Power quality analysis applying a hybrid methodology with wavelet transforms and neural networks

A hybrid system to automatically detect, locate and classify disturbances affecting power quality in an electrical power system is presented in this paper. The disturbances characterized are events from an actual power distribution system simulated by the ATP (Alternative Transients Program) software. The hybrid approach introduced consists of two stages. In the first stage, the wavelet transform (WT) is used to detect disturbances in the system and to locate the time of their occurrence. When such an event is flagged, the second stage is triggered and various artificial neural networks (ANNs) are applied to classify the data measured during the disturbance(s). A computational logic using WTs and ANNs together with a graphical user interface (GU) between the algorithm and its end user is then implemented. The results obtained so far are promising and suggest that this approach could lead to a useful application in an actual distribution system. (C) 2009 Elsevier Ltd. All rights reserved.

The family health system: analysis of a health survey in Sao Paulo, Brazil

Background The Family Health Strategy (FHS) has been implemented as a strategy for primary care improvement in Brazil. Working with teams that include one doctor, one nurse, auxiliary nurses and community health workers in predefined areas, the FHS began in 1994 (known then as the Family Health Program) and has since grown considerably. The programme has only recently undergone assessment of outcomes, in contrast to more routine evaluations of infrastructure and process. Methods In 2001, a health survey was carried out in two administrative districts (with 190 000 inhabitants) on the outskirts of the city of Sao Paulo, both partially served by the FHS. Chronic morbidity (hypertension, diabetes and ischaemic heart disease) of individuals aged 15 or older was studied in areas covered and not covered by the programme. Stratified univariate analysis was applied for sex, age, education, income, working status and social insurance of these populations. Multivariate analysis was applied where applicable. Results There was a distinct pattern in the morbidity profile of these populations, suggesting differentiated self-knowledge on chronic disease status in the areas served by the FHS. Conclusion The FHS can increase population awareness of chronic diseases, possibly through increasing access to primary care.

An algorithm for computerized automatic tuning of power system stabilizers

The main objective of this paper is to relieve the power system engineers from the burden of the complex and time-consuming process of power system stabilizer (PSS) tuning. To achieve this goal, the paper proposes an automatic process for computerized tuning of PSSs, which is based on an iterative process that uses a linear matrix inequality (LMI) solver to find the PSS parameters. It is shown in the paper that PSS tuning can be written as a search problem over a non-convex feasible set. The proposed algorithm solves this feasibility problem using an iterative LMI approach and a suitable initial condition, corresponding to a PSS designed for nominal operating conditions only (which is a quite simple task, since the required phase compensation is uniquely defined). Some knowledge about the PSS tuning is also incorporated in the algorithm through the specification of bounds defining the allowable PSS parameters. The application of the proposed algorithm to a benchmark test system and the nonlinear simulation of the resulting closed-loop models demonstrate the efficiency of this algorithm. (C) 2009 Elsevier Ltd. All rights reserved.

Innovation concept for measurement gross error detection and identification in power system state estimation

In this study, the innovation approach is used to estimate the measurement total error associated with power system state estimation. This is required because the power system equations are very much correlated with each other and as a consequence part of the measurements errors is masked. For that purpose an index, innovation index (II), which provides the quantity of new information a measurement contains is proposed. A critical measurement is the limit case of a measurement with low II, it has a zero II index and its error is totally masked. In other words, that measurement does not bring any innovation for the gross error test. Using the II of a measurement, the masked gross error by the state estimation is recovered; then the total gross error of that measurement is composed. Instead of the classical normalised measurement residual amplitude, the corresponding normalised composed measurement residual amplitude is used in the gross error detection and identification test, but with m degrees of freedom. The gross error processing turns out to be very simple to implement, requiring only few adaptations to the existing state estimation software. The IEEE-14 bus system is used to validate the proposed gross error detection and identification test.

Digital control and integration of a 192 MW wind farm with doubly fed induction generator into the Brazilian power system

This paper reports on design of digital control for wind turbines and its relation to the quality of power fed into the Brazilian grid on connecting to it a 192 MW wind farm equipped with doubly fed induction generators. PWM converters are deployed as vector controlled regulated current voltage sources for their rotors, for independent control of both active and reactive power of those generators. Both speed control and active power control strategies are analyzed, in the search for maximum efficiency of conversion of wind kinetic energy into electric power and enhanced quality of delivered power. (C) 2009 Elsevier B.V. All rights reserved.

Studies of cases in power systems by Sensitivity Analysis oriented by OPF

This paper presents studies of cases in power systems by Sensitivity Analysis (SA) oriented by Optimal Power Flow (OPF) problems in different operation scenarios. The studies of cases start from a known optimal solution obtained by OPF. This optimal solution is called base case, and from this solution new operation points may be evaluated by SA when perturbations occur in the system. The SA is based on Fiacco`s Theorem and has the advantage of not be an iterative process. In order to show the good performance of the proposed technique tests were carried out on the IEEE 14, 118 and 300 buses systems. (C) 2010 Elsevier Ltd. All rights reserved.

Renal denervation in an animal model of diabetes and hypertension: Impact on the autonomic nervous system and nephropathy

Background: The effects of renal denervation on cardiovascular reflexes and markers of nephropathy in diabetic-hypertensive rats have not yet been explored. Methods: Aim: To evaluate the effects of renal denervation on nephropathy development mechanisms (blood pressure, cardiovascular autonomic changes, renal GLUT2) in diabetic-hypertensive rats. Forty-one male spontaneously hypertensive rats (SHR) similar to 250 g were injected with STZ or not; 30 days later, surgical renal denervation (RD) or sham procedure was performed; 15 days later, glycemia and albuminuria (ELISA) were evaluated. Catheters were implanted into the femoral artery to evaluate arterial pressure (AP) and heart rate variability (spectral analysis) one day later in conscious animals. Animals were killed, kidneys removed, and cortical renal GLUT2 quantified (Western blotting). Results: Higher glycemia (p < 0.05) and lower mean AP were observed in diabetics vs. nondiabetics (p < 0.05). Heart rate was higher in renal-denervated hypertensive and lower in diabetic-hypertensive rats (384.8 +/- 37, 431.3 +/- 36, 316.2 +/- 5, 363.8 +/- 12 bpm in SHR, RD-SHR, STZ-SHR and RD-STZ-SHR, respectively). Heart rate variability was higher in renal-denervated diabetic-hypertensive rats (55.75 +/- 25.21, 73.40 +/- 53.30, 148.4 +/- 93 in RD-SHR, STZ-SHR-and RD-STZ-SHR, respectively, p < 0.05), as well as the LF component of AP variability (1.62 +/- 0.9, 2.12 +/- 0.9, 7.38 +/- 6.5 in RD-SHR, STZ-SHR and RD-STZ-SHR, respectively, p < 0.05). GLUT2 renal content was higher in all groups vs. SHR. Conclusions: Renal denervation in diabetic-hypertensive rats improved previously reduced heart rate variability. The GLUT2 equally overexpressed by diabetes and renal denervation may represent a maximal derangement effect of each condition.

Exercise training associated with diet improves heart rate recovery and cardiac autonomic nervous system activity in obese children

The purpose of this study was to test the hypotheses that in obese children: 1) hypocaloric diet (D) improves both heart rate recovery at 1 min (Delta HRR1) cfter an exercise test, and cardiac autonomic nervous system activity (CANSA) in obese children; 2) Diet and exercise training (DET) combined leads to greater improvement in both Delta HRR1 after an exercise test and in CANSA, than D alone. Moreover, we examined the relationships among Delta HRR1, CANSA, cardiorespiratory fitness and anthropometric variables (AV) in obese children submitted to D and to DET. 33 obese children (10 +/- 0.2 years; body mass index (BMI) >95(th) percentile) were divided into 2 groups: D (n = 15; BMI = 31 +/- 1 kg/m(2)) and DET (n = 18; 29 +/- 1 kg/m(2)). All children performed a maximal cardiopulmonary exercise test on a treadmill. The Delta HRR1 was defined as the difference between heart rate at peak and at 1-min post-exercise. CANSA was assessed using power spectral analysis of heart rate variability at rest. The sympathovagal balance (low frequency and high frequency ratio, LF/HF) was measured. After interventions, all obese children showed reduced body weight (P < 0.05). The D group did not improve in terms of peak VO(2), Delta HRR1 or LF/HF ratio (P > 0.05). In contrast, the DET group showed increased peak VO(2) (P = 0.01) and improved Delta HRR1 (Delta HRR1 = 37.3 +/- 2.6; P = 0.01) and LF/HF ratio (P = 0.001). The DET group demonstrated significant relationships among Delta HRR1, peak VO(2) and CANSA (P < 0.05). In conclusion, DET, in contrast to D, promoted improved Delta HRR1 and CANSA in obese children, suggesting a positive influence of increased levels of cardiorespiratory fitness by exercise training on cardiac autonomic activity.

GOOAL: A routine based on Genetic Algorithms to track harmonics in electric power systems

Voltage and current waveforms of a distribution or transmission power system are not pure sinusoids. There are distortions in these waveforms that can be represented as a combination of the fundamental frequency, harmonics and high frequency transients. This paper presents a novel approach to identifying harmonics in power system distorted waveforms. The proposed method is based on Genetic Algorithms, which is an optimization technique inspired by genetics and natural evolution. GOOAL, a specially designed intelligent algorithm for optimization problems, was successfully implemented and tested. Two kinds of representations concerning chromosomes are utilized: binary and real. The results show that the proposed method is more precise than the traditional Fourier Transform, especially considering the real representation of the chromosomes.

Day-night pattern of autonomic nervous system modulation in patients with heart failure with and without sleep apnea

Introduction: Among patients with congestive heart failure (CHF) both obstructive and central sleep apnea (SA) are associated with increased sympathetic activity. However, the day-night pattern of cardiac autonomic nervous system modulation in CHF patients with and without sleep apnea is unknown. Material and methods: Twenty-five CHF patients underwent polysomnography with simultaneous beat-to-beat blood pressure (Portapres), respiration and electrocardiogram monitoring. Patients were divided according to the presence (SA, n=17) and absence of SA (NoSA, n=8). Power spectral analyses of heart rate variability (HRV) and spontaneous baroreflex sensitivity (BRS) were determined in periods with stable breathing while awake at 6 AM, 10 AM, 10 PM, as well as during stage 2 sleep. In addition, muscle sympathetic nerve activity (MSNA) was evaluated at 10 AM. Results: RR variance, low-frequency (LF), high-frequency (HF) powers of HRV, and BRS were significantly lower in patients with SA compared with NoSA in all periods. HF power, a marker of vagal activity, increased during sleep in patients with NoSA but in contrast did not change across the 24-hour period in patients with SA. MSNA was significantly higher in patients with SA compared with NoSA. RR variance, LF and HF powers correlated inversely with simultaneous MSNA (r=-0.64, -0.61, and -0.61 respectively; P < 0.01). Conclusions: Patients with CHF and SA present a reduced and blunted cardiac autonomic modulation across the 24-hour period. These findings may help to explain the increased cardiovascular risk in patients with CHF and SA. (C) 2009 Elsevier Ireland Ltd. All rights reserved.

Optimisation of environmental gas cleaning routes for solid wastes cogeneration systems - Part I - Analysis of waste incineration steam cycle

Research of advanced technologies for energy generation contemplates a series of alternatives that are introduced both in the investigation of new energy sources and in the improvement and/or development of new components and systems. Even though significant reductions are observed in the amount of emissions, the proposed alternatives require the use of exhaust gases cleaning systems. The results of environmental analyses based on two configurations proposed for urban waste incineration are presented in this paper; the annexation of integer (Boolean) variables to the environomic model makes it possible to define the best gas cleaning routes based on exergetic cost minimisation criteria. In this first part, the results for steam cogeneration system analysis associated with the incineration of municipal solid wastes (MSW) is presented. (c) 2007 Elsevier Ltd. All rights reserved.

Power Transformer Differential Protection Based on Clarke`s Transform and Fuzzy Systems

The power transformer is a piece of electrical equipment that needs continuous monitoring and fast protection since it is very expensive and an essential element for a power system to perform effectively. The most common protection technique used is the percentage differential logic, which provides discrimination between an internal fault and different operating conditions. Unfortunately, there are some operating conditions of power transformers that can affect the protection behavior and the power system stability. This paper proposes the development of a new algorithm to improve the differential protection performance by using fuzzy logic and Clarke`s transform. An electrical power system was modeled using Alternative Transients Program (ATP) software to obtain the operational conditions and fault situations needed to test the algorithm developed. The results were compared to a commercial relay for validation, showing the advantages of the new method.

Harmonic identification using parallel neural networks in single-phase systems

In this paper, artificial neural networks are employed in a novel approach to identify harmonic components of single-phase nonlinear load currents, whose amplitude and phase angle are subject to unpredictable changes, even in steady-state. The first six harmonic current components are identified through the variation analysis of waveform characteristics. The effectiveness of this method is tested by applying it to the model of a single-phase active power filter, dedicated to the selective compensation of harmonic current drained by an AC controller. Simulation and experimental results are presented to validate the proposed approach. (C) 2010 Elsevier B. V. All rights reserved.

Combined heuristic with fuzzy system to transmission system expansion planning

A heuristic algorithm that employs fuzzy logic is proposed to the power system transmission expansion planning problem. The algorithm is based on the divide to conquer strategy, which is controlled by the fuzzy system. The algorithm provides high quality solutions with the use of fuzzy decision making, which is based on nondeterministic criteria to guide the search. The fuzzy system provides a self-adjusting mechanism that eliminates the manual adjustment of parameters to each system being solved. (C) 2010 Elsevier B.V. All rights reserved.

Digital frequency relaying based on the modified least mean square method

This research presents a method for frequency estimation in power systems using an adaptive filter based on the Least Mean Square Algorithm (LMS). In order to analyze a power system, three-phase voltages were converted into a complex signal applying the alpha beta-transform and the results were used in an adaptive filtering algorithm. Although the use of the complex LMS algorithm is described in the literature, this paper deals with some practical aspects of the algorithm implementation. In order to reduce computing time, a coefficient generator was implemented. For the algorithm validation, a computing simulation of a power system was carried Out using the ATP software. Many different situations were Simulated for the performance analysis of the proposed methodology. The results were compared to a commercial relay for validation, showing the advantages of the new method. (C) 2009 Elsevier Ltd. All rights reserved.