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A Comparative Analysis of the Market Bidding Decisions of Operational Pv Plants during Near-Zero Prices in the Spanish Electricity Markets
No full textPublisher Copyright: © 2025 IEEE.Nowadays, Day-Ahead market price cannibalization particularly affects photovoltaic (PV) plants, as this phenomenon impacts the revenue per unit of energy. However, renewable assets can participate in balancing services to increase their market revenues. Despite many research articles proposed complex optimization techniques, the market bidding of operational PV assets remains unsophisticated nowadays. This article studies and compares the market strategies of PV plants during near-zero price days in Spain, highlighting how these PV plants, despite having similar characteristics, operate with significantly different market decisions. It concludes that participation in balancing markets increases solar value by capturing higher revenues. Solar trackers also enhance daily solar generation. In the future, market agents of PV systems should adjust their operations to multiple energy markets and trends in market prices to optimize revenue stacking.Peer reviewe
Optimisation of Multi-Energy Systems and Power-To-X Technologies: A Hydrogen-Based Industrial Case Study
No full textPublisher Copyright: © 2025 IEEE.This study presents a daily cost optimization for a hybrid renewable energy system, hydrogen and battery storage, for PtX technology implementation. Using mixed-integer linear programming, this paper aims at minimising total system cost, subject to technical system constraints. This paper is focused on the modelling and optimisation of a hydrogen-based industrial case study comparing the operating strategy between a typical summer and winter day. Although RES generation is not sufficient to fully meet the energy needs of the industry, the system operation aims to reduce the daily cost. The results show a clear priority for the direct use of hydrogen over its conversion into electricity, due to its low efficiency and cost. The system successfully manages hydrogen generation, battery and production, depending on prices, while ensuring a stable industrial supply. Hydrogen storage fluctuates and tends to reduce system cost, which requires accurate management to avoid hydrogen shortages during peak demand.Peer reviewe
Flexible Constraint-Based Controller Framework for Ros_Control
Get PDFPublisher Copyright: © 2025 by the authors.Generating robot behaviors in dynamic real-world situations generally requires the programming of multiple, often redundant degrees of freedom to meet multiple goals governing the desired motions. In this work, we propose a constraint-based controller specification methodology. A novel declarative language is used to combine semantically specialized building blocks into composite controllers. This description is automatically transformed at runtime into an executable form, which can automatically leverage multiple threads to parallelize computations whenever possible. Enabling runtime definition of controller topologies out of declarative descriptions not only reduces the work required to develop such controllers, but it also allows one to dynamically synthesize new controllers based on higher-level task planners or by user interaction through Graphical User Interfaces (GUIs). Our solution adds new functionality to the Robot Operating System (ROS)/ros_control ecosystem, where robot behaviors are typically achieved by deploying single-objective, off-the-shelf controllers for tasks like following joint trajectories, executing interpolated point-to-point motions in Cartesian space, or for basic compliant behaviors. Our proposed constraint-based framework enhances ros_control by providing the means to easily construct composite controllers from existing primary elements using our design language. Building on top of the ros_control infrastructure facilitates the usage of our controller with a wide range of supported robots and enables quick integration with the existing ROS ecosystem.Peer reviewe
Prioritising Critical Factors for Local Economic Development in Urban Regeneration Strategies
Get PDFPublisher Copyright: © 2025 by the authors.Local economic development (LED) strategies at the district level—such as sub-city or neighbourhood initiatives—play a crucial role in fostering sustainable and inclusive urban growth. This study explores the critical factors influencing LED and urban regeneration at the district scale, emphasising the integration of sustainability, digital technologies, inclusivity, energy efficiency, community engagement, and innovation into strategic planning. To prioritise these CFs, a tailored survey was distributed among a group of 13 city experts from European cities, involved in research projects focused on district-level quality-of-life enhancements through building retrofits, urban space interventions, energy community promotion, and technological deployment. By focusing on the district level, this research highlights the importance of tailoring strategies to local contexts and leveraging the unique characteristics of each neighbourhood. The findings reveal the need for local governments to enhance the capacity of administrative staff to engage citizens and direct external support for development projects. The normative recommendations derived from this study are specifically grounded in district-level research and practice, ensuring their applicability to sub-city areas. This paper concludes that a context-specific and collaborative approach is essential for achieving equitable and sustainable economic development at the district level.Peer reviewe
Hydrogen Evolution Reaction of Electrodeposited Ni-W Films in Acidic Medium and Performance Optimization Using Machine Learning
No full textPublisher Copyright: © 2024 The Authors. ChemSusChem published by Wiley-VCH GmbH.Ni−W alloy films were electrodeposited from a gluconate aqueous bath at pH=5.0, at varying current densities and temperatures. While there is little to no difference in composition, i. e., all films possess ~12 at.% W, their activity at hydrogen evolution reaction (HER) in acidic medium is greatly influenced by differences in surface morphology. The kinetics of HER in 0.5 M H2SO4 indicates that the best performing film was obtained at a current density of −4.8 mA/cm2 and 50 °C. The Tafel slopes (b) and the overpotentials at a geometric current density of −10 mA/cm2 (η10) obtained for 200 cycles of linear sweep voltammetry (LSV) from a set of films deposited using different parameters were fed into a machine learning algorithm to predict optimum deposition conditions to minimize b, η10, and the degradation of samples over time. The optimum deposition conditions predicted by the machine learning model led to the electrodeposition of Ni−W films with superior performance, exhibiting b of 33–45 mV/dec and an η10 of 0.09–0.10 V after 200 LSVs.Peer reviewe
Heritage valorisation as a means of rural regeneration: the RURITAGE inventory of Lessons Learnt
No full textPublisher Copyright: © 2025, Emerald Publishing Limited.Purpose: Cultural and natural heritage play a crucial role in the enhancement of sustainable development strategies in rural areas, even though their full potential is still under-explored. Rural areas are currently facing common challenges related to depopulation, unemployment, poverty and ageing, making knowledge and experiences sharing a way to inspire and get insight on how to develop and implement rural regeneration strategies. The purpose of this study is to propose a knowledge framework assessment based on the analysis, documentation and mapping of successful heritage-led practices, to obtain and gather replicable lessons learnt in the form of inventory, to facilitate replicable regeneration strategies. Design/methodology/approach: The paper draws on good practices implemented by 20 Role Models and analysed in the context of the RURITAGE project, introducing the inventory of Lessons Learnt, a tool aimed at supporting and improving the use of evidence in decision-making processes and facilitating replication. Findings: The multilevel analysis described in this paper allowed to identify 40 Lessons Learnt, which were clustered according to their main area of knowledge and cross-cutting issues, demonstrating and reinforcing the importance of culture and heritage in the sustainable development of rural areas. Originality/value: This paper, through the structured analysis of information provided, contributes to support the decision-making process by improving the use of evidence and knowledge integration.Peer reviewe
Leveraging Hyperledger Fabric for Criminal Evidence Integrity-Proofs
No full textPublisher Copyright: © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.Nowadays, digital evidence plays a significant role in criminal investigations due to the widespread use of technology in daily life. As in the case of physical evidence, digital evidence requires suitable and secure handling and storage processes to guarantee its integrity and be admissible in a court. This paper presents a blockchain-based integrity-proof system that leverages the security features of Hyperledger Fabric to enable secure and reliable evidence. This system also enhances the usability of the blockchain technology, allowing authorities with no technical knowledge to use it. The design and specific implementation are described in detail, resulting in a real prototype for a reliable, secure, and user-friendly criminal evidence integrity-proof system. This system has been successfully used in the analysis of car accidents, resulting in a very useful tool for securing car accident 3D reconstruction and energetic analysis.Peer reviewe
Novel Bio-Based Formulations for Alkyd Wood Coatings: Effects on Biodegradation and Technical Performance
Get PDFPublisher Copyright: © 2025 by the authors.Alkyd resins are still one of the most important classes of binders for paint systems. They are outstanding in terms of their versatility of formulations and applications, cost-effectiveness, and durability. Traditionally, they are synthesized using phthalic anhydride, polyalcohols with three or four functional groups (pentaerythritol, glycerol, and trimethylolpropane), and fatty acids or oils. In this study, new bio-alkyd resins were synthesized with the objective of increasing the bio-based content by substituting phthalic anhydride, thereby also enhancing the biodegradability of coatings. The newly synthesized alkyd resins, formulated with azelaic acid, were used to develop coatings incorporating additives while avoiding cobalt-based driers. Additional agents such as leveling, wetting, and anti-skinning agents, were also included. Paints were applied to wood substrates and dried at room temperature. The resulting films were characterized by pendulum hardness, transparency, and color by colorimetry, cross-cut test, contact angle, and gloss. Thermal properties were analyzed by Differential Scanning Calorimetry (DSC), and Total Organic Carbon (TOC) content and aerobic biodegradation were also evaluated. The resulting coating films exhibited good mechanical performance, with hardness values ranging from 132 to 148 Persoz oscillations and strong adhesion to wood substrates (smooth cross-cut edges, Class 0). Significant biodegradability (70% in less than 90 days) was demonstrated under composting conditions, which was considerably higher than that of a commercial reference alkyd coating (34.7%) under the same conditions. These findings suggest that the developed bio-alkyd coatings formulated with azelaic acid and DCO-FA without cobalt-based driers represent a promising alternative to conventional phthalic acid-based alkyds. These novel coatings move closer to fully bio-based formulations and offer enhanced biodegradability, making them a more sustainable option for coating applications.Peer reviewe
Satellite image classification with neural quantum kernels
Get PDFPublisher Copyright: © 2025 The Author(s).Achieving practical applications of quantum machine learning (QML) for real-world scenarios remains challenging despite significant theoretical progress. This paper proposes a novel approach for classifying satellite images, a task of particular relevance to the earth observation industry, using QML techniques. Specifically, we focus on classifying images that contain solar panels, addressing a complex real-world classification problem. Our approach begins with classical pre-processing to reduce the dimensionality of the satellite image dataset. We then apply neural quantum kernels-quantum kernels derived from trained quantum neural networks-for classification. We evaluate several strategies within this framework, demonstrating results that are competitive with the best classical methods. Key findings include the robustness of or results and their scalability, with successful performance achieved up to 8 qubits.Peer reviewe
An Authentication System Based on Self-sovereign Identity for Vehicle-to-Vehicle (V2V) Communications
No full textPublisher Copyright: © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.In the evolving landscape of connected vehicles, secure and reliable communication between them (V2V) is crucial. In this scenario, a cornerstone is the achievement of the security service of authentication, that is, guaranteeing that right users with the right permissions are those who get specific resources. The present work proposes an authentication system based on Self-Sovereign Identity (SSI) to protect Vehicle-to-Vehicle (V2V) communications. Its implementation is based on the use of the Hyperledger Aries Cloud Agent (ACA-Py) and Arduino platform. The ACA-Py is a key component of the Hyperledger Aries project and has been designed to facilitate the development of Self-Sovereign Identity (SSI) services by abstracting developers of the logic of SSI methods. In this work, we have implemented an ACA-py controller on an Arduino SP32 board and conducted a series of experiments to assess its performance, with the aim of evaluating if SSI implementations using low-resource devices as Arduino are feasible. Our findings reveal that, when a proper design and adaptation is done, an ACA-Py controller can be run on an Arduino without any issues. Consequently, an authentication mechanism based on SSI can be integrated as a piece of software in vehicles for helping to protect V2V communications.Peer reviewe