Modeling and Control of Hybrid Distribution Transformers for Simultaneous Grid Services
Martin Doff-Sotta, Florian Cech, Rishabh Manjunatha, Costantino Citro, Matthew Williams, Thomas Morstyn
TL;DR
This work develops an averaged three-phase model of a hybrid distribution transformer (HDT) with two back-to-back voltage-source converters in a series-shunt topology and demonstrates that simple decentralised PI controllers in the dq0 reference frame can deliver multiple grid services. The control architecture comprises inner loops for load-voltage and shunt-current regulation and outer loops for DC-link maintenance, power-factor correction, frequency regulation, and phase balancing, enabling simultaneous ancillary services with minimal cross-coupling. Numerical experiments in Python validate rapid responses to voltage disturbances, reactive-power compensation, and frequency deviations, as well as robust performance under unbalanced loads and concurrent service delivery. The results suggest that HDTs offer a cost-effective, scalable path to enhanced grid support, with a clear analogy to UPQC devices and potential applicability to broader distributed energy resource coordination.
Abstract
Hybrid distribution transformers (HDTs) integrate conventional transformers with partially rated power electronic converters to improve power quality, enable advanced ancillary services and increase penetration of renewable energy sources in the national power grid. In this paper, we present an averaged mathematical model of a three-phase HDT equipped with two back-to-back voltage source converters connected in a series-shunt configuration. Cascaded PI controllers are designed in the synchronously rotating dq0 reference frame to regulate load voltage, compensate reactive power, achieve grid frequency regulation, and perform load phase balancing. Simulation results implemented in Python confirm that these simple yet effective control mechanisms allow HDTs to offer simultaneous grid services without introducing complexity. The complete model, control architecture, and implementation steps are detailed, enabling further validation and adoption.
