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The main aim of the Horizon Europe Fit4Micro Project is to develop a microCHCP unit running on sustainable liquid biofuels. The application of this unit is foreseen at multi-family houses and at remote or off-grid locations. This technology will lead to very high electrical efficiencies (>40%) and a flexible heat/power ratio. Moreover, the usage of a truly advanced and RED II compliant biofuel will guarantee a high GHG emission reduction. This flexible hybrid energy system is based on a double-shaft micro gas turbine (mGT) combined with a novel humidification unit, and will be able to provide renewable heating, cooling and power production, mainly for domestic usage. The Fit4Micro solution contributes to make Europe the first enabled circular, climate-neutral and sustainable economy. Proceedings of the 31st European Biomass Conference and Exhibition, 5-8 June 2023, Bologna, Italy, pp. 514-516

Wind turbine performance monitoring is a complex task because of the non-stationary operation conditions and because the power has a multivariate dependence on the ambient conditions and working parameters. This motivates the research about the use of SCADA data for constructing reliable models applicable in wind turbine performance monitoring. The present work is devoted to multivariate wind turbine power curves, which can be conceived of as multiple input, single output models. The output is the power of the target wind turbine, and the input variables are the wind speed and additional covariates, which in this work are the blade pitch and rotor speed. The objective of this study is to contribute to the formulation of multivariate wind turbine power curve models, which conjugate precision and simplicity and are therefore appropriate for industrial applications. The non-linearity of the relation between the input variables and the output was taken into account through the simplification of a polynomial LASSO regression: the advantages of this are that the input variables selection is performed automatically. The k-means algorithm was employed for automatic multi-dimensional data clustering, and a separate sub-model was formulated for each cluster, whose total number was selected by analyzing the silhouette score. The proposed method was tested on the SCADA data of an industrial Vestas V52 wind turbine. It resulted that the most appropriate number of clusters was three, which fairly resembles the main features of the wind turbine control. As expected, the importance of the different input variables varied with the cluster. The achieved model validation error metrics are the following: the mean absolute percentage error was in the order of 7.2%, and the average difference of mean percentage errors on random subsets of the target data set was of the order of 0.001%. This indicates that the proposed model, despite its simplicity, can be reliably employed for wind turbine power monitoring and for evaluating accumulated performance changes due to aging and/or optimization.

Presentation of the Conference Paper: HYPERION: A Decision Support System for Improved Resilience and sustainable Reconstruction of historic areas in the Adapt Northern Heritage Conference 202 at Edinburgh, Scotland.

The Arctic climate system is in great distress, warming faster than the rest of the world and transforming more rapidly than previously anticipated. Sustained and harmonized multidisciplinary observations at key locations are needed to fill knowledge gaps and evaluate the ongoing climate change impacts on the complex Arctic marine system. For more than a decade, the Distributed Biological Observatory (DBO) has functioned as a “detection array” for ecosystem changes and trends in the Pacific sector of the Arctic Ocean. This long-term collaborative initiative builds on active involvement of scientists conducting in situ observations within marine disciplines to systematically document how the arctic marine ecosystem is transforming with environmental change. The DBO concept is currently being expanded into other sectors of the Arctic, including Davis Strait and Baffin Bay, the Atlantic Arctic gateway area, and the East Siberian Sea. Through increased collaboration and joint practices, findings from these regional areas can leverage to pan-Arctic perspectives and improve our understanding of the entire Arctic Ocean. Common practices are now being developed, including key phenomena and relevant indicators to study. Also, we strive towards harmonized routines for sampling, analysis and data sharing to increase the comparability across both disciplines and regions, and to improve the usability of our in-situ observations also for the modelling and remote sensing scopes. An ambition is, moreover, to expand from today's predominantly open-sea coverage towards coastal regions, to the benefit of both local communities and researchers. The process of establishing a pan-Arctic DBO network is to a large part facilitated by the EU Horizon project Arctic PASSION (2022-2025). Here, we present the latest developments and shared priorities, as well as our vision of how to incorporate our efforts into other parallel processes aiming to strengthen the pan-Arctic observing system towards, during and beyond the upcoming IPY.

A new out-of-step relaying concept has been previously reported. The concept involves augmaenting apparent resistance (R) measurement with rate-of-change of apparent resistance (Rdot) computation. The new R-Rdot relay thus has more intelligence for control decisions. This follow-up paper presents the following new information: large scale simulation results, including use of relay outputs for discrete supplemental control action; additional details on design and testing of the microprocessor based relay; and experience during an extensive monitoring period at Malin Substation on the Pacific AC Intertie. The relay is now energized for initiating controlled separations at several locations within the Western North American Power System.

The paper presents the results of a literature review on how social media can impact on disaster risk perception and vulnerability and how these two aspects are interconnected, trying to understand what factors have consequences especially on informational vulnerability. The paper answers to the increasing requests at an international level to move from a technocratic approach to disaster risk management and reduction to a holistic one, where social perspective is integrated. The paper states that this change of paradigm is relevant, especially considering the role that new technologies in communication and information systems are acquiring in disaster risk management and reduction. What emerges from the literature review is that there is a limited scientific production on the topic and further works are desired, to improve knowledge on how new communication and information technologies can impact on vulnerability and risk perception. Furthermore, the two topics are usually discussed separately. However, the role that risk perception can have in increasing or reducing vulnerability deserves to be better discussed.

AbstractXylella fastidiosais a bacterium that infects crops like grapevines, coffee, almonds, citrus and olives, causing economically devastating damage. There is, however, little understanding of the genes that contribute to resistance, the genomic architecture of resistance, and the potential role of climate in shaping resistance, in part because major crops like grapevines (V. vinifera) are not resistant to the bacterium. Here we studied a wild grapevine species,Vitis arizonica, that segregates for resistance toX. fastidiosa. Using genome-wide association, we identified candidate genes that mediate the host response toX. fastidiosainfection. We uncovered evidence that resistance requires genes from multiple genomic regions, based on data from breeding populations and from additionalVitisspecies. We also inferred that resistance evolved more than once in the wild, suggesting that wildVitisspecies may be a rich source for resistance alleles and mechanisms. Finally, resistance inV. arizonicawas climate dependent, because individuals from low (< 10°C) temperature locations in the wettest quarter were typically susceptible to infection, likely reflecting a lack of pathogen pressure in these climates. Surprisingly, climate was nearly as effective a predictor of resistance phenotypes as some genetic markers. This work underscores that pathogen pressure is likely to increase with climate, but it also provides genetic insight and tools for breeding and transforming resistant crops.