Optimal Placement and Sizing of Hybrid Distribution Transformers in Active Distribution Networks Under Load and PV Generation Uncertainty

The increasing integration of renewable energy sources in modern power systems has intensified challenges such as voltage sags, swells, and phase imbalances. Hybrid distribution transformers (HDT) offer a cost-effective solution with their low operational costs, reduced power loss, and high reliability. This paper introduces a robust optimization approach for the optimal placement and sizing of HDT in active distribution networks (ADNs), accounting for uncertainties in load and photovoltaic (PV) generation. We enhance model accuracy by proposing an improved branch power flow model that addresses three-phase imbalances and incorporates coupling coefficients. Our robust optimization framework seeks to minimize operational costs under worst-case scenarios by combining a centralized control strategy for reactive power optimization with a particle swarm optimization (PSO) algorithm for HDT placement and sizing. The effectiveness of the proposed method is validated on a modified IEEE 33-node system, demonstrating significant improvements in network performance and reliability.