Microgrid energy management system for academic building

Usman Bashir Tayab, Junwei Lu, Fuwen Yang, Mojaharul Islam, Ali Zia, Jahangir Hossain

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionpeer-review

Abstract

In this paper, an optimal energy management system (EMS) for grid-connected microgrid is proposed. The gridconnected microgrid system comprises of photovoltaic (PV) panel, and battery as an energy storage unit. The optimal EMS is aimed to minimize the total operating cost of grid-connected microgrid for academic building. The feedforward neural network with improved salp swarm alogrithm based on weight factor is used to determine the 24-hours ahead data forecasting of load demand and PV power, while improved salp swarm alogrithm based on weight factor (WSSA) is used to perform the day-ahead optimal scheduling to control the power flow between PV, energy storage unit, load and main grid. The proposed microgrid EMS (MGEMS) is simulated using MATLAB/Simulink. The simulation result shows the effectiveness and validity of presented EMS with academic load.
Original languageEnglish
Title of host publication2019 29th Australasian Universities Power Engineering Conference (AUPEC)
Place of PublicationPiscataway, NJ
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages1-5
Number of pages5
ISBN (Electronic)9781728150437, 9781728150420
ISBN (Print)9781728150444
DOIs
Publication statusPublished - 2019
Event2019 29th Australasian Universities Power Engineering Conference - Nadi, Fiji
Duration: 26 Nov 201929 Nov 2019

Publication series

Name
ISSN (Print)2474-1493
ISSN (Electronic)2474-1507

Conference

Conference2019 29th Australasian Universities Power Engineering Conference
Abbreviated titleAUPEC
CountryFiji
CityNadi
Period26/11/1929/11/19

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