms were collected from samplers consisting of polyethylene coupons, previously installed in the reservoirs. These coupons were transferred to PGRBA plates and incubated using with the same conditions described for free FF. For the in situ detection of FF in biofilms the Calcofluor White staining technique was used. This procedure demonstrated FF forming biofilms on the surfaces of the coupons. Brazilian legislation does not define limits for FF in drinking water. However considering the potential risk of fungal contamination, the data obtained in this study will contribute to developing future quantitative and qualitative parameters for the presence of fungi in drinking water distribution systems in Brazil. [1] HageskaL, G, Lima, N, Skaar, I. The study of fungi in drinking water. Mycological Research, 113, 2009, 165-172. [2] Skaar I, Hageskal G. Fungi in Drinking Water. In.: Paterson RRM, Lima N. (Eds.) Molecular Biology of Food and Water Borne Mycotoxigenic and Mycotic Fungi. CRC Press, Taylor & Francis Group, Boca Raton, 2015, 597-606.

Robust power allocation algorithms for MIMO OFDM systems with imperfect CSI

This paper presents a Bayesian approach to the design of transmit prefiltering matrices in closed-loop schemes robust to channel estimation errors. The algorithms are derived for a multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) system. Two different optimizationcriteria are analyzed: the minimization of the mean square error and the minimization of the bit error rate. In both cases, the transmitter design is based on the singular value decomposition (SVD) of the conditional mean of the channel response, given the channel estimate. The performance of the proposed algorithms is analyzed,and their relationship with existing algorithms is indicated. As withother previously proposed solutions, the minimum bit error rate algorithmconverges to the open-loop transmission scheme for very poor CSI estimates.