Multi-Period Optimal Power Flow for Smart Transformer-based Meshed Hybrid AC/DC Microgrids

Abstract

Smart Transformer (ST)-based Meshed Hybrid AC/DC Microgrids (MHM) present advantages concerning the performance of conventional AC/DC microgrids (MG). Despite this, MHMs present challenges in managing and controlling electronic converters associated with the ST and Distributed Energy Resources (DER), a scenario that makes it complex to achieve optimal system performance. Additionally, the high penetration of DER would impact the voltage profile, reduce the reactive compensation, and increase the losses in the distribution lines at a high cost in operation. This work proposes an optimal power management computational model for the day-ahead optimal operation planning of ST-based MHM. The management algorithm delivers the optimal operating points of each of the converters of the MG so that it allows the control of active power on both the AC and DC sides; likewise, it will enable reactive power injection control according to the availability of the solar photovoltaic resource and Battery Energy Storage Systems (BESS). According to the tests performed under different operation scenarios with varying degrees of penetration of Photovoltaic Generator (PVG), the benefits of implementing the ST as an energy router according to the operating set points by the optimization algorithm are evidenced. Integrating the ST in MHM and optimization algorithms is a suitable alternative for managing microgrids with high penetration of distributed energy resources. This allows for improving the voltage profile in the MHM, reducing losses in the lines and energy exchange costs with the distribution network.