Real-time economic dispatch considering adverse weather conditions in renewable generation

Md Mainul Islam; Mahmood Nagrial; Jamal Rizk; Ali Hellany

doi:10.1109/AUPEC62273.2024.10807600

Real-time economic dispatch considering adverse weather conditions in renewable generation

Md Mainul Islam, Mahmood Nagrial, Jamal Rizk, Ali Hellany

School of Engineering, Design & Built Environment

Research output: Chapter in Book / Conference Paper › Conference Paper › peer-review

Abstract

Economic dispatch (ED) of the microgrid (MG) is challenging for real-time power generation and storage because of the unpredictability of renewable energy sources. The MG ED with the battery storage system is therefore essential to diminish the uncertainty. This study suggests a novel binary jellyfish search algorithm to solve the MG ED problem with adverse weather conditions. The results show that incorporating the battery storage unit can appreciably reduce the real-time operating costs by more than 5%. Furthermore, the simulation results also show the effectiveness of the suggested MG ED approach.

Original language	English
Title of host publication	Proceedings of the IEEE 34th Australasian Universities Power Engineering Conference (AUPEC 2024), 20th - 22nd November, 2024, Sydney, Australia
Place of Publication	U.S.
Publisher	IEEE
Number of pages	6
ISBN (Electronic)	9798350377941
DOIs	https://doi.org/10.1109/AUPEC62273.2024.10807600
Publication status	Published - 2024
Event	AUPEC (Conference) - Sydney, Australia Duration: 20 Nov 2024 → 22 Nov 2024 Conference number: 34th

Conference

Conference	AUPEC (Conference)
Country/Territory	Australia
City	Sydney
Period	20/11/24 → 22/11/24

Keywords

battery storage
economic dispatch
jellyfish algorithm
microgrid
renewable energy

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10.1109/AUPEC62273.2024.10807600

Cite this

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title = "Real-time economic dispatch considering adverse weather conditions in renewable generation",

abstract = "Economic dispatch (ED) of the microgrid (MG) is challenging for real-time power generation and storage because of the unpredictability of renewable energy sources. The MG ED with the battery storage system is therefore essential to diminish the uncertainty. This study suggests a novel binary jellyfish search algorithm to solve the MG ED problem with adverse weather conditions. The results show that incorporating the battery storage unit can appreciably reduce the real-time operating costs by more than 5%. Furthermore, the simulation results also show the effectiveness of the suggested MG ED approach.",

keywords = "battery storage, economic dispatch, jellyfish algorithm, microgrid, renewable energy",

author = "Islam, {Md Mainul} and Mahmood Nagrial and Jamal Rizk and Ali Hellany",

year = "2024",

doi = "10.1109/AUPEC62273.2024.10807600",

language = "English",

booktitle = "Proceedings of the IEEE 34th Australasian Universities Power Engineering Conference (AUPEC 2024), 20th - 22nd November, 2024, Sydney, Australia",

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note = "AUPEC (Conference) ; Conference date: 20-11-2024 Through 22-11-2024",

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Islam, MM, Nagrial, M , Rizk, J & Hellany, A 2024, Real-time economic dispatch considering adverse weather conditions in renewable generation. in Proceedings of the IEEE 34th Australasian Universities Power Engineering Conference (AUPEC 2024), 20th - 22nd November, 2024, Sydney, Australia. IEEE, U.S., AUPEC (Conference), Sydney, New South Wales, Australia, 20/11/24. https://doi.org/10.1109/AUPEC62273.2024.10807600

Real-time economic dispatch considering adverse weather conditions in renewable generation. / Islam, Md Mainul; Nagrial, Mahmood ; Rizk, Jamal et al.
Proceedings of the IEEE 34th Australasian Universities Power Engineering Conference (AUPEC 2024), 20th - 22nd November, 2024, Sydney, Australia. U.S.: IEEE, 2024.

Research output: Chapter in Book / Conference Paper › Conference Paper › peer-review

TY - GEN

T1 - Real-time economic dispatch considering adverse weather conditions in renewable generation

AU - Islam, Md Mainul

AU - Nagrial, Mahmood

AU - Rizk, Jamal

AU - Hellany, Ali

N1 - Conference code: 34th

PY - 2024

Y1 - 2024

N2 - Economic dispatch (ED) of the microgrid (MG) is challenging for real-time power generation and storage because of the unpredictability of renewable energy sources. The MG ED with the battery storage system is therefore essential to diminish the uncertainty. This study suggests a novel binary jellyfish search algorithm to solve the MG ED problem with adverse weather conditions. The results show that incorporating the battery storage unit can appreciably reduce the real-time operating costs by more than 5%. Furthermore, the simulation results also show the effectiveness of the suggested MG ED approach.

AB - Economic dispatch (ED) of the microgrid (MG) is challenging for real-time power generation and storage because of the unpredictability of renewable energy sources. The MG ED with the battery storage system is therefore essential to diminish the uncertainty. This study suggests a novel binary jellyfish search algorithm to solve the MG ED problem with adverse weather conditions. The results show that incorporating the battery storage unit can appreciably reduce the real-time operating costs by more than 5%. Furthermore, the simulation results also show the effectiveness of the suggested MG ED approach.

KW - battery storage

KW - economic dispatch

KW - jellyfish algorithm

KW - microgrid

KW - renewable energy

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DO - 10.1109/AUPEC62273.2024.10807600

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AN - SCOPUS:85215543297

BT - Proceedings of the IEEE 34th Australasian Universities Power Engineering Conference (AUPEC 2024), 20th - 22nd November, 2024, Sydney, Australia

PB - IEEE

CY - U.S.

T2 - AUPEC (Conference)

Y2 - 20 November 2024 through 22 November 2024

ER -

Real-time economic dispatch considering adverse weather conditions in renewable generation

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Keywords

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