Exploring the Effect of Different Load Models on System Reconfiguration

Rawdha H. Alkuwaiti; Hany E.Z. Farag; Wael El-Sayed; Ahmed Al-Durra; Ehab F. El-Sadaany

doi:10.1109/GTD49768.2023.00104

Exploring the Effect of Different Load Models on System Reconfiguration

Rawdha H. Alkuwaiti
, Hany E.Z. Farag
, Wael El-Sayed
, Ahmed Al-Durra
, Ehab F. El-Sadaany

York University
Shoubra Faculty of Engineering

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

Abstract

The self-healing framework has always aimed to restore as many loads as possible following a fault, which is usually accomplished by reconfiguring the power network. In most cases, the load is assumed to be a constant power load, and thus has no effect on the final network topology. According to recent research, the type of load and its equivalent model could influence how the network is reconfigured. This paper highlights and investigates the impact of various load types on the reconfiguration/self-healing scheme. A sensitivity analysis was performed on an islanded IEEE-69 bus system with probabilistic wind turbines (WTs) and several dispatchable distributed generation (DGs) units. The cases examine the system with separate load types and then with a mix of load types. The results show that the load type affects the final topology of the system as well as the amount of energy not served after reconfiguration.

Original language	British English
Title of host publication	Proceedings - 2023 IEEE PES GTD International Conference and Exposition, GTD 2023
Editors	Mehmet Tahir Sandikkaya, Omer Usta
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	414-418
Number of pages	5
ISBN (Electronic)	9781728170251
DOIs	https://doi.org/10.1109/GTD49768.2023.00104
State	Published - 2023
Event	2023 IEEE PES Generation, Transmission and Distribution International Conference and Exposition, GTD 2023 - Istanbul, Turkey Duration: 22 May 2023 → 25 May 2023

Publication series

Name	Proceedings - 2023 IEEE PES GTD International Conference and Exposition, GTD 2023

Conference

Conference	2023 IEEE PES Generation, Transmission and Distribution International Conference and Exposition, GTD 2023
Country/Territory	Turkey
City	Istanbul
Period	22/05/23 → 25/05/23

UN SDGs

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

SDG 7 Affordable and Clean Energy

Keywords

distribution system
load modeling
reconfiguration
Self-healing

Access to Document

10.1109/GTD49768.2023.00104

OpenUrl availability

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Cite this

Alkuwaiti, R. H., Farag, H. E. Z., El-Sayed, W., Al-Durra, A., & El-Sadaany, E. F. (2023). Exploring the Effect of Different Load Models on System Reconfiguration. In M. T. Sandikkaya, & O. Usta (Eds.), Proceedings - 2023 IEEE PES GTD International Conference and Exposition, GTD 2023 (pp. 414-418). (Proceedings - 2023 IEEE PES GTD International Conference and Exposition, GTD 2023). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/GTD49768.2023.00104

Alkuwaiti, Rawdha H. ; Farag, Hany E.Z. ; El-Sayed, Wael et al. / Exploring the Effect of Different Load Models on System Reconfiguration. Proceedings - 2023 IEEE PES GTD International Conference and Exposition, GTD 2023. editor / Mehmet Tahir Sandikkaya ; Omer Usta. Institute of Electrical and Electronics Engineers Inc., 2023. pp. 414-418 (Proceedings - 2023 IEEE PES GTD International Conference and Exposition, GTD 2023).

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Alkuwaiti, RH, Farag, HEZ, El-Sayed, W, Al-Durra, A & El-Sadaany, EF 2023, Exploring the Effect of Different Load Models on System Reconfiguration. in MT Sandikkaya & O Usta (eds), Proceedings - 2023 IEEE PES GTD International Conference and Exposition, GTD 2023. Proceedings - 2023 IEEE PES GTD International Conference and Exposition, GTD 2023, Institute of Electrical and Electronics Engineers Inc., pp. 414-418, 2023 IEEE PES Generation, Transmission and Distribution International Conference and Exposition, GTD 2023, Istanbul, Turkey, 22/05/23. https://doi.org/10.1109/GTD49768.2023.00104

Exploring the Effect of Different Load Models on System Reconfiguration. / Alkuwaiti, Rawdha H.; Farag, Hany E.Z.; El-Sayed, Wael et al.
Proceedings - 2023 IEEE PES GTD International Conference and Exposition, GTD 2023. ed. / Mehmet Tahir Sandikkaya; Omer Usta. Institute of Electrical and Electronics Engineers Inc., 2023. p. 414-418 (Proceedings - 2023 IEEE PES GTD International Conference and Exposition, GTD 2023).

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

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AB - The self-healing framework has always aimed to restore as many loads as possible following a fault, which is usually accomplished by reconfiguring the power network. In most cases, the load is assumed to be a constant power load, and thus has no effect on the final network topology. According to recent research, the type of load and its equivalent model could influence how the network is reconfigured. This paper highlights and investigates the impact of various load types on the reconfiguration/self-healing scheme. A sensitivity analysis was performed on an islanded IEEE-69 bus system with probabilistic wind turbines (WTs) and several dispatchable distributed generation (DGs) units. The cases examine the system with separate load types and then with a mix of load types. The results show that the load type affects the final topology of the system as well as the amount of energy not served after reconfiguration.

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ER -

Alkuwaiti RH, Farag HEZ, El-Sayed W, Al-Durra A , El-Sadaany EF. Exploring the Effect of Different Load Models on System Reconfiguration. In Sandikkaya MT, Usta O, editors, Proceedings - 2023 IEEE PES GTD International Conference and Exposition, GTD 2023. Institute of Electrical and Electronics Engineers Inc. 2023. p. 414-418. (Proceedings - 2023 IEEE PES GTD International Conference and Exposition, GTD 2023). doi: 10.1109/GTD49768.2023.00104

Exploring the Effect of Different Load Models on System Reconfiguration

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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