Historical Evolution of theWave Resource and Energy Production off the Chilean Coast over the 20th Century

The wave energy resource in the Chilean coast shows particularly profitable characteristics for wave energy production, with relatively high mean wave power and low inter-annual resource variability. This combination is as interesting as unusual, since high energetic locations are usually also highly variable, such as the west coast of Ireland. Long-term wave resource variations are also an important aspect when designing wave energy converters (WECs), which are often neglected in resource assessment. The present paper studies the long-term resource variability of the Chilean coast, dividing the 20th century into five do-decades and analysing the variations between the different do-decades. To that end, the ERA20C reanalysis of the European Centre for Medium-Range Weather Forecasts is calibrated versus the ERA-Interim reanalysis and validated against buoy measurements collected in different points of the Chilean coast. Historical resource variations off the Chilean coast are compared to resource variations off the west coast in Ireland, showing a significantly more consistent wave resource. In addition, the impact of historical wave resource variations on a realistic WEC, similar to the Corpower device, is studied, comparing the results to those obtained off the west coast of Ireland. The annual power production off the Chilean coast is demonstrated to be remarkably more regular over the 20th century, with variations of just 1% between the different do-decades.The authors with the Centre for Ocean Energy Research in Maynooth University are supported by Science Foundation Ireland under Grant No. 13/IA/1886. It is also supported by grant CGL2016-76561-R, MINECO/ERDF, UE. Additional funding was received from the University of Basque Country (UPV/EHU, GIU17/002)

MIDAS: A Benchmarking Multi-Criteria Method for the Identification of Defective Anemometers in Wind Farms

A novel multi-criteria methodology for the identification of defective anemometers is shown in this paper with a benchmarking approach: it is called MIDAS: multi-technique identification of defective anemometers. The identification of wrong wind data as provided by malfunctioning devices is very important, because the actual power curve of a wind turbine is conditioned by the quality of its anemometer measurements. Here, we present a novel method applied for the first time to anemometers’ data based on the kernel probability density function and the recent reanalysis ERA5. This estimation improves classical unidimensional methods such as the Kolmogorov–Smirnov test, and the use of the global ERA5’s wind data as the first benchmarking reference establishes a general method that can be used anywhere. Therefore, adopting ERA5 as the reference, this method is applied bi-dimensionally for the zonal and meridional components of wind, thus checking both components at the same time. This technique allows the identification of defective anemometers, as well as clear identification of the group of anemometers that works properly. After that, other verification techniques were used versus the faultless anemometers (Taylor diagrams, running correlation and RMSE RMSE , and principal component analysis), and coherent results were obtained for all statistical techniques with respect to the multidimensional method. The developed methodology combines the use of this set of techniques and was able to identify the defective anemometers in a wind farm with 10 anemometers located in Northern Europe in a terrain with forests and woodlands. Nevertheless, this methodology is general-purpose and not site-dependent, and in the future, its performance will be studied in other types of terrain and wind farmsThis work was financially supported by the Spanish Government through the MINECO project CGL2016-76561-R (MINECO/ERDF, UE), the University of the Basque Country through the Euskoiker PT10477 and GIU 17/002 contracts, and the project DIANEMOS of the Council of Gipuzkoa with Maxwind-Hispavista. ERA5 data were downloaded at no cost from the MARSserver of the ECMWF. Most of the calculations were carried out in the framework of

Adaptive Control of HVDC Transmission Systems -- Designing a stability-preserving energy-balancing outer loop

The large-scale introduction of offshore renewable generation will indeed require a multi-terminal HVDC transmission system—based on voltage source (power) converters—in order to efficiently transfer the offshore power to shore over long distances. The conventional power converter control solutions associated to this technology (typically based on standard current control methods) have been designed to satisfactory operate near a single nominal operating point. This makes them inherently unsuitable for guaranteeing uninterrupted operation (stability) of the system in the event of an unexpected large signal-disturbance. Moreover, the offshore HVDC grid architecture complexity is expected to increase as more lines and renewable energy sources are connected to the grid. It then seems desirable to find control alternatives able to operate the system with large-signal stability guarantees, preserved regardless of any topological change or system disturbance size—and therefore avoiding any costly operational interruption of the system. This manuscript presents the Energy Balance Based Adaptive (EBBA) outer-loop rooted in the Immersion & Invariance methodology, which replaces the traditional outer-loops while preserving the large-signal stability certificate on 2-Level VSCs. This novel controller places particular emphasis on the estimation of the system parameters, crucial for the converter load-flow computation. Additionally, for the development of this Master’s Thesis port-Hamiltonian representation, Lyapunov theory and Passivity Based Control strategy are used