  As power systems become more complex and uncertain, low-voltage distribution
networks face numerous challenges, including three-phase imbalances caused by
asymmetrical loads and distributed energy resources. We propose a robust
stochastic optimization (RSO) based optimal power flow (OPF) control method for
three-phase, four-wire low-voltage distribution networks that consider
uncertainty to address these issues. Using historical data and deep learning
classification methods, the proposed method simulates optimal system behaviour
without requiring communication infrastructure. The simulation results verify
that the proposed method effectively controls the voltage and current amplitude
while minimizing the operational cost and three-phase imbalance within
acceptable limits. The proposed method shows promise for managing uncertainties
and optimizing performance in low-voltage distribution networks.
