Julio J. Melero

Combined system for reactive power control in wind farms

Operation of wind turbine installations may affect the steady-state voltage in the connected network. The voltage fluctuations imposed by the wind farm will depend on the characteristics of the grid. This paper presents a combined system of a capacitor, a thyristor controlled reactor (TCR) and a small-rated active filter (PWM-VSI) whose goal is to obtain a regulation of reactive power in wind farms with a generation of harmonic currents very reduced. The electrical analysis and filtering characteristics are discussed theoretically and several situations are simulated.

Data-driven learning framework for associating weather conditions and wind turbine failures

Abstract The need for cost effective operation and maintenance (O&M) strategies in wind farms has risen significantly with the growing wind energy sector. In order to decrease costs, current practice in wind farm O&M is switching from corrective and preventive strategies to rather predictive ones. Anticipating wind turbine (WT) failures requires sophisticated models to understand the complex WT component degradation processes and to facilitate maintenance decision making. Environmental conditions and their impact on WT reliability play a significant role in these processes and need to be investigated profoundly. This paper is presenting a framework to assess and correlate weather conditions and their effects on WT component failures. Two approaches, using (a) supervised and (b) unsupervised data mining techniques are applied to pre-process the weather and failure data. An apriori rule mining algorithm is employed subsequently, in order to obtain logical interconnections between the failure occurrences and the environmental data, for both approaches. The framework is tested using a large historical failure database of modern wind turbines. The results show the relation between environmental parameters such as relative humidity, ambient temperature, wind speed and the failures of five major WT components: gearbox, generator, frequency converter, pitch and yaw system. Additionally, the performance of each technique, associating weather conditions and WT component failures, is assessed.

Selection of the Most Suitable Decomposition Filter for the Measurement of Fluctuating Harmonics

The proliferation of nonlinear loads in both industrial and residential distribution grids leads to undesirable nonsinusoidal and fluctuating harmonic pollution on voltage and current waveforms. New analysis tools, such as wavelets, are being used to overcome the problems posed by the use of the Fourier transform when analyzing complex waveforms. Nevertheless, the selection of the wavelet basis must be done carefully to minimize spectral leakage due to the nonexact frequency discrimination. In this context, this paper proposes an objective method for comparing different wavelet families for the measurement of harmonic contents. This methodology is applicable for determining the best filter among the 53 preselected structures according to the following requirements: frequency selectivity, computational complexity, convolution results, and observed spectral leakage. With all these considerations, the Butterworth infinite-impulse response filter of order 29 was found to be the best wavelet decomposition structure to achieve an effective harmonic analysis up to the 50th order.

On the use of high-frequency SCADA data for improved wind turbine performance monitoring

SCADA-based condition monitoring of wind turbines facilitates the move from costly corrective repairs towards more proactive maintenance strategies. In this work, we advocate the use of high-frequency SCADA data and quantile regression to build a cost effective performance monitoring tool. The benefits of the approach are demonstrated through the comparison between state-of-the-art deterministic power curve modelling techniques and the suggested probabilistic model. Detection capabilities are compared for low and high-frequency SCADA data, providing evidence for monitoring at higher resolutions. Operational data from healthy and faulty turbines are used to provide a practical example of usage with the proposed tool, effectively achieving the detection of an incipient gearbox malfunction at a time horizon of more than one month prior to the actual occurrence of the failure.

The financial benefits of various catastrophic failure prevention strategies in a wind farm: Two market studies (UK-Spain)

Operation of wind farms is driven by the overall aim of minimising costs while maximising energy sales. However, in certain circumstances investments are required to guarantee safe operation and survival of an asset. In this paper, we discuss the merits of various catastrophic failure prevention strategies in a Spanish wind farm. The wind farm operator was required to replace blades in two phases: temporary and final repair. We analyse the power performance of the turbine in the different states and investigate four scenarios with different timing of temporary and final repair during one year. The financial consequences of the scenarios are compared with a baseline by using a discounted cash flow analysis that considers the wholesale electricity market selling prices and interest rates. A comparison with the UK electricity market is conducted to highlight differences in the rate of return in the two countries.

Statistical Evaluation of SCADA data for Wind Turbine Condition Monitoring and Farm Assessment

Operational data from wind farms is crucial for wind turbine condition monitoring and performance assessment. In this paper, we analyse three wind farms with the aim to monitor environmental and operational conditions that might result in underperformance or failures. The assessment includes a simple wind speed characterisation and wake analysis. The evolution of statistical parameters is used to identify anomalous turbine behaviour. In total, 88 turbines and 12 failures are analysed, covering different component failures. Notwithstanding the short period of data available, several operational parameters are found to deviate from the farm trend in some turbines affected by failures. As a result, some parameters show better monitoring capabilities than others, for the detection of certain failures. However, the limitations of SCADA statistics are also shown as not all failures showed anomalies in the observed parameters.

Phase transitions in the (Cs1−xRbx)2ZnI4 system

Abstract(Cs1−xRbx)2ZnI4 crystals were grown by two different methods with Rb concentrations varying from x=0 to 2.5%. 127I NQR and calorimetric measurements showed that crystals grown by the Bridgman technique contain residual impurities (∼0.5%) for all x. While x=0 crystals grown from solution do not contain detectable impurities, they allow incorporation only of a low Rb concentration, not above 0.5%. A transition-temperature-concentration (x) phase diagram has been constructed for Bridgman-grown crystals from NQR data. Rb doping shifts the normal-incommensurate and incommensurate-ferroelastic phase-transition points toward higher temperatures with different rates. The P21/m↔P1 first-order transition shifts toward lower temperatures. The region of low Rb concentrations lies closest to the critical point.