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.

Memory effect and fast spinodal decomposition

We consider the modification of the Cahn-Hilliard equation when a time delay process through a memory function is taken into account. We then study the process of spinodal decomposition in fast phase transitions associated with a conserved order parameter. The introduced memory effect plays an important role to obtain a finite group velocity. Then, we discuss the constraint for the parameters to satisfy causality. The memory effect is seen to affect the dynamics of phase transition at short times and have the effect of delaying, in a significant way, the process of rapid growth of the order parameter that follows a quench into the spinodal region.

Short term hydroelectric scheduling combining network flow and interior point approaches

In this paper, short term hydroelectric scheduling is formulated as a network flow optimization model and solved by interior point methods. The primal-dual and predictor-corrector versions of such interior point methods are developed and the resulting matrix structure is explored. This structure leads to very fast iterations since it avoids computation and factorization of impedance matrices. For each time interval, the linear algebra reduces to the solution of two linear systems, either to the number of buses or to the number of independent loops. Either matrix is invariant and can be factored off-line. As a consequence of such matrix manipulations, a linear system which changes at each iteration has to be solved, although its size is reduced to the number of generating units and is not a function of time intervals. These methods were applied to IEEE and Brazilian power systems, and numerical results were obtained using a MATLAB implementation. Both interior point methods proved to be robust and achieved fast convergence for all instances tested. (C) 2004 Elsevier Ltd. All rights reserved.

Electrode poling of cellular polypropylene films with short high-voltage pulses

Recently, piezoelectric cellular polypropylene (PP) was proposed as a new type of quasi-ferroelectric. The observed hysteresis of the charge density as a function of the electric field could be explained as field-dependent charging inside the gas-filled voids. Interestingly enough, the measurable poling behavior of the macroscopic dipoles formed by charges that are trapped at the internal void surfaces is phenomenologically completely identical to the cooperative poling behavior of microscopic molecular dipoles in ferroelectric polymers. Therefore, it can be assumed that charge separation (or charge redistribution) and subsequent trapping in cellular PP is a rather fast switching process. In order to examine the poling dynamics, we developed an experimental setup for pulsed poling. High-voltage pulses with a duration of 45 μs (FWHM) were applied in direct contact to two-side metallized cellular PP films. The pulsed poling yields piezoelectricity in the cellular PP. We study and discuss the dependence of the resulting piezoelectricity on the poling field. We also characterize the charge separation during application of higher electric poling fields of up to -10 kV in direct contact to the two-side metallized films for longer times.

A fast electric load forecasting using adaptive neural networks

This work presents a procedure for electric load forecasting based on adaptive multilayer feedforward neural networks trained by the Backpropagation algorithm. The neural network architecture is formulated by two parameters, the scaling and translation of the postsynaptic functions at each node, and the use of the gradient-descendent method for the adjustment in an iterative way. Besides, the neural network also uses an adaptive process based on fuzzy logic to adjust the network training rate. This methodology provides an efficient modification of the neural network that results in faster convergence and more precise results, in comparison to the conventional formulation Backpropagation algorithm. The adapting of the training rate is effectuated using the information of the global error and global error variation. After finishing the training, the neural network is capable to forecast the electric load of 24 hours ahead. To illustrate the proposed methodology it is used data from a Brazilian Electric Company. © 2003 IEEE.

A constructive heuristic algorithm to Short Term Transmission Network Expansion Planning

In this paper a method for solving the Short Term Transmission Network Expansion Planning (STTNEP) problem is presented. The STTNEP is a very complex mixed integer nonlinear programming problem that presents a combinatorial explosion in the search space. In this work we present a constructive heuristic algorithm to find a solution of the STTNEP of excellent quality. In each step of the algorithm a sensitivity index is used to add a circuit (transmission line or transformer) to the system. This sensitivity index is obtained solving the STTNEP problem considering as a continuous variable the number of circuits to be added (relaxed problem). The relaxed problem is a large and complex nonlinear programming and was solved through an interior points method that uses a combination of the multiple predictor corrector and multiple centrality corrections methods, both belonging to the family of higher order interior points method (HOIPM). Tests were carried out using a modified Carver system and the results presented show the good performance of both the constructive heuristic algorithm to solve the STTNEP problem and the HOIPM used in each step.

Heuristic algorithm to solve the short term transmission network expansion planning

In this paper, a method for solving the short term transmission network expansion planning problem is presented. This is a very complex mixed integer nonlinear programming problem that presents a combinatorial explosion in the search space. In order to And a solution of excellent quality for this problem, a constructive heuristic algorithm is presented in this paper. In each step of the algorithm, a sensitivity index is used to add a circuit (transmission line or transformer) or a capacitor bank (fixed or variable) to the system. This sensitivity index is obtained solving the problem considering the numbers of circuits and capacitors banks to be added (relaxed problem), as continuous variables. The relaxed problem is a large and complex nonlinear programming and was solved through a higher order interior point method. The paper shows results of several tests that were performed using three well-known electric energy systems in order to show the possibility and the advantages of using the AC model. ©2007 IEEE.

A specialized genetic algorithm to solve the short term transmission network expansion planning

In this paper, the short term transmission network expansion planning (STTNEP) is solved through a specialized genetic algorithm (SGA). A complete AC model of the transmission network is used, which permits the formulation of an integrated power system transmission network expansion planning problem (real and reactive power planning). The characteristics of the proposed SGA to solve the STTNEP problem are detailed and an interior point method is employed to solve nonlinear programming problems during the solution steps of the SGA. Results of tests carried out with two electrical energy systems show the capabilities of the SGA and also the viability of using the AC model to solve the STTNEP problem. © 2009 IEEE.

An application of CHA to concurrent short-term transmission expansion & reactive power planning

In this paper a heuristic technique for solving simultaneous short-term transmission network expansion and reactive power planning problem (TEPRPP) via an AC model is presented. A constructive heuristic algorithm (CHA) aimed to obtaining a significant quality solution for such problem is employed. An interior point method (IPM) is applied to solve TEPRPP as a nonlinear programming (NLP) during the solution steps of the algorithm. For each proposed network topology, an indicator is deployed to identify the weak buses for reactive power sources placement. The objective function of NLP includes the costs of new transmission lines, real power losses as well as reactive power sources. By allocating reactive power sources at load buses, the circuit capacity may increase while the cost of new lines can be decreased. The proposed methodology is tested on Garver's system and the obtained results shows its capability and the viability of using AC model for solving such non-convex optimization problem. © 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.

Short periods of fasting followed by refeeding change the expression of muscle growth-related genes in juvenile Nile tilapia (Oreochromis niloticus)

Muscle growth mechanisms are controlled by molecular pathways that can be affected by fasting and refeeding. In this study, we hypothesized that short period of fasting followed by refeeding would change the expression of muscle growth-related genes in juvenile Nile tilapia (Oreochromis niloticus). The aim of this study was to analyze the expression of MyoD, myogenin and myostatin and the muscle growth characteristics in the white muscle of juvenile Nile tilapia during short period of fasting followed by refeeding. Juvenile fish were divided into three groups: (FC) control, feeding continuously for 42. days, (F5) 5. days of fasting and 37. days of refeeding, and (F10) 10. days of fasting and 32. days of refeeding. At days 5 (D5), 10 (D10), 20 (D20) and 42 (D42), fish (n = 14 per group) were anesthetized and euthanized for morphological, morphometric and gene expression analyses. During the refeeding, fasted fish gained weight continuously and, at the end of the experiment (D42), F5 showed total compensatory mass gain. After 5 and 10. days of fasting, a significant increase in the muscle fiber frequency (class 20) occurred in F5 and F10 compared to FC that showed a high muscle fiber frequency in class 40. At D42, the muscle fiber frequency in class 20 was higher in F5. After 5. days of fasting, MyoD and myogenin gene expressions were lower and myostatin expression levels were higher in F5 and F10 compared to FC; at D42, MyoD, myogenin and myostatin gene expression was similar among all groups. In conclusion, this study showed that short periods of fasting promoted muscle fiber atrophy in the juvenile Nile tilapia and the refeeding caused compensatory mass gain and changed the expression of muscle growth-related genes that promote muscle growth. These fasting and refeeding protocols have proven useful for understanding the effects of alternative warm fish feeding strategies on muscle growth-related genes. © 2013.

Multiobjective short-term planning of electric power distribution systems using NSGA-II

This paper presents a mixed integer nonlinear programming multiobjective model for short-term planning of distribution networks that considers in an integrated manner the following planning activities: allocation of capacitor banks; voltage regulators; the cable replacement of branches and feeders. The objective functions considered in the proposed model are: to minimize operational and investment costs and minimize the voltage deviations in the the network buses, subject to a set of technical and operational constraints. A multiobjective genetic algorithm based on a Non-Dominated Sorting Genetic Algorithm (NSGA-II) is proposed to solve this model. The proposed mathematical model and solution methodology is validated testing a medium voltage distribution system with 135 buses. © 2013 Brazilian Society for Automatics - SBA.

A fast cholinergic modulation of the primary acoustic startle circuit in rats

Cochlear root neurons (CRNs) are the first brainstem neurons which initiate and participate in the full expression of the acoustic startle reflex. Although it has been suggested that a cholinergic pathway from the ventral nucleus of the trapezoid body (VNTB) conveys auditory prepulses to the CRNs, the neuronal origin of the VNTB-CRNs projection and the role it may play in the cochlear root nucleus remain uncertain. To determine the VNTB neuronal type which projects to CRNs, we performed tract-tracing experiments combined with mechanical lesions, and morphometric analyses. Our results indicate that a subpopulation of non-olivocochlear neurons projects directly and bilaterally to CRNs via the trapezoid body. We also performed a gene expression analysis of muscarinic and nicotinic receptors which indicates that CRNs contain a cholinergic receptor profile sufficient to mediate the modulation of CRN responses. Consequently, we investigated the effects of auditory prepulses on the neuronal activity of CRNs using extracellular recordings in vivo. Our results show that CRN responses are strongly inhibited by auditory prepulses. Unlike other neurons of the cochlear nucleus, the CRNs exhibited inhibition that depended on parameters of the auditory prepulse such as intensity and interstimulus interval, showing their strongest inhibition at short interstimulus intervals. In sum, our study supports the idea that CRNs are involved in the auditory prepulse inhibition of the acoustic startle reflex, and confirms the existence of multiple cholinergic pathways that modulate the primary acoustic startle circuit. © 2013 Springer-Verlag Berlin Heidelberg.

Are early and late rate of force development differently influenced by fast-velocity resistance training?

This study examined the effect of fast-velocity concentric isokinetic resistance training (FV) on the rate of force development (RFD) at early (<100 ms) and late phases (>100 ms) of rising muscle force. Nine men participated in a 6-week resistance training intervention for the lower body, and nine matched subjects participated as controls (CON). During concentric isokinetic (180°s-1) knee extension training, subjects were instructed to do each contraction 'as fast and forcefully as possible'. Maximal muscle strength (MVC) and RFD (0-10, 0-20, ..., 0-250 ms from the onset of contraction) were measured during maximal voluntary isometric contraction of the knee extensors (KE). There were no significant changes in MVC of KE in both groups after intervention (FV = 314·2 ± 101·1 versus 338·7 ± 88·0 N{bullet operator}m, P>0·05; CON = 293·3 ± 94·8 versus 280·0 ± 72·2 N{bullet operator}m, P>0·05). The RFD increased 39-71% at time intervals up to 90 ms from the onset of the contraction (P<0·05), whereas no change occurred at later time intervals. Similarly, relative RFD (i.e.%MVC{bullet operator}s-1) (RFDr) increased 33-56% at time intervals up to 70 ms from the onset of the contraction (P<0·05). It can be concluded that a short period of resistance training performed with concentric fast-velocity isokinetic muscle contractions is able to enhance RFD and RFDr obtained at the early phase of rising muscle force. © 2013 The Authors Clinical Physiology and Functional Imaging © 2013 Scandinavian Society of Clinical Physiology and Nuclear Medicine.

Detecção e classificação de faltas de curto-circuito em sistemas de distribuição de energia elétrica usando lógica nebulosa

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)