Multivariate quality control studies applied to Ca(II) and Mg(II) determination by a portable method

A portable or field test method for simultaneous spectrophotometric determination of calcium and magnesium in water using multivariate partial least squares (PLS) calibration methods is proposed. The method is based on the reaction between the analytes and methylthymol blue at pH 11. The spectral information was used as the X-block, and the Ca(II) and Mg(II) concentrations obtained by a reference technique (ICP-AES) were used as the Y-block. Two series of analyses were performed, with a month's difference between them. The first series was used as the calibration set and the second one as the validation set. Multivariate statistical process control (MSPC) techniques, based on statistics from principal component models, were used to study the features and evolution with time of the spectral signals. Signal standardization was used to correct the deviations between series. Method validation was performed by comparing the predictions of the PLS model with the reference Ca(II) and Mg(II) concentrations determined by ICP-AES using the joint interval test for the slope and intercept of the regression line with errors in both axes. (C) 1998 John Wiley & Sons, Ltd.

An efficient geometric parameterization technique for the continuation power flow

Continuation methods have been shown as efficient tools for solving ill-conditioned cases, with close to singular Jacobian matrices, such as the maximum loading point of power systems. Some parameterization techniques have been proposed to avoid matrix singularity and successfully solve those cases. This paper presents a new geometric parameterization scheme that allows the complete tracing of the P-V curves without ill-conditioning problems. The proposed technique associates robustness to simplicity and, it is of easy understanding. The Jacobian matrix singularity is avoided by the addition of a line equation, which passes through a point in the plane determined by the total real power losses and loading factor. These two parameters have clear physical meaning. The application of this new technique to the IEEE systems (14, 30, 57, 118 and 300 buses) shows that the best characteristics of the conventional Newton's method are not only preserved but also improved. (C) 2006 Elsevier B.V. All rights reserved.

A decentralized approach for optimal reactive power dispatch using a Lagrangian decomposition method

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Production grinding burn detection using acoustic emission and electric power signals

This work uses a monitoring system based on a PC platform, where the acoustic emission and electric power signals generated during the grinding process are used to investigate superficial burning occurrence in a surface grinding operation using two types of steel, three grinding conditions and an Al203 vitrified grinding wheel. Acoustic emission signals on the workpiece and grinding power were measured during a surface plunge operation until the grinding burn happened. From the results the standard deviation of the acoustic emission signal and the maximum electric power were calculated for each grinding pass. The proposed DPO parameter is the product between the power level and acoustic emission standard deviation. The results show that both signals can be used for burning detection, and the parameter DPO is the best indicator for the burning studied in this work. This can be explained by the high dispersion of the acoustic emission RMS level associated to the high power consumption when the grinding wheel lose its sharpness.

VAr planning using genetic algorithm and linear programming

A combined methodology consisting of successive linear programming (SLP) and a simple genetic algorithm (SGA) solves the reactive planning problem. The problem is divided into operating and planning subproblems; the operating subproblem, which is a nonlinear, ill-conditioned and nonconvex problem, consists of determining the voltage control and the adjustment of reactive sources. The planning subproblem consists of obtaining the optimal reactive source expansion considering operational, economical and physical characteristics of the system. SLP solves the optimal reactive dispatch problem related to real variables, while SGA is used to determine the necessary adjustments of both the binary and discrete variables existing in the modelling problem. Once the set of candidate busbars has been defined, the program implemented gives the location and size of the reactive sources needed, if any, to maintain the operating and security constraints.

An analytical solution to the optimal power flow

This letter presents an approach for a geometrical solution of an optimal power flow (OPF) problem for a two-bus system (slack and PV busses). The algebraic equations for the calculation of the Lagrange multipliers and for the minimum losses value are obtained. These equations are used to validate the results obtained using an OPF program.

A novel programmable PFC based hybrid rectifier for ultra clean power application

A novel hybrid high power rectifier capable to achieve unity power factor is proposed in this paper. Single-phase SEPIC rectifiers are associated in parallel with each leg of three-phase 6-pulse diode rectifier resulting in a programmable input current waveform structure. In this paper it is described the principles of operation of the proposed converter with detailed simulation and experimental results. For a total harmonic distortion of the input line current (THDI) less than 2% the rated power of the SEPIC rectifiers is 33%. Therefore, power rating of the SEPIC parallel converters is a fraction of the output power, on the range of 20% to 33% of the nominal output power, making the proposed solution economically viable for high power installations, with fast pay back of the investment. Moreover, retrofits to existing installations are also possible with this proposed topology, since the parallel path can be easily controlled by integration with the already existing de-link. Experimental results are presented for a 3 kW implemented prototype, in order to verify the developed analysis.

Modified barrier method for optimal power flow problem

In this paper is presented a new approach for optimal power flow problem. This approach is based on the modified barrier function and the primal-dual logarithmic barrier method. A Lagrangian function is associated with the modified problem. The first-order necessary conditions for optimality are fulfilled by Newton's method, and by updating the barrier terms. The effectiveness of the proposed approach has been examined by solving the Brazilian 53-bus, IEEE118-bus and IEEE162-bus systems.

Alternative continuation method for loading margin improvement and transmission losses reduction

This paper presents an alternative methodology for loading margin improvement and total real power losses reduction by using a continuation method. In order to attain this goal, a parameterizing equation based on the total real power losses and the equations of the reactive power at the slack and generation buses are added to the conventional power flow equations. The voltages at these buses are considered as control variables and a new parameter is chosen to reduce the real power losses in the transmission lines. The results show that this procedure leads to maximum loading point increase and consequently, in static voltage stability margin improvement. Besides, this procedure also takes to a reduction in the operational costs and, simultaneously, to voltage profile improvement. Another important result of this methodology is that the resulting operating points are close to that provided by an optimal power flow program. © 2004 IEEE.

Distribution line models analysis for loss calculation within three-phase three-wire power flow algorithms

Three-phase three-wire power flow algorithms, as any tool for power systems analysis, require reliable impedances and models in order to obtain accurate results. Kron's reduction procedure, which embeds neutral wire influence into phase wires, has shown good results when three-phase three-wire power flow algorithms based on current summation method were used. However, Kron's reduction can harm reliabilities of some algorithms whose iterative processes need loss calculation (power summation method). In this work, three three-phase three-wire power flow algorithms based on power summation method, will be compared with a three-phase four-wire approach based on backward-forward technique and current summation. Two four-wire unbalanced medium-voltage distribution networks will be analyzed and results will be presented and discussed. © 2004 IEEE.

Stability analysis of power system including facts (TCSC) effects by direct method approach

The problem of power system stability including the effects of a flexible alternating current transmission system (FACTS) is approached. First, the controlled series compensation is considered in the machine against infinite bar system and its effects are taken into account by means of construction of a Lyapunov function (LF). This simple system is helpful in order to understand the form the device affects dynamic and transient performance of the power system. After, the multimachine case is considered and it is shown that the single-machine results apply to multimachine systems. An energy-form Lyapunov function is derived for the power system including the FACTS device and it is used to analyse damping and synchronizing effects due to the FACTS device in single-machine as well as in multimachine power systems. © 2005 Elsevier Ltd. All rights reserved.

Carbon isotope composition as a tool for quality control of herbs, spices and medicinal plants

Isotope screening is a simple and cheap test for determining the photosynthetic pathway used by plants. The scope of this work was to classify the photosynthetic type of Melissa officinalis L. and Cymbopogon citratus [DC.] Stapf, through studies of the carbon isotope composition (δ13 C), and we are proposing the use of carbon isotope composition results as a tool to control the quality of medicinal plants. For studies of δ 13C (13 C% = [R (sample)/R (standard) - 1] × 10 -3), dried, powdered leaves were analyzed in a mass spectrometer coupled with an elemental analyzer for determining the ratio R (R = 13CO2/12CO2). As results, M. officinalis presented a C3 photosynthetic type, and C. citratus presented a C4 photosynthetic type. The carbon isotope composition from this study can be used as quality control of M. officinalis adulterants.

An approach based on neural networks for identification of fault sections in radial distribution systems

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

Intelligent alarm processing

This paper presents the analysis that have been carried out in the alarm system of the DCRanger EMS. The intention of this study is to present the problem of alarm processing in electric energy control centers, its various aspects and operational difficulties due to operator needs. Some tests are produced in order to identify the desirable features an alarm system should possess in order to be of effective help in the operative duty. © 2006 IEEE.

Neural network approach for surface roughness prediction in surface grinding

Several systems are currently tested in order to obtain a feasible and safe method for automation and control of grinding process. This work aims to predict the surface roughness of the parts of SAE 1020 steel ground in a surface grinding machine. Acoustic emission and electrical power signals were acquired by a commercial data acquisition system. The former from a fixed sensor placed near the workpiece and the latter from the electric induction motor that drives the grinding wheel. Both signals were digitally processed through known statistics, which with the depth of cut composed three data sets implemented to the artificial neural networks. The neural network through its mathematical logical system interpreted the signals and successful predicted the workpiece roughness. The results from the neural networks were compared to the roughness values taken from the worpieces, showing high efficiency and applicability on monitoring and controlling the grinding process. Also, a comparison among the three data sets was carried out.