Spike Talk in Power Electronic Grids -- Leveraging Post Moore's Computing Laws

Autor:	Song, Yubo, Sahoo, Subham
Rok vydání:	2024
Předmět:	Computer Science - Emerging Technologies Computer Science - Artificial Intelligence Computer Science - Neural and Evolutionary Computing Electrical Engineering and Systems Science - Systems and Control
Druh dokumentu:	Working Paper
Popis:	Emerging distributed generation demands highly reliable and resilient coordinating control in microgrids. To improve on these aspects, spiking neural network is leveraged, as a grid-edge intelligence tool to establish a talkative infrastructure, Spike Talk, expediting coordination in next-generation microgrids without the need of communication at all. This paper unravels the physics behind Spike Talk from the perspective of its distributed infrastructure, which aims to address the Von Neumann Bottleneck. Relying on inferring information via power flows in tie lines, Spike Talk allows adaptive and flexible control and coordination itself, and features in synaptic plasticity facilitating online and local training functionality. Preliminary case studies are demonstrated with results, while more extensive validations are to be included as future scopes of work. Comment: The manuscript has been accepted for publication in the Proceedings of 2024 IEEE Design Methodologies for Power Electronics Conference (DMC2024)
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2411.07654 Zobrazit plný text záznamu View this record from Arxiv