Virtual Power Grid Reinforcement via Coordinated Volt/VAr Control

The rise in residential photovoltaics (PV) as well as other distributed energy sources poses unprecedented challenges for the operation of distribution grids. The high active power infeed of such sources during times of peak production is a stress test which distribution grids have usually not been exposed to in the past. When high amounts of active power are injected into the grid, the overall power flow is often limited because of voltages reaching their upper acceptable limits. Volt/VAr methods aim to raise this power flow limit by controlling the voltage using reactive power. This way, more active power can be transmitted safely without physically reinforcing the grid. In this paper, we use real consumption and generation data on a low-voltage CIGR\'E grid model and an experiment on a real distribution grid feeder to analyze how different Volt/VAr methods can virtually reinforce the distribution grid. We show that droop control and machine-learning-improved droop control virtually reinforce the grid but do not utilize the reactive power resources to their full extent. In contrast, methods which coordinate the usage of reactive power resources across the grid, such as \ac{OFO}, can reinforce the grid to its full potential. The simulation study performed on data of an entire year suggests that Online Feedback Optimization (OFO) can enable another 9\% of maximum active power injections. To achieve that, OFO only requires voltage magnitude measurements, minimal model knowledge and communication with the reactive power sources. A real-life experiment provides a demonstration of how OFO acts at the level of a single device, and proves the practical feasibility of the proposed approach.