Biologically inspired modelling of smart grid for dynamic power-flow control under power failure. (2018)

• Record Type: Journal Article
• Authors: Sawai, Hidefumi; Suzuki, Hideaki; Ohsaki, Hiroyuki
• Is Part Of: International journal of autonomous and adaptive communications systems. Volume 11:Number 4(2018)
• Page Start: 365
• Page End: 389
• Publication Date: 2018
• Subjects: smart grid -- dynamic power-flow control -- highly distributed asynchronous system -- brain function -- fault tolerance -- microgrid -- demand response -- power-failure -- automatic power recovery -- biologically inspired modelling -- optimisation -- objective function -- simulation; Adaptive computing systems -- Periodicals; Wireless communication systems -- Periodicals; Computer networks -- Periodicals; 004.6
• Languages: English
• ISSNs: 1754-8632

Abstract

Smart grid is an electric power network that enables an effective use of electric power in a highly parallel-distributed manner. We have first formulated the basic equations for the smart grid by inspiring from the mechanisms in biological organism, and controlled the power-flow dynamically in the smart grid by monitoring an objective function, which reflects the power-flow and the constraint imposing on the power nodes. To validate the operation of the smart grid, we performed several simulation experiments, which include the operations of a conventional power network, a microgrid (comprises eight power nodes), and a smart grid (comprises three microgrids integrated into the conventional power network) both in synchronous and asynchronous manners for the operation of power nodes. Furthermore, even for several cases of power failure such as outage, a thunderbolt shock on the power plant and disconnection of power cables, power recovery can be automatically achieved through bypass connections similar to synaptic interconnections in a dynamic function of brain. Thus, the proposed control method guarantees a dynamically stable operation even in several cases of power failure by monitoring the objective function, while always reflecting an optimal state in smart grid as a whole system.