Iberdrola Renovables was a subsidiary of Iberdrola, headquartered in Valencia, Spain, which included companies in the domains of renewable energy, particularly wind power. The firm was the world's largest renewable energy firm: it was the world's largest owner-operator of wind farms, but also operated in the solar, hydro, biomass and wave power industries..
The aim of this research is to complement and improve the results about ejection effect in a low-head hydropower plant from a previous study in physical models and to evaluate the effect of ejection on the turbine power and efficiency, in the model alternative with the best performance. The study covers four additional geometric alternatives, aside from the original design and the six already tested alternatives in that study, using 1:70 scale model tests. Three approaches were considered: (1) The development of a theoretical equation for the ejection effect, based on the equations of conservation of momentum and energy, (2) An assessment of an empirical relationship for the effective ejection using dimensionless flow parameters from 521 flow scenarios and (3) The development of two empirical relationships between the effective ejection and the power and efficiency increments of the HPP turbines (63 flow scenarios).
Randomization-based Machine Learning methods for prediction are currently a hot topic in Artificial Intelligence, due to their excellent performance in many prediction problems, with a bounded computation time. The application of randomization-based approaches to renewable energy prediction problems has been massive in the last few years, including many different types of randomization-based approaches, their hybridization with other techniques and also the description of new versions of classical randomization-based algorithms, including deep and ensemble approaches. In this paper we review the most important characteristics of randomization-based machine learning approaches and their application to renewable energy prediction problems. We describe the most important methods and algorithms of this family of modeling methods, and perform a critical literature review, examining prediction problems related to solar, wind, marine/ocean and hydro-power renewable sources. We support our critical analysis with an extensive experimental study, comprising real-world problems related to solar, wind and hydro-power energy, where randomization-based algorithms are found to achieve superior results at a significantly lower computational cost than other modeling counterparts. We end our survey with a prospect of the most important challenges and research directions that remain open this field, along with an outlook motivating further research efforts in this exciting research field.
This work analyzes the impact of the operation and maintenance procedure on the condition of gearbox oil. The analytical results reveals how different scenarios modify them. The analysis is based on key operational data collected from 30 different multi-megawatt wind turbines at different locations in Spain with a variety of technologies from different top-tier manufacturers. The study includes various situations and decisions, such as leakage and replacement of oil, offline filter installation, oil brand change, substitution of valves, and even the position where the sample is taken and how these situations can provoke false warnings that trigger modifications in the operation and maintenance of wind farms with new unnecessary tasks and costs. The experimental results conclude that complete and reliable information is crucial when warning about risk situations. It is not possible to take appropriate actions without accurate information and consequently the spread of the problem cannot be stopped.
Following from smaller-scale investigations of grid-forming converter control applied to wind turbines in 2017-2018, this study describes a much larger trial involving an entire wind farm, owned and operated by ScottishPower Renewables. To the authors' knowledge, this was the first UK converter-connected wind farm to operate in grid-forming mode, and the largest in the world to date. The 23-turbine, 69 MW farm ran in the grid-forming mode for 6 weeks, exploring inertia contributions between H = 0.2 s and H = 8 s. A number of unscheduled frequency disturbances occurred due to interconnector, combined cycle gas turbine (CCGT) and other trips, to which un-curtailed turbines were able to respond. In addition, several deliberate tests were carried out. The turbines were able to provide a stable and appropriate response at relatively high inertia levels to the frequency events commonly occurring today. The captured responses stimulated a debate as to whether external damping power might be required in a grid-forming converter, or whether internal damping is sufficient to allow stable and robust power-sharing with parallel devices in all grid event scenarios. Analysis in this study suggests that, practically, internal damping is probably appropriate, and that any deficiency in external damping power can be more than mitigated by reactance and/or droop-slope response-time management in the grid-forming converters.
The aim of this document is to present how the interpretation of the RVM (Recovery Voltage Measurement) test can be improved through the use of a Debye equivalent circuit. As it is described in the literature, the interpretation of the RVM test requires expertise and if the transformer presents a high interfacial polarization it is not possible to diagnose it in detail. The Debye model is proposed in this work for enhancing RVM interpretation. This model is based on an electrical circuit that includes basic R-C components, that allows two interesting features: on one hand, insulation physical effects can be separately represented and, on the other, the values of the R-C components can be calculated from the RVM response. A method is proposed in which using a sweep with a constant number of predefined time constants branches allows us to determine the areas of influence of the different compounds present in the dielectric. Finally, several case studies are presented, in which it is correlated a dielectric oil treatment carried out and the equivalent circuit changes using a sweep allows us to analyze different branches’ sensitivity and to identify the areas of influence of each compound.
