Battery Energy Storage Systems Allocation Considering Distribution Network Congestion

Ahmed A.Raouf Mohamed; D John Morrow; Robert Best; Ian Bailie; Andrew Cupples; Jonathan Pollock

doi:10.1109/ISGT-Europe47291.2020.9248982

Battery Energy Storage Systems Allocation Considering Distribution Network Congestion

Ahmed A.Raouf Mohamed, D John Morrow, Robert Best, Ian Bailie, Andrew Cupples, Jonathan Pollock

School of Electronics, Electrical Engineering and Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

16 Citations (Scopus)

494 Downloads (Pure)

Abstract

This paper proposes an operational planning strategy for battery energy storage systems (BESS) in medium voltage distribution networks. This strategy determines the optimal location and size for BESS as well as the discharging and charging schedules. The objective of this methodology is to improve reliability and stability by relieving distribution network congestion, such as voltage violations and lines overloading. Particle Swarm, Firefly, Novel Bat, Krill herd and Coyote optimization algorithms have been utilized to find the optimal solutions that improve the network’s performance by mitigating network stresses. The strategy is implemented and validated using two networks; a 53-node test feeder located in Northern Ireland and the 33-bus radial distribution network. Actual demand measurements were used and high uptake scenarios for low carbon technologies were investigated.

Original language	English
Title of host publication	2020 IEEE PES Innovative Smart Grid Technologies Europe (ISGT-Europe)
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1015
Number of pages	1019
ISBN (Electronic)	978-1-7281-7100-5
DOIs	https://doi.org/10.1109/ISGT-Europe47291.2020.9248982
Publication status	Published - 10 Nov 2020
Event	IEEE PES Innovative Smart Grid Technologies Europe - Duration: 26 Oct 2020 → 28 Oct 2020 https://ieee-isgt-europe.org/

Conference

Conference	IEEE PES Innovative Smart Grid Technologies Europe
Abbreviated title	IEEE ISGT-Europe
Period	26/10/2020 → 28/10/2020
Internet address	https://ieee-isgt-europe.org/

Keywords

Allocation and sizing
Battery Energy Storage Systems
Distribution Networks
Low Carbon Technologies
optimization
scheduling

Access to Document

10.1109/ISGT-Europe47291.2020.9248982Licence: Unspecified

Battery Energy Storage Systems Allocation Considering Distribution Network Congestion
Copyright 2020 IEEE. This work is made available online in accordance with the publisher’s policies. Please refer to any applicable terms of use of the publisher.
Accepted author manuscript, 1.06 MBLicence: Unspecified

R6966ELE: SPIRE 2 - Storage Platform for the Integration of Renewable Energy
Liu, X. A. (PI), Best, R. (CoI), Foley, A. (CoI) & Morrow, D. J. (CoI)
09/06/2017 → …
Project: Research

The integration of battery energy storage systems in modern distribution networks
Mohamed, A. A. R. (Author), Best, R. (Supervisor), Liu, X. (Supervisor) & Morrow, D. J. (Supervisor), Jul 2022
Student thesis: Doctoral Thesis › Doctor of Philosophy

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Cite this

Mohamed, A. A. R., Morrow, D. J., Best, R., Bailie, I., Cupples, A., & Pollock, J. (2020). Battery Energy Storage Systems Allocation Considering Distribution Network Congestion. In 2020 IEEE PES Innovative Smart Grid Technologies Europe (ISGT-Europe) (pp. 1015). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISGT-Europe47291.2020.9248982

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title = "Battery Energy Storage Systems Allocation Considering Distribution Network Congestion",

abstract = "This paper proposes an operational planning strategy for battery energy storage systems (BESS) in medium voltage distribution networks. This strategy determines the optimal location and size for BESS as well as the discharging and charging schedules. The objective of this methodology is to improve reliability and stability by relieving distribution network congestion, such as voltage violations and lines overloading. Particle Swarm, Firefly, Novel Bat, Krill herd and Coyote optimization algorithms have been utilized to find the optimal solutions that improve the network{\textquoteright}s performance by mitigating network stresses. The strategy is implemented and validated using two networks; a 53-node test feeder located in Northern Ireland and the 33-bus radial distribution network. Actual demand measurements were used and high uptake scenarios for low carbon technologies were investigated.",

keywords = "Allocation and sizing, Battery Energy Storage Systems, Distribution Networks, Low Carbon Technologies, optimization, scheduling",

author = "Mohamed, {Ahmed A.Raouf} and Morrow, {D John} and Robert Best and Ian Bailie and Andrew Cupples and Jonathan Pollock",

year = "2020",

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day = "10",

doi = "10.1109/ISGT-Europe47291.2020.9248982",

language = "English",

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booktitle = "2020 IEEE PES Innovative Smart Grid Technologies Europe (ISGT-Europe)",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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note = "IEEE PES Innovative Smart Grid Technologies Europe , IEEE ISGT-Europe ; Conference date: 26-10-2020 Through 28-10-2020",

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Mohamed, AAR, Morrow, DJ , Best, R, Bailie, I, Cupples, A & Pollock, J 2020, Battery Energy Storage Systems Allocation Considering Distribution Network Congestion. in 2020 IEEE PES Innovative Smart Grid Technologies Europe (ISGT-Europe). Institute of Electrical and Electronics Engineers Inc., pp. 1015, IEEE PES Innovative Smart Grid Technologies Europe , 26/10/2020. https://doi.org/10.1109/ISGT-Europe47291.2020.9248982

Battery Energy Storage Systems Allocation Considering Distribution Network Congestion. / Mohamed, Ahmed A.Raouf; Morrow, D John ; Best, Robert et al.
2020 IEEE PES Innovative Smart Grid Technologies Europe (ISGT-Europe). Institute of Electrical and Electronics Engineers Inc., 2020. p. 1015.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Battery Energy Storage Systems Allocation Considering Distribution Network Congestion

AU - Mohamed, Ahmed A.Raouf

AU - Morrow, D John

AU - Best, Robert

AU - Bailie, Ian

AU - Cupples, Andrew

AU - Pollock, Jonathan

PY - 2020/11/10

Y1 - 2020/11/10

N2 - This paper proposes an operational planning strategy for battery energy storage systems (BESS) in medium voltage distribution networks. This strategy determines the optimal location and size for BESS as well as the discharging and charging schedules. The objective of this methodology is to improve reliability and stability by relieving distribution network congestion, such as voltage violations and lines overloading. Particle Swarm, Firefly, Novel Bat, Krill herd and Coyote optimization algorithms have been utilized to find the optimal solutions that improve the network’s performance by mitigating network stresses. The strategy is implemented and validated using two networks; a 53-node test feeder located in Northern Ireland and the 33-bus radial distribution network. Actual demand measurements were used and high uptake scenarios for low carbon technologies were investigated.

AB - This paper proposes an operational planning strategy for battery energy storage systems (BESS) in medium voltage distribution networks. This strategy determines the optimal location and size for BESS as well as the discharging and charging schedules. The objective of this methodology is to improve reliability and stability by relieving distribution network congestion, such as voltage violations and lines overloading. Particle Swarm, Firefly, Novel Bat, Krill herd and Coyote optimization algorithms have been utilized to find the optimal solutions that improve the network’s performance by mitigating network stresses. The strategy is implemented and validated using two networks; a 53-node test feeder located in Northern Ireland and the 33-bus radial distribution network. Actual demand measurements were used and high uptake scenarios for low carbon technologies were investigated.

KW - Allocation and sizing

KW - Battery Energy Storage Systems

KW - Distribution Networks

KW - Low Carbon Technologies

KW - optimization

KW - scheduling

U2 - 10.1109/ISGT-Europe47291.2020.9248982

DO - 10.1109/ISGT-Europe47291.2020.9248982

M3 - Conference contribution

SP - 1015

BT - 2020 IEEE PES Innovative Smart Grid Technologies Europe (ISGT-Europe)

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - IEEE PES Innovative Smart Grid Technologies Europe

Y2 - 26 October 2020 through 28 October 2020

ER -

Battery Energy Storage Systems Allocation Considering Distribution Network Congestion

Abstract

Conference

Keywords

Access to Document

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Projects

R6966ELE: SPIRE 2 - Storage Platform for the Integration of Renewable Energy

Student theses

The integration of battery energy storage systems in modern distribution networks

Cite this