The recent research in the field of smart energy systems and smart grids has seen significant advancements in enhancing security, interoperability, and energy sharing mechanisms. There is a notable shift towards developing more resilient and secure systems, particularly in the face of laser-based fault injection attacks on finite state machines. Innovations like the transition-based encoding CAD framework, which incorporates spatial vulnerability metrics and floorplan optimization, are leading the way in improving FSM resiliency with minimal overhead. Additionally, the focus on interoperability testing for smart energy systems has intensified, with a push towards harmonizing procedures and developing systematic testing approaches that can handle complex integration scenarios. Security in smart grids, especially in the context of Smart Grid 2.0, is being redefined with the introduction of scalable blockchain-based models, physical unclonable functions, and trustworthy AI models to manage distributed microgrids. Energy sharing algorithms are also being refined, with new models like Selfish Sharing showing promise in reducing grid dependency across different microgrid configurations. Finally, the field is witnessing the development of advanced attack analytics tools, such as MISGUIDE, which can extract complex attack vectors from smart grid dynamics, enhancing the security posture of these critical infrastructures.

Noteworthy papers include one that introduces a transition-based encoding CAD framework for improving FSM resiliency against laser-based fault injection attacks, and another that proposes a novel energy sharing algorithm, Selfish Sharing, which shows significant reductions in grid dependency across microgrids.