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Energy management within microgrids under the presence of large number of renewables such as photovoltaics is complicated due to uncertainties involved. Randomness in energy production and consumption make both the prediction and optimality of exchanges challenging. In this paper, we evaluate the impact of uncertainties on optimality of different robust energy exchange strategies. To address the problem, we present AIROBE, a data-driven system that uses machine-learning-based predictions of energy supply and demand as input to calculate robust energy exchange schedules using a multiband robust optimization approach to protect from deviations. AIROBE allows the decision maker to tradeoff robustness with stability of the system and energy costs. Our evaluation shows, how AIROBE can deal effectively with asymmetric deviations and how better prediction methods can reduce both the operational cost while at the same time may lead to increased operational stability of the system.

Abstract This work, framed in the IEA SHC Task 51 “Solar Energy in Urban Planning”, presents an illustrative perspective of solar energy in urban planning through the analysis of 34 international case studies conducted in 10 countries. The aim here is to examine challenges, barriers and opportunities for active solar systems and passive solar strategies by taking into consideration interrelated technical and non-technical aspects in ongoing and completed projects. It focuses on exposing potential pitfalls and illustrating lessons learned in case studies divided into three categories: (i) existing urban areas, (ii) new urban areas, and (iii) solar landscapes. The analysis has yielded insights into the solar energy strategy adoption, the evaluation of solar energy production, solar irradiation and daylighting, and the architectural quality, sensitivity and visibility of the solar systems for urban planning. The outcomes have implications to stimulate successful practices in implementing solar strategies in urban planning and facilitating their replicability worldwide by avoiding common mistakes.

Analyzing television discourse during 2021 through a statistical sample of records extracted from TV networks, the configuration that, in the pandemic, adjusted the dialectical mediation between television communication and cognitive capital available for resilience to Climate Change is revealed. This study originates from reports that in collaboration with ECODES and funding from the Ministry for the Ecological Transition and the Demographic Challenge, carried out by the Media Communication Observatory on Climate Change at its headquarters of the MDCS Research Group of the UCM. The analysis revealed how the causes, impacts, mitigation, and adaptation projects to the effects of climate change were communicated, and the identity of those who speak and/or are referred to. The discursive hegemony of mediators (journalists) and politicians is confirmed, to the detriment of scientists, and improved communication for resilience to climate change is promoted. ; Analizado el discurso televisivo durante 2021 a través de una muestra representativa de registros extraídos de cadenas de TV, se revela la configuración que, en la pandemia, ajustó la mediación dialéctica entre comunicación televisiva y capital cognitivo disponible para la resiliencia ante el Cambio Climático. Este estudio se origina en informes que en colaboración con ECODES y financiación del Ministerio para la Transición Ecológica y el Reto Demográfico, realiza el Observatorio de la Comunicación Mediática del Cambio Climático en su sede del Grupo de Investigación MDCS, de la UCM. El análisis desveló cómo se comunicaron las causas, los impactos, los proyectos de mitigación y adaptación ante los efectos del cambio climático, y la identidad de quienes toman la palabra y/o son aludidos. Se confirma la hegemonía discursiva de mediadores (periodistas) y políticos, en detrimento de los científicos, y se promueve mejorar la comunicación para la resiliencia ante el cambio climático.

There are different monitoring procedures in wind farms with two main objectives: (i) to improve energy production by the capability of the national electrical network and (ii) to reduce the stooped hours due to preventive and or corrective maintenance activities. In this sense, different sensors are employed to sample in real-time the working conditions of equipment, the electrical production and the weather conditions. Despite this, just the anemometer measurement can be related to the more important errors of interruption of power regulation and anemometer errors. Both errors are related to gusty winds and contribute to more than 33% of the cost of a wind farm. The present paper reports some mathematical relations between weather and maintenance but there are no extreme values of each variable that let us predict a near failure and its corresponding loss of working hours. To achieve this, statistical analysis identifies the relation between weather variables and errors and different models are obtained. What is more, due to the difficulty and economic implications involving the implementation of complex algorithms and techniques of artificial intelligence, it is still a challenge to optimize this process. Finally, the obtained results show a particular case study that can be extrapolated to other wind farms after different case studies to adjust the model to different weather regions, and serve as a useful tool for weather maintenance.

Municipal solid waste (MSW) management in Spain, particularly in the Valencian Community, heavily relies on mechanical–biological treatment (MBT) plants followed by landfill disposal. These MBT facilities utilize mechanical processes like shredding, screening, and sorting to segregate recyclables (metals, plastics, paper) from organic material and other nonrecyclables. While public funding supports these plants, private entities manage them through complex, long-term concession contracts. This structure restricts access to crucial data on the sale prices of the byproducts generated during MBT. Publicly available information on relevant company and administration websites is typically absent, hindering transparency surrounding byproduct revenue. This study addresses this gap by analyzing 2012’s available data on revenues obtained from byproduct sales following mechanical treatment at MBT plants within the Valencian Community and comparing them with Spanish national data. This research revealed a significant finding—the statistical distribution of average prices obtained from Ecoembes auctions in the Valencian Community mirrored the corresponding distribution for prices calculated from auctions conducted in other Spanish regions. This suggests a potential uniformity in byproduct pricing across the country. It has also been found that none of the analyzed price distributions exhibited a normal (Gaussian) distribution. The findings also highlight the need for alternative pricing models that move beyond simple averages and account for regional variations and outliers. As actual prices are not available after 2012, this lack of transparency poses a challenge in comprehensively evaluating the economic viability of MBT plants. Furthermore, it raises concerns regarding whether the revenue generated from byproduct sales reflects fair market value. Limited public access to this information can potentially indicate conflicts of interest or inefficiencies within the waste management system.

Bromine and chlorine are almost ubiquitous in waste of electrical and electronic equipment (WEEE) and the knowledge of their content in the plastic fraction is an essential step for proper end of life management. The aim of this study is to compare the following analytical methods: energy dispersive X-ray fluorescence spectroscopy (ED-XRF), ion chromatography (IC), ion-selective electrodes (ISEs), and elemental analysis for the quantitative determination of chlorine and bromine in four real samples taken from different WEEE treatment plants, identifying the best analytical technique for waste management workers. Home-made plastic standard materials with known concentrations of chlorine or bromine have been used for calibration of ED-XRF and to test the techniques before the sample analysis. Results showed that IC and ISEs, based upon dissolution of the products of the sample combustion, have not always achieved a quantitative absorption of the analytes in the basic solutions and that bromine could be underestimated since several oxidation states occur after combustion. Elemental analysis designed for chlorine determination is subjected to strong interference from bromine and required frequent regeneration and recalibration of the measurement cell. The most reliable method seemed to be the non-destructive ED-XRF. Calibration with home-made standards, having a similar plastic matrix of the samples, enabled us to carry out quantitative determinations, which have been revealed to be satisfactorily accurate and precise. In all the analyzed samples a total concentration of chlorine and/or bromine between 0.6 and 4 w/w% was detected, compromising the feasibility of a mechanical recycling and suggesting the exploration of an alternative route for managing these plastic wastes.