Z-source converter based grid-interface for variable-speed permanent magnet wind turbine generators

A Z-source inverter based grid-interface for a variable-speed wind turbine connected to a permanent magnet synchronous generator is proposed. A control system is designed to harvest maximum wind energy under varied wind conditions with the use of the permanent magnet synchronous generator, diode-rectifier and Z-source inverter. Control systems for speed regulation of the generator and for DC- and AC- sides of the Z-source inverter are investigated using computer simulations and laboratory experiments. Simulation and experimental results verify the efficacy of the proposed approach.

Three-dimensional off-design numerical analysis of an organic Rankine cycle radial-inflow turbine

Optimisation of organic Rankine cycles(ORCs for binary cycle applications could play a major role in determining the competitiveness of low to moderate renewable sources. An important aspect of the optimisation is to maximise the turbine output power for a given resource. This requires careful attention to the turbine design notably through numerical simulations. Challenges in the numerical modelling of radial-inflow turbines using high-density working fluids still need to be addressed in order to improve the turbine design and better optimise ORCs. Thispaper presents preliminary 3D numerical simulations of a high-density radial-inflow ORC turbine in sensible geothermal conditions. Following extensive investigation of the operating conditions and thermodynamic cycle analysis, therefrigerant R143a is chosen as the high-density working fluid. The 1D design of the candidate radial-inflow turbine is presented in details. Furthermore, commercially-available software Ansys-CFX is used to perform preliminary steady-state 3D CFD simulations of the candidate R143a radial-inflow turbine for a number of operating conditions including off-design conditions. The real-gas properties are obtained using the Peng–Robinson equations of state.The thermodynamic ORC cycle is presented. The preliminary design created using dedicated radial-inflow turbine software Concepts-Rital is discussed and the 3D CFD results are presented and compared against the meanline analysis.

Application of anomaly technique in wind turbine bearing fault detection

Bearing faults are the most common cause of wind turbine failures. Unavailability and maintenance cost of wind turbines are becoming critically important, with their fast growing in electric networks. Early fault detection can reduce outage time and costs. This paper proposes Anomaly Detection (AD) machine learning algorithms for fault diagnosis of wind turbine bearings. The application of this method on a real data set was conducted and is presented in this paper. For validation and comparison purposes, a set of baseline results are produced using the popular one-class SVM methods to examine the ability of the proposed technique in detecting incipient faults.

Fault detection of wind turbine drivetrain utilizing power-speed characteristics

Wind energy, being the fastest growing renewable energy source in the present world, requires a large number of wind turbines to transform wind energy into electricity. One factor driving the cost of this energy is the reliable operation of these turbines. Therefore, it is a growing requirement within the wind farm community, to monitor the operation of the wind turbines on a continuous basis so that a possible fault can be detected ahead of time. As the wind turbine operates in an environment of constantly changing wind speed, it is a challenging task to design a fault detection technique which can accommodate the stochastic operational behavior of the turbines. Addressing this issue, this paper proposes a novel fault detection criterion which is robust against operational uncertainty, as well as having the ability to quantify severity level specifically of the drivetrain abnormality within an operating wind turbine. A benchmark model of wind turbine has been utilized to simulate drivetrain fault condition and effectiveness of the proposed technique has been tested accordingly. From the simulation result it can be concluded that the proposed criterion exhibits consistent performance for drivetrain faults for varying wind speed and has linear relationship with the fault severity level.

MATLAB/Simulink simulation and C2000 code generation model for a grid-interactive 3-phase 4-wire inverter

This work is a MATLAB/Simulink model of a controller for a three-phase, four-wire, grid-interactive inverter. The model provides capacity for simulating the performance of power electroinic hardware, as well as code generation for an embedded controller. The implemented hardware topology is a three-leg bridge with a neutral connection to the centre-tap of the DC bus. An LQR-based current controller and MAF-based phase detector are implemented. The model is configured for code generation for a Texas Instruments TMS320F28335 Digital Signal Processor (DSP).

Robust design and optimisation of a radial turbine within a supercritical CO2 solar Brayton Cycle

The generation of solar thermal power is dependent upon the amount of sunlight exposure,as influenced by the day-night cycle and seasonal variations. In this paper, robust optimisation is applied to the design of a power block and turbine, which is generating 30 MWe from a concentrated solar resource of 560oC. The robust approach is important to attain a high average performance (minimum efficiency change) over the expected operating ranges of temperature, speed and mass flow. The final objective function combines the turbine performance and efficiency weighted by the off-design performance. The resulting robust optimisation methodology as presented in the paper gives further information that greatly aids in the design of non-classical power blocks through considering off-design conditions and resultant performance.

Stochastic analysis of a radial-inflow turbine in the presence of parametric uncertainties

This paper presents an uncertainty quantification study of the performance analysis of the high pressure ratio single stage radial-inflow turbine used in the Sundstrand Power Systems T-100 Multi-purpose Small Power Unit. A deterministic 3D volume-averaged Computational Fluid Dynamics (CFD) solver is coupled with a non-statistical generalized Polynomial Chaos (gPC) representation based on a pseudo-spectral projection method. One of the advantages of this approach is that it does not require any modification of the CFD code for the propagation of random disturbances in the aerodynamic and geometric fields. The stochastic results highlight the importance of the blade thickness and trailing edge tip radius on the total-to-static efficiency of the turbine compared to the angular velocity and trailing edge tip length. From a theoretical point of view, the use of the gPC representation on an arbitrary grid also allows the investigation of the sensitivity of the blade thickness profiles on the turbine efficiency. The gPC approach is also applied to coupled random parameters. The results show that the most influential coupled random variables are trailing edge tip radius coupled with the angular velocity.

A 4-DOF SIMULINK model of a coastal patrol vessel for manoeuvring in waves

This paper presents a detailed simulation model of a Naval coastal patrol vessel. The vessel described is a 50m long, fast monohull coastal patrol vessel. The paper describes the complete model and its implementation in Matlab-Simulink. In order to promote the use of this model, the Simulink files are openly available through a website.

Analysis Of The Hvdc Turbine Generator Torsional Interactions

In the recent past it has been found that HVDC transmission systems and turbine-generator shaft torsional dynamics can interact in an unfavourable manner. This paper presents a detailed linearised state space model of AC/DC system to study this torsional interaction. The model developed is used to study the effect of various system parameters, such as, dc line loading, converter firing angle, the firing scheme employed. The results obtained are compared with those given in[3].

Gas turbine diagnostics using a soft computing approach

A fuzzy system is developed using a linearized performance model of the gas turbine engine for performing gas turbine fault isolation from noisy measurements. By using a priori information about measurement uncertainties and through design variable linking, the design of the fuzzy system is posed as an optimization problem with low number of design variables which can be solved using the genetic algorithm in considerably low amount of computer time. The faults modeled are module faults in five modules: fan, low pressure compressor, high pressure compressor, high pressure turbine and low pressure turbine. The measurements used are deviations in exhaust gas temperature, low rotor speed, high rotor speed and fuel flow from a base line 'good engine'. The genetic fuzzy system (GFS) allows rapid development of the rule base if the fault signatures and measurement uncertainties change which happens for different engines and airlines. In addition, the genetic fuzzy system reduces the human effort needed in the trial and error process used to design the fuzzy system and makes the development of such a system easier and faster. A radial basis function neural network (RBFNN) is also used to preprocess the measurements before fault isolation. The RBFNN shows significant noise reduction and when combined with the GFS leads to a diagnostic system that is highly robust to the presence of noise in data. Showing the advantage of using a soft computing approach for gas turbine diagnostics.

Breakup of drops around the edges of Rushton turbine

A detailed experimental and simulation study has been carried out in the present work to understand drop breakup in regions around the edge of the Rushton turbine in agitated vessels. The effect of impeller speed, impeller size, interfacial tension, and the viscosities of the two phases is studied on drop breakup through their effect on dmax, the size of the largest drop in the system, and the whole size distribution. The measurements were carried out using Galai particle size analyser and optical microscope. Experimental analysis shows that the dmax, maximum stable drop diameter varies with impeller tip velocity to the power -1. The variation of dmax with interfacial tension is studied using different surfactants. The effect of viscosity ratio, achieved by changing the dispersed phase viscosity, on dmax is captured. For the same dmax values obtained from two different dispersed phases show that the wider drop size distribution is observed for higher dispersed phase viscosity.

Three- and Seven-Point Optimally Weighted Recursive Median Filters for Gas Turbine Diagnostics

Measured health signals incorporate significant details about any malfunction in a gas turbine. The attenuation of noise and removal of outliers from these health signals while preserving important features is an important problem in gas turbine diagnostics. The measured health signals are a time series of sensor measurements such as the low rotor speed, high rotor speed, fuel flow, and exhaust gas temperature in a gas turbine. In this article, a comparative study is done by varying the window length of acausal and unsymmetrical weighted recursive median filters and numerical results for error minimization are obtained. It is found that optimal filters exist, which can be used for engines where data are available slowly (three-point filter) and rapidly (seven-point filter). These smoothing filters are proposed as preprocessors of measurement delta signals before subjecting them to fault detection and isolation algorithms.

Fuzzy logic intelligent system for gas turbine module and system fault isolation

A fuzzy logic intelligent system is developed for gas-turbine fault isolation. The gas path measurements used for fault isolation are exhaust gas temperature, low and high rotor speed, and fuel flow. These four measurements are also called the cockpit parameters and are typically found in almost all older and newer jet engines. The fuzzy logic system uses rules developed from a model of performance influence coefficients to isolate engine faults while accounting for uncertainty in gas path measurements. It automates the reasoning process of an experienced powerplant engineer. Tests with simulated data show that the fuzzy system isolates faults with an accuracy of 89% with only the four cockpit measurements. However, if additional pressure and temperature probes between the compressors and before the burner, which are often found in newer jet engines, are considered, the fault isolation accuracy rises to as high as 98%. In addition, the additional sensors are useful in keeping the fault isolation system robust as quality of the measured data deteriorates.