Distributed Average Integral Control Based Energy Management Model

Neelofar Shaukat; Bilal Khan; Muhamamd Bilal Qureshi; Muhammad Jawad; Noman Shabbir; Kamran Daniel

doi:10.1109/ETFG55873.2023.10407358

Distributed Average Integral Control Based Energy Management Model

Neelofar Shaukat^*, Bilal Khan, Muhamamd Bilal Qureshi, Muhammad Jawad, Noman Shabbir, Kamran Daniel

^*Corresponding author for this work

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

Abstract

In this research study, we proposed a Distributed Average Integral (DAI) control-based Energy Management Model (EMM) to achieve the economic load dispatch and consensus within a distributed energy system. The proposed model incorporates the Laplacian graph theory for establishing communication among energy districts (acting as agents/nodes) and optimizing the power distribution while satisfying the load demand. In order to evaluate the effectiveness of the proposed model, simulations are performed using MATLAB. The simulation results illustrate that the DAI control mechanism ensures the optimized power distribution leading to enhanced resource utilization while effectively achieving economic consensus among energy districts. However, in this study ideal case scenario is assumed. Therefore, this research study may highlight the potential for future investigations on utilizing the DAI control for EMM in practical scenarios with real-world challenges such as system complexities, losses, and communication delays.

Original language	English
Title of host publication	2023 IEEE International Conference on Energy Technologies for Future Grids, ETFG 2023
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781665471640
DOIs	https://doi.org/10.1109/ETFG55873.2023.10407358
State	Published - 2023
Externally published	Yes
Event	2023 IEEE International Conference on Energy Technologies for Future Grids, ETFG 2023 - Wollongong, Australia Duration: 3 Dec 2023 → 6 Dec 2023

Publication series

Name	2023 IEEE International Conference on Energy Technologies for Future Grids, ETFG 2023

Conference

Conference	2023 IEEE International Conference on Energy Technologies for Future Grids, ETFG 2023
Country/Territory	Australia
City	Wollongong
Period	3/12/23 → 6/12/23

Bibliographical note

Publisher Copyright:
© 2023 IEEE.

Keywords

Distributed Average Integral Control
Energy Districts
Graph Theory
Power Consensus

ASJC Scopus subject areas

Artificial Intelligence
Energy Engineering and Power Technology
Renewable Energy, Sustainability and the Environment
Electrical and Electronic Engineering
Control and Optimization
Safety, Risk, Reliability and Quality

Access to Document

10.1109/ETFG55873.2023.10407358

Cite this

Shaukat, N., Khan, B., Qureshi, M. B., Jawad, M., Shabbir, N., & Daniel, K. (2023). Distributed Average Integral Control Based Energy Management Model. In 2023 IEEE International Conference on Energy Technologies for Future Grids, ETFG 2023 (2023 IEEE International Conference on Energy Technologies for Future Grids, ETFG 2023). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ETFG55873.2023.10407358

Shaukat, Neelofar ; Khan, Bilal ; Qureshi, Muhamamd Bilal et al. / Distributed Average Integral Control Based Energy Management Model. 2023 IEEE International Conference on Energy Technologies for Future Grids, ETFG 2023. Institute of Electrical and Electronics Engineers Inc., 2023. (2023 IEEE International Conference on Energy Technologies for Future Grids, ETFG 2023).

@inproceedings{d1ce5f69169d4a85b76b1a91f3953ea7,

title = "Distributed Average Integral Control Based Energy Management Model",

abstract = "In this research study, we proposed a Distributed Average Integral (DAI) control-based Energy Management Model (EMM) to achieve the economic load dispatch and consensus within a distributed energy system. The proposed model incorporates the Laplacian graph theory for establishing communication among energy districts (acting as agents/nodes) and optimizing the power distribution while satisfying the load demand. In order to evaluate the effectiveness of the proposed model, simulations are performed using MATLAB. The simulation results illustrate that the DAI control mechanism ensures the optimized power distribution leading to enhanced resource utilization while effectively achieving economic consensus among energy districts. However, in this study ideal case scenario is assumed. Therefore, this research study may highlight the potential for future investigations on utilizing the DAI control for EMM in practical scenarios with real-world challenges such as system complexities, losses, and communication delays.",

keywords = "Distributed Average Integral Control, Energy Districts, Graph Theory, Power Consensus",

author = "Neelofar Shaukat and Bilal Khan and Qureshi, \{Muhamamd Bilal\} and Muhammad Jawad and Noman Shabbir and Kamran Daniel",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 IEEE International Conference on Energy Technologies for Future Grids, ETFG 2023 ; Conference date: 03-12-2023 Through 06-12-2023",

year = "2023",

doi = "10.1109/ETFG55873.2023.10407358",

language = "English",

series = "2023 IEEE International Conference on Energy Technologies for Future Grids, ETFG 2023",

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

booktitle = "2023 IEEE International Conference on Energy Technologies for Future Grids, ETFG 2023",

address = "United States",

}

Shaukat, N, Khan, B, Qureshi, MB, Jawad, M, Shabbir, N & Daniel, K 2023, Distributed Average Integral Control Based Energy Management Model. in 2023 IEEE International Conference on Energy Technologies for Future Grids, ETFG 2023. 2023 IEEE International Conference on Energy Technologies for Future Grids, ETFG 2023, Institute of Electrical and Electronics Engineers Inc., 2023 IEEE International Conference on Energy Technologies for Future Grids, ETFG 2023, Wollongong, Australia, 3/12/23. https://doi.org/10.1109/ETFG55873.2023.10407358

Distributed Average Integral Control Based Energy Management Model. / Shaukat, Neelofar; Khan, Bilal; Qureshi, Muhamamd Bilal et al.
2023 IEEE International Conference on Energy Technologies for Future Grids, ETFG 2023. Institute of Electrical and Electronics Engineers Inc., 2023. (2023 IEEE International Conference on Energy Technologies for Future Grids, ETFG 2023).

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

TY - GEN

T1 - Distributed Average Integral Control Based Energy Management Model

AU - Shaukat, Neelofar

AU - Khan, Bilal

AU - Qureshi, Muhamamd Bilal

AU - Jawad, Muhammad

AU - Shabbir, Noman

AU - Daniel, Kamran

PY - 2023

Y1 - 2023

N2 - In this research study, we proposed a Distributed Average Integral (DAI) control-based Energy Management Model (EMM) to achieve the economic load dispatch and consensus within a distributed energy system. The proposed model incorporates the Laplacian graph theory for establishing communication among energy districts (acting as agents/nodes) and optimizing the power distribution while satisfying the load demand. In order to evaluate the effectiveness of the proposed model, simulations are performed using MATLAB. The simulation results illustrate that the DAI control mechanism ensures the optimized power distribution leading to enhanced resource utilization while effectively achieving economic consensus among energy districts. However, in this study ideal case scenario is assumed. Therefore, this research study may highlight the potential for future investigations on utilizing the DAI control for EMM in practical scenarios with real-world challenges such as system complexities, losses, and communication delays.

AB - In this research study, we proposed a Distributed Average Integral (DAI) control-based Energy Management Model (EMM) to achieve the economic load dispatch and consensus within a distributed energy system. The proposed model incorporates the Laplacian graph theory for establishing communication among energy districts (acting as agents/nodes) and optimizing the power distribution while satisfying the load demand. In order to evaluate the effectiveness of the proposed model, simulations are performed using MATLAB. The simulation results illustrate that the DAI control mechanism ensures the optimized power distribution leading to enhanced resource utilization while effectively achieving economic consensus among energy districts. However, in this study ideal case scenario is assumed. Therefore, this research study may highlight the potential for future investigations on utilizing the DAI control for EMM in practical scenarios with real-world challenges such as system complexities, losses, and communication delays.

KW - Distributed Average Integral Control

KW - Energy Districts

KW - Graph Theory

KW - Power Consensus

UR - https://www.scopus.com/pages/publications/85185774905

U2 - 10.1109/ETFG55873.2023.10407358

DO - 10.1109/ETFG55873.2023.10407358

M3 - Conference contribution

AN - SCOPUS:85185774905

T3 - 2023 IEEE International Conference on Energy Technologies for Future Grids, ETFG 2023

BT - 2023 IEEE International Conference on Energy Technologies for Future Grids, ETFG 2023

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2023 IEEE International Conference on Energy Technologies for Future Grids, ETFG 2023

Y2 - 3 December 2023 through 6 December 2023

ER -

Shaukat N, Khan B, Qureshi MB, Jawad M, Shabbir N, Daniel K. Distributed Average Integral Control Based Energy Management Model. In 2023 IEEE International Conference on Energy Technologies for Future Grids, ETFG 2023. Institute of Electrical and Electronics Engineers Inc. 2023. (2023 IEEE International Conference on Energy Technologies for Future Grids, ETFG 2023). doi: 10.1109/ETFG55873.2023.10407358

Distributed Average Integral Control Based Energy Management Model

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

Fingerprint

Cite this