Neural network controlled three-phase four-wire shunt active powerfilter

A three-phase four-wire shunt active power filter for harmonic mitigation and reactive power compensation in power systems supplying nonlinear loads is presented. Three adaptive linear neurons are used to tackle the desired three-phase filter current templates. Another feedforward three-layer neural network is adopted to control the output filter compensating currents online. This is accomplished by producing the appropriate switching patterns of the converter's legs IGBTs. Adequate tracking of the filter current references is obtained by this method. The active filter injects the current required to compensate for the harmonic and reactive components of the line currents, Simulation results of the proposed active filter indicate a remarkable improvement in the source current waveforms. This is reflected in the enhancement of the unified power quality index defined. Also, the filter has exhibited quite a high dynamic response for step variations in the load current, assuring its potential for real-time applications

An ESPRIT-SAA-Based Detection Method for Broken Rotor Bar Fault in Induction Motors

This paper presents a novel detection method for broken rotor bar fault (BRB) in induction motors based on Estimation of Signal Parameters via Rotational Invariance Technique (ESPRIT) and Simulated Annealing Algorithm (SAA). The performance of ESPRIT is tested with simulated stator current signal of an induction motor with BRB. It shows that even with a short-time measurement data, the technique is capable of correctly identifying the frequencies of the BRB characteristic components but with a low accuracy on the amplitudes and initial phases of those components. SAA is then used to determine their amplitudes and initial phases and shows satisfactory results. Finally, experiments on a 3kW, 380V, 50Hz induction motor are conducted to demonstrate the effectiveness of the ESPRIT-SAA-based method in detecting BRB with short-time measurement data. It proves that the proposed method is a promising choice for BRB detection in induction motors operating with small slip and fluctuant load.

Discrete Conditional Phase-type models utilising classification trees: Application to modelling health service capacities

Discrete Conditional Phase-type (DC-Ph) models consist of a process component (survival distribution) preceded by a set of related conditional discrete variables. This paper introduces a DC-Ph model where the conditional component is a classification tree. The approach is utilised for modelling health service capacities by better predicting service times, as captured by Coxian Phase-type distributions, interfaced with results from a classification tree algorithm. To illustrate the approach, a case-study within the healthcare delivery domain is given, namely that of maternity services. The classification analysis is shown to give good predictors for complications during childbirth. Based on the classification tree predictions, the duration of childbirth on the labour ward is then modelled as either a two or three-phase Coxian distribution. The resulting DC-Ph model is used to calculate the number of patients and associated bed occupancies, patient turnover, and to model the consequences of changes to risk status.

Use of a rotating disc reactor to investigate the heterogeneously catalysed oxidation of cinnamyl alcohol in toluene and ionic liquids

To evaluate the effect of mass transfer limitations in the three-phase oxidation of cinnamyl alcohol carried out in toluene and an ionic liquid (1-butyl-3-methyl-imidazolium bis(trifluoromethylsulphonyl)imide), studies have been performed in a rotating disc reactor and compared with those carried out in a stirred tank reactor where mass transfer effects are considered negligible. High catalyst efficiencies are found in the stirred tank reactor with the use of both ionic liquid and toluene, although there is a decrease in rate for the ionic liquid reactions. In contrast, internal pore diffusion limits the reaction in both solvents in the rotating disc reactor. This mass transfer resistance reduces the problem of overoxidation of the metal surface when the reaction is carried out in toluene, leading to significantly higher rates of reaction than expected, although at the cost of decreased selectivity.

Learning Bayesian networks from data: An information-theory based approach

This paper provides algorithms that use an information-theoretic analysis to learn Bayesian network structures from data. Based on our three-phase learning framework, we develop efficient algorithms that can effectively learn Bayesian networks, requiring only polynomial numbers of conditional independence (CI) tests in typical cases. We provide precise conditions that specify when these algorithms are guaranteed to be correct as well as empirical evidence (from real world applications and simulation tests) that demonstrates that these systems work efficiently and reliably in practice.

Universal power quality manager with a new control scheme

A new universal power quality manager is proposed. The proposal treats a number of power quality problems simultaneously. The universal manager comprises a combined series and shunt three-phase PWM controlled converters sharing a common DC link. A control scheme based on fuzzy logic is introduced and the general features of the design and operation processes are outlined. The performance of two configurations of the proposed power quality manager are compared in terms of a recently formulated unified power quality index. The validity and integrity of the proposed system is proved through computer simulated experiments

Current transients in the small salient-pole alternator caused by sudden short-circuit and synchronisation events

Small salient-pole machines, in the range 30 kVA to 2 MVA, are often used in distributed generators, which in turn are likely to form the major constituent of power generation in power system islanding schemes or microgrids. In addition to power system faults, such as short-circuits, islanding contains an inherent risk of out-of-synchronism re-closure onto the main power system. To understand more fully the effect of these phenomena on a small salient-pole alternator, the armature and field currents from tests conducted on a 31.5 kVA machine are analysed. This study demonstrates that by resolving the voltage difference between the machine terminals and bus into direct and quadrature axis components, interesting properties of the transient currents are revealed. The presence of saliency and short time-constants cause intriguing differences between machine events such as out-of-phase synchronisations and sudden three-phase short-circuits.

Improved Direct Power Control of Grid Connected DC/AC Converters

This paper proposes new direct power control (DPC) strategies for three-phase DC/AC converters with improved dynamic response and steady-state performance. As with an electrical machine, source and converter flux which equal the integration of the respective source and converter voltage are used to define active and reactive power flow. Optimization of the look-up-table used in conventional DPC is outlined first, to improve the power control and reduce the current distortion. Then constant switching frequency DPC is developed where the required converter voltage vector within a fixed half switching period is calculated directly from the active and reactive power errors. Detailed angle compensation due to the finite sampling frequency and the use of integral controller to further improve the power control accuracy, are described. Both simulation and experimental results are used to compare conventional DPC and vector control, and to demonstrate the effectiveness and robustness of the proposed control strategies during active and reactive power steps, and line inductance variations.