Unit Commitment and Optimal Power Flow Based Optimal Sizing Strategy of Energy Storage Systems

Mohammed A. Abdulgalil; Megat Gadalla; Kamal Ramadan Doud

doi:10.1109/ICCCEEE49695.2021.9429653

Unit Commitment and Optimal Power Flow Based Optimal Sizing Strategy of Energy Storage Systems

Mohammed A. Abdulgalil
, Megat Gadalla
, Kamal Ramadan Doud

Department of Electrical Engineering

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

3 Scopus citations

Abstract

This paper proposes a new strategy to optimally size an energy storage system (ESS) based on optimization problems in power systems. These optimization problems are unit commitment (UC) which is solved using mixed-integer linear programming (MILP), DC optimal power flow (DC-OPF) which is solved using linear programming (LP), and AC optimal power flow (AC-OPF) which is solved using non-linear programming (NLP). The proposed strategy is tested on the IEEE Reliability Test System (RTS-96) 24-bus system. The results show the effectiveness of integrating an ESS to a power system, which is a microgrid in this paper. General algebraic modeling system (GAMS) is used to model and solve the proposed models.

Original language	English
Title of host publication	Proceedings of
Subtitle of host publication	2020 International Conference on Computer, Control, Electrical, and Electronics Engineering, ICCCEEE 2020
Editors	Dalia Mahmoud, Siddig Gomha, Atif Osman
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781728191119
DOIs	https://doi.org/10.1109/ICCCEEE49695.2021.9429653
State	Published - 26 Feb 2021

Publication series

Name	Proceedings of: 2020 International Conference on Computer, Control, Electrical, and Electronics Engineering, ICCCEEE 2020

Bibliographical note

Publisher Copyright:
© 2021 IEEE.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

energy storage system
power system optimization
power system planning
renewable energy

ASJC Scopus subject areas

Artificial Intelligence
Hardware and Architecture
Energy Engineering and Power Technology
Control and Systems Engineering
Electrical and Electronic Engineering
Control and Optimization
Instrumentation

Access to Document

10.1109/ICCCEEE49695.2021.9429653

Cite this

Abdulgalil, M. A., Gadalla, M., & Doud, K. R. (2021). Unit Commitment and Optimal Power Flow Based Optimal Sizing Strategy of Energy Storage Systems. In D. Mahmoud, S. Gomha, & A. Osman (Eds.), Proceedings of: 2020 International Conference on Computer, Control, Electrical, and Electronics Engineering, ICCCEEE 2020 Article 9429653 (Proceedings of: 2020 International Conference on Computer, Control, Electrical, and Electronics Engineering, ICCCEEE 2020). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICCCEEE49695.2021.9429653

Abdulgalil, Mohammed A. ; Gadalla, Megat ; Doud, Kamal Ramadan. / Unit Commitment and Optimal Power Flow Based Optimal Sizing Strategy of Energy Storage Systems. Proceedings of: 2020 International Conference on Computer, Control, Electrical, and Electronics Engineering, ICCCEEE 2020. editor / Dalia Mahmoud ; Siddig Gomha ; Atif Osman. Institute of Electrical and Electronics Engineers Inc., 2021. (Proceedings of: 2020 International Conference on Computer, Control, Electrical, and Electronics Engineering, ICCCEEE 2020).

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abstract = "This paper proposes a new strategy to optimally size an energy storage system (ESS) based on optimization problems in power systems. These optimization problems are unit commitment (UC) which is solved using mixed-integer linear programming (MILP), DC optimal power flow (DC-OPF) which is solved using linear programming (LP), and AC optimal power flow (AC-OPF) which is solved using non-linear programming (NLP). The proposed strategy is tested on the IEEE Reliability Test System (RTS-96) 24-bus system. The results show the effectiveness of integrating an ESS to a power system, which is a microgrid in this paper. General algebraic modeling system (GAMS) is used to model and solve the proposed models.",

keywords = "energy storage system, power system optimization, power system planning, renewable energy",

author = "Abdulgalil, \{Mohammed A.\} and Megat Gadalla and Doud, \{Kamal Ramadan\}",

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Abdulgalil, MA, Gadalla, M & Doud, KR 2021, Unit Commitment and Optimal Power Flow Based Optimal Sizing Strategy of Energy Storage Systems. in D Mahmoud, S Gomha & A Osman (eds), Proceedings of: 2020 International Conference on Computer, Control, Electrical, and Electronics Engineering, ICCCEEE 2020., 9429653, Proceedings of: 2020 International Conference on Computer, Control, Electrical, and Electronics Engineering, ICCCEEE 2020, Institute of Electrical and Electronics Engineers Inc. https://doi.org/10.1109/ICCCEEE49695.2021.9429653

Unit Commitment and Optimal Power Flow Based Optimal Sizing Strategy of Energy Storage Systems. / Abdulgalil, Mohammed A.; Gadalla, Megat; Doud, Kamal Ramadan.
Proceedings of: 2020 International Conference on Computer, Control, Electrical, and Electronics Engineering, ICCCEEE 2020. ed. / Dalia Mahmoud; Siddig Gomha; Atif Osman. Institute of Electrical and Electronics Engineers Inc., 2021. 9429653 (Proceedings of: 2020 International Conference on Computer, Control, Electrical, and Electronics Engineering, ICCCEEE 2020).

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

TY - GEN

T1 - Unit Commitment and Optimal Power Flow Based Optimal Sizing Strategy of Energy Storage Systems

AU - Abdulgalil, Mohammed A.

AU - Gadalla, Megat

AU - Doud, Kamal Ramadan

PY - 2021/2/26

Y1 - 2021/2/26

N2 - This paper proposes a new strategy to optimally size an energy storage system (ESS) based on optimization problems in power systems. These optimization problems are unit commitment (UC) which is solved using mixed-integer linear programming (MILP), DC optimal power flow (DC-OPF) which is solved using linear programming (LP), and AC optimal power flow (AC-OPF) which is solved using non-linear programming (NLP). The proposed strategy is tested on the IEEE Reliability Test System (RTS-96) 24-bus system. The results show the effectiveness of integrating an ESS to a power system, which is a microgrid in this paper. General algebraic modeling system (GAMS) is used to model and solve the proposed models.

AB - This paper proposes a new strategy to optimally size an energy storage system (ESS) based on optimization problems in power systems. These optimization problems are unit commitment (UC) which is solved using mixed-integer linear programming (MILP), DC optimal power flow (DC-OPF) which is solved using linear programming (LP), and AC optimal power flow (AC-OPF) which is solved using non-linear programming (NLP). The proposed strategy is tested on the IEEE Reliability Test System (RTS-96) 24-bus system. The results show the effectiveness of integrating an ESS to a power system, which is a microgrid in this paper. General algebraic modeling system (GAMS) is used to model and solve the proposed models.

KW - energy storage system

KW - power system optimization

KW - power system planning

KW - renewable energy

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AN - SCOPUS:85107128244

T3 - Proceedings of: 2020 International Conference on Computer, Control, Electrical, and Electronics Engineering, ICCCEEE 2020

BT - Proceedings of

A2 - Mahmoud, Dalia

A2 - Gomha, Siddig

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Abdulgalil MA, Gadalla M, Doud KR. Unit Commitment and Optimal Power Flow Based Optimal Sizing Strategy of Energy Storage Systems. In Mahmoud D, Gomha S, Osman A, editors, Proceedings of: 2020 International Conference on Computer, Control, Electrical, and Electronics Engineering, ICCCEEE 2020. Institute of Electrical and Electronics Engineers Inc. 2021. 9429653. (Proceedings of: 2020 International Conference on Computer, Control, Electrical, and Electronics Engineering, ICCCEEE 2020). doi: 10.1109/ICCCEEE49695.2021.9429653

Unit Commitment and Optimal Power Flow Based Optimal Sizing Strategy of Energy Storage Systems

Abstract

Publication series

Bibliographical note

UN SDGs

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this