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Spike Talk: Genesis and Neural Coding Scheme Translations

Authors: Subham Sahoo;

Spike Talk: Genesis and Neural Coding Scheme Translations

Abstract

Although digitalization of future power grids offer several coordination incentives, the reliability and security of information and communication technologies (ICT) hinders its overall performance. In this paper, we introduce a novel architecture Spike Talk via a unified representation of power and information as a means of data normalization using spikes for coordinated control of microgrids. This grid-edge technology allows each distributed energy resource (DER) to execute decentralized secondary control philosophy independently by interacting among each other using power flow along the tie-lines. Inspired from the field of computational neuroscience, Spike Talk basically builds on a fine-grained parallelism on the information transfer theory in our brains, particularly when neurons (modeled as DERs) transmit information (inferred from power streams measurable at each DER) through synapses (modeled as tie-lines). Not only does Spike Talk simplify and address the current bottlenecks of the cyber-physical architectural operation by dismissing the ICT layer, it provides intrinsic operational and cost-effective opportunities in terms of infrastructure development, computations and modeling. Hence, this paper provides a pedagogic illustration of the key concepts and design theories. Since we focus on coordinated control of microgrids in this paper, the signaling accuracy and system performance is studied for several neural coding schemes responsible for converting the real-valued local measurements into spikes.

This paper is accepted for publication in IEEE Transactions on Smart Grid

Keywords

Neuromorphic Computing, Signal Processing (eess.SP), FOS: Computer and information sciences, microgrids, Computer Science - Information Theory, Information Theory (cs.IT), hierarchical control, Systems and Control (eess.SY), Electrical Engineering and Systems Science - Systems and Control, spiking neural network, Adaptive Control, /dk/atira/pure/sustainabledevelopmentgoals/affordable_and_clean_energy; name=SDG 7 - Affordable and Clean Energy, Artificial Intelligence, Energy Management, Neuromorphic computing, FOS: Electrical engineering, electronic engineering, information engineering, Spike Talk, Computer Science - Multiagent Systems, Electrical Engineering and Systems Science - Signal Processing, Power Electronics, /dk/atira/pure/sustainabledevelopmentgoals/sustainable_cities_and_communities; name=SDG 11 - Sustainable Cities and Communities, Neuron Modeling, Multiagent Systems (cs.MA)

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Top 10%
Average
Average
Green
hybrid