Data-Driven-Based Optimization for Power System Var-Voltage Sequential Control

This paper proposes a data-driven-based optimization method for var-voltage sequential control (V2SC). First, power system var-voltage control characteristics, defined as the function between the reactive power injections and the bus voltages, are approximated by the var-voltage sensitivities (V2S). Then, V2S is estimated online using the noise-assisted ensemble regression method. Subsequently, an optimal model is proposed for V2SC based on the V2S estimation. To avoid frequent back and forth control actions, a hysteresis control strategy is employed. The performance of the proposed method is statistically validated in the 8-generator 36-node system and the Nordic32 system with test data measured from real power systems.