Distributed energy resources (DERs) are transforming power networks, challenging traditional operational methods, and requiring new coordination mechanisms. To address this challenge, this paper introduces SecuLEx (Secure Limit Exchange), a market-based paradigm for allocating and trading power injection and withdrawal limits, known as dynamic operating envelopes (DOEs). Under this paradigm, distribution system operators (DSOs) first assign initial DOEs to customers through a fair allocation mechanism. These limits can be exchanged afterward through a market, allowing customers to reallocate them according to their needs while ensuring network operational constraints. We formalize SecuLEx and illustrate DOE allocation and market exchanges on a small-scale low-voltage (LV) network. In this case study, SecuLEx reduces renewable curtailment and improves grid utilization and social welfare compared to traditional approaches.
Face recognition in autism is well-researched and up to 1/3 of autistic individuals are reported to have severe face recognition difficulties. In comparison, there are few reports on object recognition performance in autism, and the findings are rather inconsistent. Here we report results from a series of object recognition tasks performed by autistic (N = 41) and matched non-autistic participants. Across tasks we varied the demand placed on perceptual differentiation, the structural similarity of the objects, and the salience and value of global shape information (the object’s bounding contour) relative to local shape information (details) in the recognition process. Our main hypothesis was that when local shape information was less salient than global shape information, and when both types of information needed to be integrated to support performance, autistic participants would perform less efficiently than non-autistic participants. This hypothesis was not fulfilled as the autistic group performed just as efficiently as the non-autistic group across all tasks. We discuss our findings in the context of previous reports of object recognition performance in autism and argue that former reports of impairments might reflect lexico-semantic rather than perceptual processes.
Offshore wind power (OWP) and offshore energy hubs (OEHs) have recently become stable components of decarbonisation efforts across the EU. To this end, a plan to construct "Energy Islands" was institutionalised in Danish policy in 2020, alongside ambitions to scale up OWP capacity by 6 GW. However, in 2022, the Russia-Ukraine conflict altered the geopolitical landscape, rapidly changing prospects for OWP implementation. Inflation, uncertain energy market developments and annulment of an open-door scheme have negatively impacted OWP incentives in Denmark. This article utilises the Multiple Streams Framework (MSF) to analyse symptoms, barriers, and proposed solutions to this development. It identifies how offshore energy policy 'windows' in Denmark are affected by shifting geopolitical landscapes across the EU from 2020 to 2026. To assess this, a thematic analysis of discourses surrounding OWP development is conducted, utilising themes appearing in the Problem, Policy and Politics streams of the MSF to frame the analysis. Data was gathered from six public events focusing on OWP development and from two focus group discussions. A document analysis of relevant policies and literature is conducted to support findings. Results indicate that the OWP window of opportunity has been at risk of closing due to significant shifts in deployment capabilities. Policy adaptations and new regulations can help mitigate geopolitical uncertainty and keep it open.
This paper examines the influence of boundary conditions on the vibrations of moderately curved beams subjected to static radial uniform prestress. A nonlinear curved-beam model is used to compute prestressed equilibria, critical loads, linear normal modes, nonlinear backbone curves and forced-response predictions for two boundary realizations, pinned-pinned and radially sliding ends. A one-mode prestressed reduced-order model provides a useful baseline for vibration analysis, but it can misrepresent the nonlinear backbone because it suppresses the mean and second-harmonic spatial corrections generated by quadratic nonlinearities. The corrected multiple-scales formulation shows that the two sets of boundary conditions have distinct backbone signatures. In the pinned-pinned model, the non-uniform prestress field makes the symmetric mode the most sensitive one, producing curvature-induced transitions between softening and hardening, while the skew-symmetric mode is mainly hardening under prestress. In the radially sliding-end model, the uniform prestress field gives a Duffing-like one-mode reduction, but the corrected backbone makes the skew-symmetric mode nearly neutral over much of the range and leaves the symmetric mode as the stronger hardening branch. Hence radial prestress changes not only the linear frequencies, but also the sign and magnitude of the nonlinear backbone shift in a mode-and boundary-dependent manner.
The maritime industry is among the key players in global trade, transporting the largest portion of the world’s goods. It connects economies, supports millions of jobs, and enables the movement of raw materials, energy resources, and manufactured products efficiently across continents. However, this industry is also a major source of greenhouse gas emissions. Considering these emissions, this industry is undergoing a transition to maritime electrification with net-zero emissions. In order to achieve that goal, batteries are the main tool, including the development of fully electric and hybrid vessels. To this end, this paper provides a structured overview of battery systems in marine electrification, covering various aspects of this rapidly evolving field. It presents an analysis of different ship types and the power topologies of electric and hybrid vessels, supported by updated examples of real-world commercialized and produced vessels across different regions. Additionally, the evolution of battery technology is demonstrated by detailing both commercialized and early-stage batteries, with a focus on their power rating, energy density, specific energy, cycle life, and management systems. Furthermore, the applications of Artificial Intelligence (AI) and digital twin technologies in marine electrification are presented with a detailed review of recent developments. The Artificial Intelligence (AI) strategies are classified into several categories, and a case study from a representative strategy of each class in battery and marine electrification is presented. It also includes guidelines and standards issued by official organizations to ensure compliance and safety in the sector. Additionally, it highlights recently completed and ongoing funded projects in marine electrification in the U.S. and the EU, as well as the related software tools and industry white papers. Moreover, the correlation between battery systems and marine electrification is provided with the United Nation (UN) Sustainable Development Goals (SDGs) and which SDGs they are effective and aligned. Finally, the updated challenges and future research directions are presented for a forward-looking perspective on the marine electrification sector and its transition to a net-zero industry.
