Abstract: One of the existing most popular technologies for finding open bypass circuits to prevent hotspots is the measurement of surface temperature with an IR camera. However, this solution has defects. For example, the thermal image is affected by the reflection of surrounding structures such as antennas and buildings, and so on, and it is difficult to measure the true surface temperature of PV modules with an IR camera. To solve the problems mentioned previously, we developed new detection technology for open-fault bypass circuits. The stationary state reflection effect is deleted, and the position of the open fault part is identified exactly by the development technology. However, the reflection effect of moving clouds is not deleted. Therefore, we studied the advanced detection technology to delete the reflection effect of moving clouds. In this paper, the outline and effect of a new proposed technology is described.

Abstract: With the advancement of computational resources and methodologies, computational materials science has significantly reinforced experimental efforts and accelerated materials research and development. However, a significant disparity exists between experimental observations and theoretical calculations, primarily because of the structural simplifications often employed in computational models to enhance feasibility. Bridging this gap is challenging, especially when dealing with large, complex systems such as nanoparticles and interfaces. This requires solutions that extend computational simulations to emulate actual systems. In this study, we propose a method that utilizes the moment tensor potential (MTP) combined with active learning techniques for highly reliable and large-scale simulations of alloy nanoparticle catalysts and reactive dynamics at electrode interfaces.

Abstract: The escalating frequency and severity of natural disasters necessitates a fundamental reevaluation of operational strategies for critical microgrids serving essential facilities such as hospitals, emergency response centers, and security establishments. Traditional approaches to microgrid resilience – whether through preemptive islanding or responsive load shedding – are becoming increasingly cost-prohibitive and operationally risky. Preemptive islanding strategies, while protective, can trigger frequent false alarms that deplete valuable energy and fuel reserves. Conversely, responsive load-shedding approaches often result in significant operational disruptions due to inadequate preparedness for islanding events.
This talk introduces an innovative adaptive defense framework that bridges this operational gap through optimally balanced defensive strategies. Our approach leverages simulation-optimization techniques to capture the complex nonlinear dynamics during potential islanding transitions, enabling a defense plan that maintains operational economy while ensuring reliable islanding capability. The methodology's distinctive feature lies in its ability to dynamically adjust defensive measures based on real-time risk assessment, significantly reducing both operational costs and islanding transition-related disruptions.
The presentation will detail the mathematical formulation and solution methodology, with particular emphasis on the framework's application to inverter-dominated microgrids. We will explore the critical role of mode-transition-capable grid-forming (GFM) inverters and present a comprehensive analysis of current research developments in this domain. The discussion concludes by examining future research trajectories, including framework scalability for interconnected microgrid systems and its adaptation for emerging grid-edge technologies, with specific focus on enhancing resilience in critical infrastructure applications.