Distribution systems fault analysis considering fault resistance estimation

Fault resistance is a critical component of electric power systems operation due to its stochastic nature. If not considered, this parameter may interfere in fault analysis studies. This paper presents an iterative fault analysis algorithm for unbalanced three-phase distribution systems that considers a fault resistance estimate. The proposed algorithm is composed by two sub-routines, namely the fault resistance and the bus impedance. The fault resistance sub-routine, based on local fault records, estimates the fault resistance. The bus impedance sub-routine, based on the previously estimated fault resistance, estimates the system voltages and currents. Numeric simulations on the IEEE 37-bus distribution system demonstrate the algorithm`s robustness and potential for offline applications, providing additional fault information to Distribution Operation Centers and enhancing the system restoration process. (C) 2011 Elsevier Ltd. All rights reserved.

A Family of Autoconnected Transformers for 12-and 18-Pulse Converters-Generalization for Delta and Wye Topologies

Multipulse rectifier topologies based on autoconnections are increasingly applied as interface stages between mains and power electronics converters. These topologies are attractive and cost-effective solutions for meeting the requirements of low total harmonic distortion of line current and high power factor. Furthermore, as only a small fraction of the total power required by the load is processed in the magnetic core, the overall resulting volume and weight are reduced. This paper proposes a mathematical analysis based on phasor diagrams that results in a single and general expression capable of unifying all delta and wye step-up or step-down autotransformer connections for 12-and 18-pulse ac-dc converters. The expression obtained allows the choice of a wide range of input/output voltage ratio for step-up or step-down autotransformer, and this general expression is also presented in a graphical form for each converter. Moreover, it simplifies the procedure for determining turn ratios and polarities for all windings of the autotransformer. A routine for easy and fast calculations is developed and validated by a design example. Finally, experimental results are presented along with comments on a 6-kW 220-V line voltage, 400-V rectified voltage, and 18-pulse delta-autoconnected prototype.

Transmission lines distance protection using artificial neural networks

This work presents the development and implementation of an artificial neural network based algorithm for transmission lines distance protection. This algorithm was developed to be used in any transmission line regardless of its configuration or voltage level. The described ANN-based algorithm does not need any topology adaptation or ANN parameters adjustment when applied to different electrical systems. This feature makes this solution unique since all ANN-based solutions presented until now were developed for particular transmission lines, which means that those solutions cannot be implemented in commercial relays. (c) 2011 Elsevier Ltd. All rights reserved.

Sterilization by pure oxygen plasma and by oxygen-hydrogen peroxide plasma: An efficacy study

Plasma is an innovative sterilization method characterized by a low toxicity to operators and patients, and also by its operation at temperatures close to room temperatures. The use of different parameters for this method of sterilization and the corresponding results were analyzed in this study. A low-pressure inductive discharge was used to study the plasma sterilization processes. Oxygen and a mixture of oxygen and hydrogen peroxide were used as plasma source gases. The efficacy of the processes using different combinations of parameters such as plasma-generation method, type of gas, pressure, gas flow rate, temperature, power, and exposure time was evaluated. Two phases were developed for the processes, one using pure oxygen and the other a mixture of gases. Bacillus subtilis var. niger ATCC 9372 (Bacillus atrophaeus) spores inoculated on glass coverslips were used as biological indicators to evaluate the efficacy of the processes. All cycles were carried out in triplicate for different sublethal exposure times to calculate the D value by the enumeration method. The pour-plate technique was used to quantify the spores. D values of between 8 and 3 min were obtained. Best results were achieved at high power levels (350 and 40oW) using pure oxygen, showing that plasma sterilization is a promising alternative to other sterilization methods. (c) 2007 Elsevier B.V. All rights reserved.

Nanocomposite Nafion-Silica membranes for direct methanol fuel cells

Commercially available proton exchange membranes such as Nafion do not meet the requirements for high power density direct methanol fuel cells, partly due to their high methanol permeability. The aim of this work is to develop a new class of high-proton conductivity membranes, with thermal and mechanical stability similar to Nafion and reduced methanol permeability. Nanocomposite membranes were produced by the in-situ sol-gel synthesis of silicon dioxide particles in preformed Nafion membranes. Microstructural modification of Nafion membranes with silica nanoparticles was shown in this work to reduce methanol crossover from 7.48x10-6 cm2s^-1 for pure Nafion® to 2.86 x10-6 cm2s^-1 for nanocomposite nafion membranes (Methanol 50% (v/v) solution, 75 degrees C). Best results were achieved with a silica composition of 2.6% (w/w). We propose that silica inhibits the conduction of methanol through Nafion by blocking sites necessary for methanol diffusion through the polymer electrolyte membrane. Effects of surface chemistry, nanoparticle formation and interactions with Nafion matrix are further addressed.

Development of novel bioanodes for ethanol biofuel cell using PAMAM dendrimers as matrix for enzyme immobilization

This paper describes the preparation and application of a novel bioanode for use in ethanol/O(2) biofuel cells based upon immobilization of alcohol dehydrogenase (ADH) and polyamidoamine (PAMAM) dendrimers onto carbon cloth platforms. The power density measurements indicated a direct relationship between the amount of anchored ADH and the anode power values, which increased upon enzyme loading. The power density values ranged from 0.04 to 0.28 mW cm(-2), and the highest power density was achieved with the bioanode prepared with 28 U of ADH, which provided a power density of 0.28 mW cm(-2) at 0.3 V. The latter power output values were the maximum observed, even for higher enzyme concentrations. Stability of the bioanodes was quite satisfactory, since there was no appreciable reduction of enzymatic activity during the measurements. The method of bioanode preparation described here has proven to be very effective. The PAMAM dendrimer represents a friendly environment for the immobilization of enzymes, and it is stable and capable of generating high power density compared to other immobilization methods. (C) 2010 Elsevier B.V. All rights reserved.

Direct measurement of pulse distortion near the zero-dispersion wavelength in an optical fiber by frequency-resolved optical gating

The technique of frequency-resolved optical gating is used to characterize the intensity and the phase of picosecond pulses after propagation through 700 m of fiber at close to the zero-dispersion wavelength. Using the frequency-resolved optical gating technique, we directly measure the severe temporal distortion resulting from the interplay between self-phase modulation and higher-order dispersion in this regime. The measured intensity and phase of the pulses after propagation are found to be in good agreement with the predictions of numerical simulations with the nonlinear Schrodinger equation. (C) 1997 Optical Society of America.

Novel molecular sieve silica (MSS) membranes: characterisation and permeation of single-step and two-step sol-gel membranes

High quality MSS membranes were synthesised by a single-step and two-step catalysed hydrolyses employing tetraethylorthosilicate (TEOS), absolute ethanol (EtOH), I M nitric acid (HNO3) and distilled water (H2O). The Si-29 NMR results showed that the two-step xerogels consistently had more contribution of silanol groups (Q(3) and Q(2)) than the single-step xerogel. According to the fractal theory, high contribution of Q(2) and Q(3) species are responsible for the formation of weakly branched systems leading to low pore volume of microporous dimension. The transport of diffusing gases in these membranes is shown to be activated as the permeance increased with temperature. Albeit the permeance of He for both single-step and two-step membranes are very similar, the two-step membranes permselectivity (ideal separation factor) for He/CO2 (69-319) and He/CH4 (585-958) are one to two orders of magnitude higher than the single-step membranes results of 2-7 and 69, respectively. The two-step membranes have high activation energy for He and H-2 permeance, in excess of 16 kJ mol(-1). The mobility energy for He permeance is three to six-fold higher for the two-step than the single-step membranes. As the mobility energy is higher for small pores than large pores and coupled with the permselectivity results, the two-step catalysed hydrolysis sol-gel process resulted in the formation of pore sizes in the region of 3 Angstrom while the single-step process tended to produce slightly larger pores. (C) 2002 Elsevier Science B.V. All rights reserved.

Scheduling of head-dependent cascaded reservoirs considering discharge ramping constraints and start/stop of units

This paper is on the problem of short-term hydro scheduling (STHS), particularly concerning head-dependent reservoirs under competitive environment. We propose a novel method, based on mixed-integer nonlinear programming (MINLP), for optimising power generation efficiency. This method considers hydroelectric power generation as a nonlinear function of water discharge and of the head. The main contribution of this paper is that discharge ramping constraints and start/stop of units are also considered, in order to obtain more realistic and feasible results. The proposed method has been applied successfully to solve two case studies based on Portuguese cascaded hydro systems, providing a higher profit at an acceptable computation time in comparison with classical optimisation methods based on mixed-integer linear programming (MILP).

A practical approach for profit-based unit commitment with emission limitations

This paper proposes a practical approach for profit-based unit commitment (PBUC) with emission limitations. Under deregulation, unit commitment has evolved from a minimum-cost optimisation problem to a profit-based optimisation problem. However, as a consequence of growing environmental concern, the impact of fossil-fuelled power plants must be considered, giving rise to emission limitations. The simultaneous address of the profit with the emission is taken into account in our practical approach by a multiobjective optimisation (MO) problem. Hence, trade-off Curves between profit and emission are obtained for different energy price profiles, in a way to aid decision-makers concerning emission allowance trading. Moreover, a new parameter is presented, ratio of change, and the corresponding gradient angle, enabling the proper selection of a compromise commitment for the units. A case study based on the standard IEEE 30-bus system is presented to illustrate the proficiency Of Our practical approach for the new competitive and environmentally constrained electricity supply industry.

Short-term electricity prices forecasting in a competitive market by a hybrid PSO-ANFIS approach

In this paper, a novel hybrid approach is proposed for electricity prices forecasting in a competitive market, considering a time horizon of 1 week. The proposed approach is based on the combination of particle swarm optimization and adaptive-network based fuzzy inference system. Results from a case study based on the electricity market of mainland Spain are presented. A thorough comparison is carried out, taking into account the results of previous publications, to demonstrate its effectiveness regarding forecasting accuracy and computation time. Finally, conclusions are duly drawn. (C) 2012 Elsevier Ltd. All rights reserved.

HVDC transmission systems: Bipolar back-to-back diode clamped multilevel converter with fastoptimum-predictive control and capacitor balancing strategy

Voltage source multilevel power converter structures are being considered for high power high voltage applications where they have well known advantages. Recently, full back-to-back connected multilevel neutral diode clamped converters (NPC) have been used in high voltage direct current (HVDC) transmission systems. Bipolar back-to-back connection of NPCs have advantages in long distance HVDC transmission systems, but highly increased difficulties to balance the dc capacitor voltage dividers on both sending and receiving end NPCs. This paper proposes a fast optimum-predictive controller to balance the dc capacitor voltages and to control the power flow in a long distance HVDCsystem using bipolar back-to-back connected NPCs. For both converter sides, the control strategy considers active and reactive power to establish ac grid currents on sending and receiving ends, while guaranteeing the balancing of both NPC dc bus capacitor voltages. Furthermore, the fast predictivecontroller minimizes the semiconductor switching frequency to reduce global switching losses. The performance and robustness of the new fast predictive control strategy and the associated dc capacitors voltage balancing are evaluated. (C) 2011 Elsevier B.V. All rights reserved.

Estudo de uma central hidroeléctrica com base em turbina hidráulica reversível

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Mecânica

Short-term electricity prices forecasting in a competetive market by a hybrid Pso-Anfis approach

In this paper, a novel hybrid approach is proposed for electricity prices forecasting in a competitive market, considering a time horizon of 1 week. The proposed approach is based on the combination of particle swarm optimization and adaptive-network based fuzzy inference system. Results from a case study based on the electricity market of mainland Spain are presented. A thorough comparison is carried out, taking into account the results of previous publications, to demonstrate its effectiveness regarding forecasting accuracy and computation time. Finally, conclusions are duly drawn.

Parallel GPU architecture for hyperspectral unmixing based on augmented Lagrangian method

Hyperspectral imaging has become one of the main topics in remote sensing applications, which comprise hundreds of spectral bands at different (almost contiguous) wavelength channels over the same area generating large data volumes comprising several GBs per flight. This high spectral resolution can be used for object detection and for discriminate between different objects based on their spectral characteristics. One of the main problems involved in hyperspectral analysis is the presence of mixed pixels, which arise when the spacial resolution of the sensor is not able to separate spectrally distinct materials. Spectral unmixing is one of the most important task for hyperspectral data exploitation. However, the unmixing algorithms can be computationally very expensive, and even high power consuming, which compromises the use in applications under on-board constraints. In recent years, graphics processing units (GPUs) have evolved into highly parallel and programmable systems. Specifically, several hyperspectral imaging algorithms have shown to be able to benefit from this hardware taking advantage of the extremely high floating-point processing performance, compact size, huge memory bandwidth, and relatively low cost of these units, which make them appealing for onboard data processing. In this paper, we propose a parallel implementation of an augmented Lagragian based method for unsupervised hyperspectral linear unmixing on GPUs using CUDA. The method called simplex identification via split augmented Lagrangian (SISAL) aims to identify the endmembers of a scene, i.e., is able to unmix hyperspectral data sets in which the pure pixel assumption is violated. The efficient implementation of SISAL method presented in this work exploits the GPU architecture at low level, using shared memory and coalesced accesses to memory.