Optimising microgrid power flow: Performance benchmarking of sparse matrix solvers against Fed-G-MARL

Ayemere P. Oriaifo; Ramesh C. Bansal

doi:10.1016/j.segan.2026.102416

Optimising microgrid power flow: Performance benchmarking of sparse matrix solvers against Fed-G-MARL

Ayemere P. Oriaifo
, Ramesh C. Bansal

Research output: Contribution to journal › Article › peer-review

Original language	English
Article number	102416
Journal	Sustainable Energy, Grids and Networks
Volume	47
DOIs	https://doi.org/10.1016/j.segan.2026.102416
State	Published - Sep 2026
Externally published	Yes

ASJC Scopus Subject Areas

Control and Systems Engineering
Renewable Energy, Sustainability and the Environment
Energy Engineering and Power Technology
Electrical and Electronic Engineering

Keywords

Decentralised energy management system (EMS)
Federated learning (FL)
Graph neural networks (GNN)
IEEE 1547
Optimal power flow (OPF)
Smart microgrids
Twin delayed DDPG (TD3)

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KW - Smart microgrids

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Optimising microgrid power flow: Performance benchmarking of sparse matrix solvers against Fed-G-MARL

ASJC Scopus Subject Areas

Keywords

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