Proposed Optimised Smart Grid System using Multi-Agent System

Li, Weixian, Logenthiran, Thillainathan, Phan, Van-Tung and Woo, Wai Lok (2018) Proposed Optimised Smart Grid System using Multi-Agent System. In: ISGT Asia 2018 - International Conference on Innovative Smart Grid Technologies, 22nd - 25th May 2018, Singapore.

Full text not available from this repository.
Official URL: http://dx.doi.org/10.1109/ISGT-Asia.2018.8467814

Abstract

Smart grid is a two-way communication power grid that leads to a reliable and efficient electrical distribution grid. Smart grid technology provides a more productive usage of electricity through Artificial intelligence (AI). This paper shows the potential of implementing an optimised smart grid system with the use of Multi-Agent System (MAS) in a power grid environment. It optimises the electricity efficiency and distribution of smart grid on different level. The efficient communication of MAS and algorithm of Energy Management System (EMS) both work together to reduce electricity wastage while optimizing consumers comfort, electricity cost and reduce overloading of power supply. Thus, the optimised smart grid system was designed and developed with the use of MAS for its IEEE FIPA standards compliant communication system. Simulation studies carried out on the proposed system shows its potential to provide the optimal solutions to achieve better electricity distribution efficiency and electricity bill price. This paper demonstrates how the influences of different level of EMS with MAS decision making system will affect the smart grid.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Electricity bill, Energy management system, Multi-agent system, Smart grid
Subjects: G400 Computer Science
H600 Electronic and Electrical Engineering
Department: Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User: Paul Burns
Date Deposited: 29 Mar 2019 15:49
Last Modified: 10 Oct 2019 20:48
URI: http://nrl.northumbria.ac.uk/id/eprint/38647

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics