Two-stage cooperative real-time autonomy control strategy considering vulnerability of active distribution networks

A two-stage cooperative real-time autonomy control strategy considering vulnerability of active distribution networks (ADNs) is proposed to solve the problems of intensified voltage fluctuation, increased network loss, and risk of voltage violation. A vulnerability index of the power grid is proposed to optimize the model from "point" to "area", which can more comprehensively evaluate the power quality of ADNs. The day-ahead stage, considering the action times of the on-load tap changer (OLTC) and capacitor bank (CB) and the reactive power response ability of the photovoltaic (PV) inverter, a relaxation-clustering-correction decoupling strategy based on Ward clustering is proposed to make the optimization results more reasonable; based on the curve-increasing particle swarm optimization (CIPSO) algorithm, a high-dimensional, strongly coupled mixed integer nonlinear model was solved. The real-time stage, taking the optimization results of the day-ahead stage as the benchmark data, based on the relationship between the reactive power increment and real-time output prediction error of PV inverter, a real-time autonomy control strategy that only relies on local real-time information is proposed by fusing voltage sensitivity information. The rationality and superiority of the proposed strategy are verified through the simulation analysis of the modified IEEE 33 bus system.