Electric consumption in SHSs in rural communities of brazil and Peru and recommendations for sizing

The lack of data records of electric power consumption of smallphotovoltaic home systems, independently of the method used for sizing them, drives to consider the demand as a constant. However, the existing data reveal the variability of the consumption due to the influences of some social, cultural and psychosocial aspects of the human groups. This paper presents records of consumption data obtainedfrom several solar home systems (SHSs) in Brazil and Peru, and it discusses about the Gamma distribution function that can express to a great extent the behaviour of the demand. By this analysis it was verified that `a lot of people consume little and few people consume a lot`. In that sense, a few recommendations for sizing procedures that can be useful in the implantation of extensive programmes of rural electrification by SHSs are presented. Copyright (c) 2007 John Wiley & Sons, Ltd.

Optimal reactive power flow via the modified barrier Lagrangian function approach

A new approach called the Modified Barrier Lagrangian Function (MBLF) to solve the Optimal Reactive Power Flow problem is presented. In this approach, the inequality constraints are treated by the Modified Barrier Function (MBF) method, which has a finite convergence property: i.e. the optimal solution in the MBF method can actually be in the bound of the feasible set. Hence, the inequality constraints can be precisely equal to zero. Another property of the MBF method is that the barrier parameter does not need to be driven to zero to attain the solution. Therefore, the conditioning of the involved Hessian matrix is greatly enhanced. In order to show this, a comparative analysis of the numeric conditioning of the Hessian matrix of the MBLF approach, by the decomposition in singular values, is carried out. The feasibility of the proposed approach is also demonstrated with comparative tests to Interior Point Method (IPM) using various IEEE test systems and two networks derived from Brazilian generation/transmission system. The results show that the MBLF method is computationally more attractive than the IPM in terms of speed, number of iterations and numerical conditioning. (C) 2011 Elsevier B.V. All rights reserved.

Algebraic-graph method for identification of islanding in power system grids

In this paper, a new algebraic-graph method for identification of islanding in power system grids is proposed. The proposed method identifies all the possible cases of islanding, due to the loss of a equipment, by means of a factorization of the bus-branch incidence matrix. The main features of this new method include: (i) simple implementation, (ii) high speed, (iii) real-time adaptability, (iv) identification of all islanding cases and (v) identification of the buses that compose each island in case of island formation. The method was successfully tested on large-scale systems such as the reduced south Brazilian system (45 buses/72 branches) and the south-southeast Brazilian system (810 buses/1340 branches). (C) 2011 Elsevier Ltd. All rights reserved.

A modified Primal-Dual Logarithmic-Barrier Method for solving the Optimal Power Flow problem with discrete and continuous control variables

The aim of solving the Optimal Power Flow problem is to determine the optimal state of an electric power transmission system, that is, the voltage magnitude and phase angles and the tap ratios of the transformers that optimize the performance of a given system, while satisfying its physical and operating constraints. The Optimal Power Flow problem is modeled as a large-scale mixed-discrete nonlinear programming problem. This paper proposes a method for handling the discrete variables of the Optimal Power Flow problem. A penalty function is presented. Due to the inclusion of the penalty function into the objective function, a sequence of nonlinear programming problems with only continuous variables is obtained and the solutions of these problems converge to a solution of the mixed problem. The obtained nonlinear programming problems are solved by a Primal-Dual Logarithmic-Barrier Method. Numerical tests using the IEEE 14, 30, 118 and 300-Bus test systems indicate that the method is efficient. (C) 2012 Elsevier B.V. All rights reserved.

Influence of pattern gradation on the design of piezocomposite energy harvesting devices using topology optimization

Piezoelectric materials can be used to convert oscillatory mechanical energy into electrical energy. Energy harvesting devices are designed to capture the ambient energy surrounding the electronics and convert it into usable electrical energy. The design of energy harvesting devices is not obvious, requiring optimization procedures. This paper investigates the influence of pattern gradation using topology optimization on the design of piezocomposite energy harvesting devices based on bending behavior. The objective function consists of maximizing the electric power generated in a load resistor. A projection scheme is employed to compute the element densities from design variables and control the length scale of the material density. Examples of two-dimensional piezocomposite energy harvesting devices are presented and discussed using the proposed method. The numerical results illustrate that pattern gradation constraints help to increase the electric power generated in a load resistor and guides the problem toward a more stable solution. (C) 2012 Elsevier Ltd. All rights reserved.

BRAZILIAN MOSQUITO (DIPTERA: CULICIDAE) FAUNA. I. Anopheles SPECIES FROM PORTO VELHO, RONDONIA STATE, WESTERN AMAZON, BRAZIL

This study contributes to knowledge of Anopheles species, including vectors of Plasmodium from the western Brazilian Amazon in Porto Velho, Rondonia State. The sampling area has undergone substantial environmental changes as a consequence of agricultural and hydroelectric projects, which have caused intensive deforestation and favored habitats for some mosquito species. The purpose of this study was to diagnose the occurrence of anopheline species from collections in three locations along an electric-power transmission line. Each locality was sampled three times from 2010 to 2011. The principal adult mosquitoes captured in Shannon trap were Anopheles darlingi, An. triannulatus, An. nuneztovari l.s., An. gilesi and An. costai. In addition, larvae were collected in ground breeding sites for Anopheles braziliensis, An. triannulatus, An. darlingi, An. deaneorum, An. marajoara, An. peryassui, An. nuneztovari l.s. and An. oswaldoi-konderi. Anopheles darlingi was the most common mosquito in the region. We discuss Culicidae systematics, fauna distribution, and aspects of malaria in altered habitats of the western Amazon.

Brazilian mosquito (Diptera: Culicidae) fauna: I. Anopheles species from Porto Velho, Rondônia state, western Amazon, Brazil

This study contributes to knowledge of Anopheles species, including vectors of Plasmodium from the western Brazilian Amazon in Porto Velho, Rondônia State. The sampling area has undergone substantial environmental changes as a consequence of agricultural and hydroelectric projects, which have caused intensive deforestation and favored habitats for some mosquito species. The purpose of this study was to diagnose the occurrence of anopheline species from collections in three locations along an electric-power transmission line. Each locality was sampled three times from 2010 to 2011. The principal adult mosquitoes captured in Shannon trap were Anopheles darlingi, An. triannulatus, An. nuneztovari l.s., An.gilesi and An. costai. In addition, larvae were collected in ground breeding sites for Anopheles braziliensis, An. triannulatus, An. darlingi, An. deaneorum, An. marajoara, An. peryassui, An. nuneztovari l.s. and An. oswaldoi-konderi. Anopheles darlingi was the most common mosquito in the region. We discuss Culicidae systematics, fauna distribution, and aspects of malaria in altered habitats of the western Amazon.

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.

Programmable logic design of a compact Genetic Algorithm for phasor estimation in real-time

The main objective of this work is to present an efficient method for phasor estimation based on a compact Genetic Algorithm (cGA) implemented in Field Programmable Gate Array (FPGA). To validate the proposed method, an Electrical Power System (EPS) simulated by the Alternative Transients Program (ATP) provides data to be used by the cGA. This data is as close as possible to the actual data provided by the EPS. Real life situations such as islanding, sudden load increase and permanent faults were considered. The implementation aims to take advantage of the inherent parallelism in Genetic Algorithms in a compact and optimized way, making them an attractive option for practical applications in real-time estimations concerning Phasor Measurement Units (PMUs).