Regression-based inverter control for power flow and voltage regulation

Rapid and substantial voltage changes can occur in distribution networks with a high pen- etration of photovoltaic (PV) systems, due to their unpredictable nature. Electronic power inverters are capable of delivering fast reactive power support to maintain customer voltages within operating tolerances and reduce system losses in distribution feeders. While optimization based paradigms have been proposed to control the reactive power output of inverters, these methods typically rely on the presence of an extensive and fast communication infrastructure which is currently not in place and would be expensive to build. On the other hand, approaches that utilize completely local data require the design of a relation between local measurements and inverter output (i.e. a Volt-VAr curve). These relationships are often naively designed and typically do not yield optimal results. In this work, a systematic and data driven approach is presented to determine PV inverter output as a function of locally obtained measurements in a manner that obtains near optimal results. First, a network model and historic information are used to compute globally optimal settings a posteriori for all controllable inverters in the network. Subsequently, a regression approach is used to find a function for each inverter that maps the solely local historical data to an approximation of the globally optimal inverter output. The resulting functions are then employed as decentralized controllers of the inverters and approximate the globally optimal reactive power outputs based on local measurements only. Simulation results on real feeder models demonstrate that this method achieves near optimal results when performing voltage- and capacity-constrained loss minimization and voltage flattening. This method paves the way to an efficient voltage optimization scheme in which legacy control equipment collaborates with existing inverters to facilitate safe operation of distribution networks with higher levels of distributed generation.Systems and ControlDelft Center for Systems and ControlMechanical, Maritime and Materials Engineerin