Fast Adaptive Reactive-Power Compensation Control for Renewable Power Plants Considering Dynamic Active-Power–Voltage Coupling
Abstract
Renewable power plants connected to low-system-strength grids are increasingly dominated by inverter-based resources (IBRs). Their point of common coupling (PCC) voltage is therefore shaped not only by reactive-power support but also by active-power ramps, network impedance, short-circuit capacity, and converter limits. Conventional Q-V droop control, fixed power-factor control, Volt/VAR control, and fixed active-power/reactive-power (P/Q) decoupling schemes often absorb active-power excursions into the voltage error, which can drive excessive reactive-power injection during fault clearing, post-fault power recovery, and phase-angle disturbances. Here, an active-power–voltage-coupling-aware reactive-power compensation (APVQ-RC) method is proposed for plant-level voltage control. The method estimates local P-V and Q-V voltage sensitivities online, reconstructs an effective voltage error, and produces a capacity-constrained reactive-power reference through smooth coupling activation. The reduced-order evaluation includes estimator conditioning, excitation screening, sensitivity-estimation error and empirical 95% estimator-error intervals, sensitivity to the smoothing factor and window length, measurement noise, converter capability saturation, and computational timing. Under P-V-coupled transients, APVQ-RC reduces voltage overshoot and reactive-power compensation energy while retaining Q-V-like support during voltage-sag-dominated events. Compared with the best scanned fixed P/Q baseline, it reduces overshoot, reactive-power compensation energy, and reactive-power peak by 42.03%, 60.35%, and 8.90%, respectively; the representative single-step calculation time is 0.0188 ms within a 1 ms control cycle. These results indicate millisecond-scale plant-level feasibility within the reduced model, while electromagnetic-transient, hardware-in-the-loop, and field validation remain necessary before deployment.