Decentralized Stochastic Recursive Gradient Method for Fully Decentralized OPF in Multi-Area Power Systems

This paper addresses the critical challenge of optimizing power flow in multi-area power systems while maintaining information privacy and decentralized control. The main objective is to develop a novel decentralized stochastic recursive gradient (DSRG) method for solving the optimal power flow (OPF) problem in a fully decentralized manner. Unlike traditional centralized approaches, which require extensive data sharing and centralized control, the DSRG method ensures that each area within the power system can make independent decisions based on local information while still achieving global optimization. Numerical simulations are conducted using MATLAB (Version 24.1.0.2603908) to evaluate the performance of the DSRG method on a 3-area, 9-bus test system. The results demonstrate that the DSRG method converges significantly faster than other decentralized OPF methods, reducing the overall computation time while maintaining cost efficiency and system stability. These findings highlight the DSRG method’s potential to significantly enhance the efficiency and scalability of decentralized OPF in modern power systems.

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Publication Details

Journal
Mathematics
Published
2024-09-30
DOI
https://doi.org/10.3390/math12193064
Citations
24
Primary Topic
Optimal Power Flow Distribution
Type
article
Field-Weighted Citation Impact
5.01

Funders

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article

Decentralized Stochastic Recursive Gradient Method for Fully Decentralized OPF in Multi-Area Power Systems

Umair Hussan, Hui Jiang, Muhammad Ahsan Ayub, Huaizhi Wang et al.
24 citations
Mathematics
Optimal Power Flow Distribution
5.01
article

Decentralized Stochastic Recursive Gradient Method for Fully Decentralized OPF in Multi-Area Power Systems

Umair Hussan, Hui Jiang, Muhammad Ahsan Ayub, Huaizhi Wang, Hamna Rasheed, Muhammad Asghar Majeed, Jianchun Peng
article en
24 citations

Abstract

This paper addresses the critical challenge of optimizing power flow in multi-area power systems while maintaining information privacy and decentralized control. The main objective is to develop a novel decentralized stochastic recursive gradient (DSRG) method for solving the optimal power flow (OPF) problem in a fully decentralized manner. Unlike traditional centralized approaches, which require extensive data sharing and centralized control, the DSRG method ensures that each area within the power system can make independent decisions based on local information while still achieving global optimization. Numerical simulations are conducted using MATLAB (Version 24.1.0.2603908) to evaluate the performance of the DSRG method on a 3-area, 9-bus test system. The results demonstrate that the DSRG method converges significantly faster than other decentralized OPF methods, reducing the overall computation time while maintaining cost efficiency and system stability. These findings highlight the DSRG method’s potential to significantly enhance the efficiency and scalability of decentralized OPF in modern power systems.

MathematicsVol. 12(19)
Chulalongkorn University (TH), Shenzhen University (CN)
National Natural Science Foundation of China, Natural Science Foundation of Guangdong Province
Openalex Percentile: Top 4%
Optimal Power Flow Distribution
5.01
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Decentralized Stochastic Recursive Gradient Method for Fully Decentralized OPF in Multi-Area Power Systems — Umair Hussan, Hui Jiang, et al. · Mathematics (2024) | TGRS Research Map | TGRS