Supplementary Feedforward Voltage Control in a Reconfigurable Distribution Network using Robust Optimization

Network reconfiguration (NR) has attracted much attention due to its ability to convert conventional distribution networks (DNs) into self-healing grids. This paper proposes a new strategy for real-time voltage regulation (VR) in a reconfigurable DN, whereby optimal feedforward control of distributed generators (DGs) is achieved in coordination with the operation of line switches (SWs). This enables preemptive compensation of upcoming deviations in DN voltages resulting from NR-aided load restoration. A robust optimization problem is formulated using a dynamic analytical model of NR to design the feedforward voltage controllers (FVCs) that minimize voltage deviations with respect to the
H
_∞
norm. Errors in the estimates of DG modeling parameters and load demands are reflected in the design of optimal FVCs via polytopic uncertainty modeling. Small-signal analysis and case studies are conducted, verifying the effectiveness and robustness of the optimal FVCs in improving real-time VR when NR is activated for load restoration. The performance of the proposed FVCs is confirmed under various conditions of a self-healing DN,characterized by network islanding and size, parameter errors, SW operations, and communication time delays.