Optimal Reactive Power Dispatch in Distribution Networks with Distributed Generation

Abstract

To address the issue that the uncertainty of renewable energy output
and load fluctuations may cause voltage limit violations after grid connection,
severely impacting the stable operation of power systems, a dynamic reactive
power optimization mathematical model for distribution networks with
distributed generators (DGs) is established. The model accounts for the daily
switching limits of DG integration locations and transformer tap ratios, with
system active power losses and voltage deviations serving as the objective
functions. A scenario reduction method combining Monte Carlo sampling and
K-means clustering is employed to significantly reduce the computational
complexity of the optimization. The improved whale optimization algorithm is
applied to conduct simulation analyses on the IEEE 33-bus. Simulation results
demonstrate that the proposed model and method can satisfy system operational
planning requirements while enhancing both economic efficiency and
operational stability.