Affiliations 

  • 1 Smart Assistive and Rehabilitative Technology (SMART), Research Group, Universiti Teknologi PETRONAS, 32610 Perak, Malaysia
  • 2 Department of Electrical and Electronics Engineering, Universiti Teknologi PETRONAS, 32610 Perak, Malaysia
  • 3 Faculty of Engineering, Multimedia University, Persiaran Multimedia, 63100 Cyberjaya, Selangor, Malaysia
  • 4 University Institute of Engineering and Technology, Kurukshetra University, Thanesar, 136119 Haryana, India
Sensors (Basel), 2020 May 25;20(10).
PMID: 32466240 DOI: 10.3390/s20102992

Abstract

Microgrids help to achieve power balance and energy allocation optimality for the defined load networks. One of the major challenges associated with microgrids is the design and implementation of a suitable communication-control architecture that can coordinate actions with system operating conditions. In this paper, the focus is to enhance the intelligence of microgrid networks using a multi-agent system while validation is carried out using network performance metrics i.e., delay, throughput, jitter, and queuing. Network performance is analyzed for the small, medium and large scale microgrid using Institute of Electrical and Electronics Engineers (IEEE) test systems. In this paper, multi-agent-based Bellman routing (MABR) is proposed where the Bellman-Ford algorithm serves the system operating conditions to command the actions of multiple agents installed over the overlay microgrid network. The proposed agent-based routing focuses on calculating the shortest path to a given destination to improve network quality and communication reliability. The algorithm is defined for the distributed nature of the microgrid for an ideal communication network and for two cases of fault injected to the network. From this model, up to 35%-43.3% improvement was achieved in the network delay performance based on the Constant Bit Rate (CBR) traffic model for microgrids.

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.