eprintid: 15491
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/01/54/91
datestamp: 2023-11-10 03:30:07
lastmod: 2023-11-10 03:30:07
status_changed: 2023-11-10 01:59:37
type: conference_item
metadata_visibility: show
creators_name: Singh, N.
creators_name: Elamvazuthi, I.
creators_name: Nallagownden, P.
creators_name: Badruddin, N.
creators_name: Ousta, F.
creators_name: Jangra, A.
title: Smart Microgrid QoS and Network Reliability Performance Improvement using Reinforcement Learning
ispublished: pub
keywords: Decision making; Electric power transmission networks; Network layers; Network routing; Quality of service; Reinforcement learning; Reliability; Smart power grids, Agent based; Bellman-Ford; Microgrid; Multi agent; Network faults; Network reliability; Reinforcement learnings; Routings; Smart grid; Smart Micro Grids, Multi agent systems
note: cited By 1; Conference of 8th International Conference on Intelligent and Advanced Systems, ICIAS 2021 ; Conference Date: 13 July 2021 Through 15 July 2021; Conference Code:175661
abstract: A Smart Microgrid consists of physical and communication layered networks. It provides communication services to each connected component and resource through multi-agent system. This paper proposes a reinforcement learning based methodology, Q-reinforcement Learning based Multi-agent based Bellmanford Routing (QRL-MABR), using multiple agents communicating over the microgrid network. It strengthens the decision-making core of the microgrid by improving Quality of service and network reliability of the smart microgrid. The performance analysis of the algorithm is tested over small-scale IEEE microgrid models i.e. IEEE 9 and IEEE 14. The work is tested and compared with four routing oriented decision-making algorithms, Open shortest path first (OSPF), Optimized link state routing (OLSR), Routing information protocol (RIP) and Multi-agent based Bellmanford routing (MABR). The results validate the productivity and learning capabilities of the proposed QRL-MABR algorithm. © 2021 IEEE.
date: 2021
publisher: Institute of Electrical and Electronics Engineers Inc.
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85124122304&doi=10.1109%2fICIAS49414.2021.9642596&partnerID=40&md5=9e9acf69b67deadb43bd568a208b166b
id_number: 10.1109/ICIAS49414.2021.9642596
full_text_status: none
publication: International Conference on Intelligent and Advanced Systems: Enhance the Present for a Sustainable Future, ICIAS 2021
refereed: TRUE
isbn: 9781728176666
citation:   Singh, N. and Elamvazuthi, I. and Nallagownden, P. and Badruddin, N. and Ousta, F. and Jangra, A.  (2021) Smart Microgrid QoS and Network Reliability Performance Improvement using Reinforcement Learning.  In: UNSPECIFIED.