Fast Distributed Resource Allocation of Smart Grid: A Zeroth-Order Optimization Algorithm

Meng LUAN; Guanghui WEN; Wei Xing ZHENG

doi:10.1109/CDC49753.2023.10383947

Fast Distributed Resource Allocation of Smart Grid: A Zeroth-Order Optimization Algorithm

Meng LUAN
, Guanghui WEN^*
, Wei Xing ZHENG

^*Corresponding author for this work

Research output: Book Chapters | Papers in Conference Proceedings › Conference paper (refereed) › Research › peer-review

3 Citations (Scopus)

Abstract

This paper investigates a multi-objective distributed resource allocation problem, where the economic cost including the transmission loss, and the environmental pollution are taken into account simultaneously. To settle this problem, a Pareto-based zeroth-order fast distributed optimization algorithm is proposed, which can always balance the overall energy demand with generation. In the algorithm design, the acceleration idea of the momentum method is tailored for the gradient estimation update, which gives a more accurate descent direction. Moreover, the unknown effect causes the gradient of the objective function to be unavailable and only the function values to be observed. Different from the gradient-based methods, a zeroth-order method is proposed to solve the distributed resource allocation problem with gradient estimation. Furthermore, the convergence of the designed algorithm is proved theoretically, and the convergence rate of linear speedup can be achieved. Finally, numerical simulations verify the validity and applicability of the proposed algorithm.

Original language	English
Title of host publication	2023 62nd IEEE Conference on Decision and Control, CDC 2023
Publisher	IEEE
Pages	6570-6575
Number of pages	6
ISBN (Electronic)	9798350301243
ISBN (Print)	9798350301250
DOIs	https://doi.org/10.1109/CDC49753.2023.10383947
Publication status	Published - 2023
Externally published	Yes

Publication series

Name	Proceedings of the IEEE Conference on Decision and Control
Publisher	IEEE
ISSN (Print)	0743-1546
ISSN (Electronic)	2576-2370

Bibliographical note

Publisher Copyright:
© 2023 IEEE.

Funding

This work was supported in part by the National Key Research and Development Program of China under Grant No. 2022YFA1004702, in part by the National Natural Science Foundation of China through Grant Nos. U22B2046, 62073079 and 62088101, and in part by the General Joint Fund of the Equipment Advance Research Program of Ministry of Education under Grant No. 8091B022114.

UN SDGs

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

SDG 7 Affordable and Clean Energy
SDG 12 Responsible Consumption and Production

Access to Document

10.1109/CDC49753.2023.10383947

Cite this

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title = "Fast Distributed Resource Allocation of Smart Grid: A Zeroth-Order Optimization Algorithm",

abstract = "This paper investigates a multi-objective distributed resource allocation problem, where the economic cost including the transmission loss, and the environmental pollution are taken into account simultaneously. To settle this problem, a Pareto-based zeroth-order fast distributed optimization algorithm is proposed, which can always balance the overall energy demand with generation. In the algorithm design, the acceleration idea of the momentum method is tailored for the gradient estimation update, which gives a more accurate descent direction. Moreover, the unknown effect causes the gradient of the objective function to be unavailable and only the function values to be observed. Different from the gradient-based methods, a zeroth-order method is proposed to solve the distributed resource allocation problem with gradient estimation. Furthermore, the convergence of the designed algorithm is proved theoretically, and the convergence rate of linear speedup can be achieved. Finally, numerical simulations verify the validity and applicability of the proposed algorithm.",

author = "Meng LUAN and Guanghui WEN and ZHENG, \{Wei Xing\}",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.",

year = "2023",

doi = "10.1109/CDC49753.2023.10383947",

language = "English",

isbn = "9798350301250",

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Fast Distributed Resource Allocation of Smart Grid: A Zeroth-Order Optimization Algorithm. / LUAN, Meng; WEN, Guanghui; ZHENG, Wei Xing.
2023 62nd IEEE Conference on Decision and Control, CDC 2023. IEEE, 2023. p. 6570-6575 (Proceedings of the IEEE Conference on Decision and Control).

Research output: Book Chapters | Papers in Conference Proceedings › Conference paper (refereed) › Research › peer-review

TY - GEN

T1 - Fast Distributed Resource Allocation of Smart Grid: A Zeroth-Order Optimization Algorithm

AU - LUAN, Meng

AU - WEN, Guanghui

AU - ZHENG, Wei Xing

PY - 2023

Y1 - 2023

N2 - This paper investigates a multi-objective distributed resource allocation problem, where the economic cost including the transmission loss, and the environmental pollution are taken into account simultaneously. To settle this problem, a Pareto-based zeroth-order fast distributed optimization algorithm is proposed, which can always balance the overall energy demand with generation. In the algorithm design, the acceleration idea of the momentum method is tailored for the gradient estimation update, which gives a more accurate descent direction. Moreover, the unknown effect causes the gradient of the objective function to be unavailable and only the function values to be observed. Different from the gradient-based methods, a zeroth-order method is proposed to solve the distributed resource allocation problem with gradient estimation. Furthermore, the convergence of the designed algorithm is proved theoretically, and the convergence rate of linear speedup can be achieved. Finally, numerical simulations verify the validity and applicability of the proposed algorithm.

AB - This paper investigates a multi-objective distributed resource allocation problem, where the economic cost including the transmission loss, and the environmental pollution are taken into account simultaneously. To settle this problem, a Pareto-based zeroth-order fast distributed optimization algorithm is proposed, which can always balance the overall energy demand with generation. In the algorithm design, the acceleration idea of the momentum method is tailored for the gradient estimation update, which gives a more accurate descent direction. Moreover, the unknown effect causes the gradient of the objective function to be unavailable and only the function values to be observed. Different from the gradient-based methods, a zeroth-order method is proposed to solve the distributed resource allocation problem with gradient estimation. Furthermore, the convergence of the designed algorithm is proved theoretically, and the convergence rate of linear speedup can be achieved. Finally, numerical simulations verify the validity and applicability of the proposed algorithm.

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DO - 10.1109/CDC49753.2023.10383947

M3 - Conference paper (refereed)

AN - SCOPUS:85184809393

SN - 9798350301250

T3 - Proceedings of the IEEE Conference on Decision and Control

SP - 6570

EP - 6575

BT - 2023 62nd IEEE Conference on Decision and Control, CDC 2023

PB - IEEE

ER -

Fast Distributed Resource Allocation of Smart Grid: A Zeroth-Order Optimization Algorithm

Abstract

Publication series

Bibliographical note

Funding

UN SDGs

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