Physiological inspiration for self-management in smart grid systems opportunities and challenges

Insaurralde, Carlos C.; Strasser, Thomas

Abstract

© 2014 IEEE. Technologies, concepts and architectures for renewable energy are currently in the thick of engineering researches. Technological application examples are sustainable electric supplies and emission-free buildings where infrastructures of power systems such as Smart Grid Systems (SGSs) play a key role. They are actually pushing their self-governing capabilities beyond limits by being required to deal with more and more challenging operational situations (topological reconfiguration, fault tolerance, etc.). Additionally, support of automatic adaptation is needed in order to provide resilience and sustainment. This paper analyzes different use cases of SGSs with the main goal of identifying potential applications for the implementation of physiologically-inspired concepts and algorithms to support self-management. The survey presented recaps the state of the art of SGSs with a particular focus on automation problems and solutions as well as physiologically-inspired adaptation in other domains. It also presents the foundations for a physiologically- inspired self-management approach, and challenging research issues when applying it to SGSs. Concluding remarks and future research directions are discussed as well.

Citation

Insaurralde, C. C., & Strasser, T. (2014). Physiological inspiration for self-management in smart grid systems opportunities and challenges. https://doi.org/10.1109/smc.2014.6974498

• Conference Name: 2014 IEEE International Conference on Systems, Man, and Cybernetics (SMC)
• Conference Location: San Diego, CA, USA
• Start Date: Oct 5, 2014
• End Date: Oct 8, 2014
• Acceptance Date: Jan 1, 2014
• Online Publication Date: Dec 4, 2014
• Publication Date: Dec 4, 2014
• Deposit Date: Mar 10, 2020
• Publisher: Institute of Electrical and Electronics Engineers (IEEE)
• Volume: 2014-January
• Pages: 3657-3662
• Series ISSN: 1062-922X
• DOI: https://doi.org/10.1109/smc.2014.6974498
• Keywords: Smart Grids, Physiologically-Inspired Self-Management, Automation and Control Systems
• Public URL: https://uwe-repository.worktribe.com/output/5285731