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.

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.

Fault Detection in Power Distribution Systems Using Automated Integration of Computational Intelligence Tools

The main purpose of this paper is to present architecture of automated system that allows monitoring and tracking in real time (online) the possible occurrence of faults and electromagnetic transients observed in primary power distribution networks. Through the interconnection of this automated system to the utility operation center, it will be possible to provide an efficient tool that will assist in decisionmaking by the Operation Center. In short, the desired purpose aims to have all tools necessary to identify, almost instantaneously, the occurrence of faults and transient disturbances in the primary power distribution system, as well as to determine its respective origin and probable location. The compilations of results from the application of this automated system show that the developed techniques provide accurate results, identifying and locating several occurrences of faults observed in the distribution system.

Transmission loss allocation based on optimal power flow and sensitivity analysis

This paper presents a new approach to the transmission loss allocation problem in a deregulated system. This approach belongs to the set of incremental methods. It treats all the constraints of the network, i.e. control, state and functional constraints. The approach is based on the perturbation of optimum theorem. From a given optimal operating point obtained by the optimal power flow the loads are perturbed and a new optimal operating point that satisfies the constraints is determined by the sensibility analysis. This solution is used to obtain the allocation coefficients of the losses for the generators and loads of the network. Numerical results show the proposed approach in comparison to other methods obtained with well-known transmission networks, IEEE 14-bus. Other test emphasizes the importance of considering the operational constraints of the network. And finally the approach is applied to an actual Brazilian equivalent network composed of 787 buses, and it is compared with the technique used nowadays by the Brazilian Control Center. (c) 2007 Elsevier Ltd. All rights reserved.

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.

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.

Gait Pattern Adaptation for an Active Lower-Limb Orthosis Based on Neural Networks

This work deals with neural network (NN)-based gait pattern adaptation algorithms for an active lower-limb orthosis. Stable trajectories with different walking speeds are generated during an optimization process considering the zero-moment point (ZMP) criterion and the inverse dynamic of the orthosis-patient model. Additionally, a set of NNs is used to decrease the time-consuming analytical computation of the model and ZMP. The first NN approximates the inverse dynamics including the ZMP computation, while the second NN works in the optimization procedure, giving an adapted desired trajectory according to orthosis-patient interaction. This trajectory adaptation is added directly to the trajectory generator, also reproduced by a set of NNs. With this strategy, it is possible to adapt the trajectory during the walking cycle in an on-line procedure, instead of changing the trajectory parameter after each step. The dynamic model of the actual exoskeleton, with interaction forces included, is used to generate simulation results. Also, an experimental test is performed with an active ankle-foot orthosis, where the dynamic variables of this joint are replaced in the simulator by actual values provided by the device. It is shown that the final adapted trajectory follows the patient intention of increasing the walking speed, so changing the gait pattern. (C) Koninklijke Brill NV, Leiden, 2011

Experimental Analysis of Structural Change and Rheological Behavior of Macromolecular Solutions with Guar and Xanthan Gums in Crossflow Microfiltration Processing

The present paper reports on the structural change and rheological behavior of mixtures of macromolecular suspensions (guar and xanthan gums) in crossflow microfiltration processing. Mixtures in suspension of guar and xanthan gums at low concentrations (1,000 ppm) and different proportions were processed by microfiltration with membrane of nominal pore size of 0.4 mu m. The rheological behavior of the mixtures was investigated in rotational viscometers at two different temperatures, 25 and 40 C, at the beginning and at the end of each experiment. The shear stress (t) in function of the shear rate (gamma) was fitted and analyzed with the power-law model. All the mixtures showed flow behavior index values (n) lower than 1, characterizing non-Newtonian fluids (pseudoplastic). The samples of both mixtures and permeates were also analyzed by absorbency spectroscopy in infrared radiation. The absorbency analysis showed that there is good synergism between xanthan and guar gums without structure modifications or gel formation in the concentration process by microfiltration.

Effect of impeller type and mechanical agitation on the mass transfer and power consumption aspects of ASBR operation treating synthetic wastewater

The effect of flow type and rotor speed was investigated in a round-bottom reactor with 5 L useful volume containing 2.0 L of granular biomass. The reactor treated 2.0 L of synthetic wastewater with a concentration of 800 mgCOD/L in 8-h cycles at 30 degrees C. Five impellers, commonly used in biological processes, have been employed to this end, namely: a turbine and a paddle impeller with six-vertical-flat-blades, a turbine and a paddle impeller with six-45 degrees-inclined-flat-blades and a three-blade-helix impeller. Results showed that altering impeller type and rotor speed did not significantly affect system stability and performance. Average organic matter removal efficiency was about 84% for filtered samples, total volatile acids concentration was below 20 mgHAc/L and bicarbonate alkalinity a little less than 400 mgCaCO(3)/L for most of the investigated conditions. However, analysis of the first-order kinetic model constants showed that alteration in rotor speed resulted in an increase in the values of the kinetic constants (for instance, from 0.57 h(-1) at 50 rpm to 0.84 h(-1) at 75 rpm when the paddle impeller with six-45 degrees-inclined-flat-blades was used) and that axial flow in mechanically stirred reactors is preferable over radial-flow when the vertical-flat-blade impeller is compared to the inclined-flat-blade impeller (for instance at 75 rpm, from 0.52 h(-1) with the six-flat-blade-paddle impeller to 0.84 h(-1) with the six-45 degrees-inclined-flat-blade-paddle impeller), demonstrating that there is a rotor speed and an impeller type that maximize solid-liquid mass transfer in the reaction medium. Furthermore, power consumption studies in this reduced reactor volume showed that no high power transfer is required to improve mass transfer (less than 0.6 kW/10(3) m(3)). (C) 2008 Elsevier Ltd. All rights reserved.

Air uptake along the lower nappe of a spillway aerator

Air concentration measurements performed along the lower nappe of a bottom aerator through the impact and downstream flow regions permitted the calculation of air entrainment along the jet length. The air uptake was also measured in the air supply conduit. It was shown that integration of the concentration profiles along the jet overestimates the air uptake measured in the air supply conduit. Corrective procedures were developed by adapting the concept of entrained and entrapped air, in which the latter is re-circulated in the cavity, but both are measured by air concentration probes.

Macro-Fiber Composite Actuators for Flow Control of a Variable Camber Airfoil

This research employs solid-state actuators for delay of flow separation seen in airfoils at low Reynolds numbers. The flow control technique investigated here is aimed for a variable camber airfoil that employs two active surfaces and a single four-bar (box) mechanism as the internal structure. To reduce separation, periodic excitation to the flow around the leading edge of the airfoil is induced by a total of nine piezocomposite actuated clamped-free unimorph benders distributed in the spanwise direction. An electromechanical model is employed to design an actuator capable of high deformations at the desired frequency for lift improvement at post-stall angles. The optimum spanwise distribution of excitation for increasing lift coefficient is identified experimentally in the wind tunnel. A 3D (non-uniform) excitation distribution achieved higher lift enhancement in the post-stall region with lower power consumption when compared to the 2D (uniform) excitation distribution. A lift coefficient increase of 18.4% is achieved with the identified non-uniform excitation mode at the bender resonance frequency of 125 Hz, the flow velocity of 5 m/s and at the reduced frequency of 3.78. The maximum lift (Clmax) is increased 5.2% from the baseline. The total power consumption of the flow control technique is 639 mW(RMS).

Extended Fault-Location Formulation for Power Distribution Systems

In this paper, an extended impedance-based fault-location formulation for generalized distribution systems is presented. The majority of distribution feeders are characterized by having several laterals, nonsymmetrical lines, highly unbalanced operation, and time-varying loads. These characteristics compromise traditional fault-location methods performance. The proposed method uses only local voltages and currents as input data. The current load profile is obtained through these measurements. The formulation considers load variation effects and different fault types. Results are obtained from numerical simulations by using a real distribution system from the Electrical Energy Distribution State Company of Rio Grande do Sul (CEEE-D), Southern Brazil. Comparative results show the technique robustness with respect to fault type and traditional fault-location problems, such as fault distance, resistance, inception angle, and load variation. The formulation was implemented as embedded software and is currently used at CEEE-D`s distribution operation center.

Hybrid fault diagnosis scheme implementation for power distribution systems automation

Power distribution automation and control are import-ant tools in the current restructured electricity markets. Unfortunately, due to its stochastic nature, distribution systems faults are hardly avoidable. This paper proposes a novel fault diagnosis scheme for power distribution systems, composed by three different processes: fault detection and classification, fault location, and fault section determination. The fault detection and classification technique is wavelet based. The fault-location technique is impedance based and uses local voltage and current fundamental phasors. The fault section determination method is artificial neural network based and uses the local current and voltage signals to estimate the faulted section. The proposed hybrid scheme was validated through Alternate Transient Program/Electromagentic Transients Program simulations and was implemented as embedded software. It is currently used as a fault diagnosis tool in a Southern Brazilian power distribution company.

Emissions of NO(x) and SO(2) from Coals of Various Ranks, Bagasse, and Coal-Bagasse Blends Burning in O(2)/N(2) and O(2)/CO(2) Environments

Oxy-coal combustion is a viable technology, for new and existing coal-fired power plants, as it facilitates carbon capture and, thereby, can mitigate climate change. Pulverized coals of various ranks, biomass, and their blends were burned to assess the evolution of combustion effluent gases, such as NO(x), SO(2), and CO, under a variety of background gas compositions. The fuels were burned in an electrically heated laboratory drop-tube furnace in O(2)/N(2) and O(2)/CO(2) environments with oxygen mole fractions of 20%, 40%, 60%, 80%, and 100%, at a furnace temperature of 1400 K. The fuel mass flow rate was kept constant in most cases, and combustion was fuel-lean. Results showed that in the case of four coals studied, NO(x) emissions in O(2)/CO(2) environments were lower than those in O(2)/N(2) environments by amounts that ranged from 19 to 43% at the same oxygen concentration. In the case of bagasse and coal/bagasse blends, the corresponding NO(x) reductions ranged from 22 to 39%. NO(x) emissions were found to increase with increasing oxygen mole fraction until similar to 50% O(2) was reached; thereafter, they monotonically decreased with increasing oxygen concentration. NO(x) emissions from the various fuels burned did not clearly reflect their nitrogen content (0.2-1.4%), except when large content differences were present. SO(2) emissions from all fuels remained largely unaffected by the replacement of the N(2) diluent gas with CO(2), whereas they typically increased with increasing sulfur content of the fuels (0.07-1.4%) and decreased with increasing calcium content of the fuels (0.28-2.7%). Under the conditions of this work, 20-50% of the fuel-nitrogen was converted to NO(x). The amount of fuel-sulfur converted to SO(2) varied widely, depending on the fuel and, in the case of the bituminous coal, also depending on the O(2) mole fraction. Blending the sub-bituminous coal with bagasse reduced its SO(2) yields, whereas blending the bituminous coal with bagasse reduced both its SO(2) and NO(x) yields. CO emissions were generally very low in all cases. The emission trends were interpreted on the basis of separate combustion observations.

Further improvements on impedance-based fault location for power distribution systems

In this study, further improvements regarding the fault location problem for power distribution systems are presented. The proposed improvements relate to the capacitive effect consideration on impedance-based fault location methods, by considering an exact line segment model for the distribution line. The proposed developments, which consist of a new formulation for the fault location problem and a new algorithm that considers the line shunt admittance matrix, are presented. The proposed equations are developed for any fault type and result in one single equation for all ground fault types, and another equation for line-to-line faults. Results obtained with the proposed improvements are presented. Also, in order to compare the improvements performance and demonstrate how the line shunt admittance affects the state-of-the-art impedance-based fault location methodologies for distribution systems, the results obtained with two other existing methods are presented. Comparative results show that, in overhead distribution systems with laterals and intermediate loads, the line shunt admittance can significantly affect the state-of-the-art methodologies response, whereas in this case the proposed developments present great improvements by considering this effect.