Probabilistic Joint Active and Reactive Power Management in an Active Distribution Network

Abstract

An active distribution network comprises renewable generation sources like solar and wind. Also, an active distribution network feeds electrical loads and plug-in hybrid electric vehicles. An optimal active and reactive power management strategy is imperative for a technically feasible and financially viable operation. The renewable sources are interfaced via power electronic voltage source converters, which can control the reactive power injection into the network. In this paper, a joint optimal active and reactive power control strategy is proposed, which utilizes the reactive power handling capability of the voltage source converters. Uncertainties of renewable generation, load demand, grid energy price, and charging load demand of the plug-in hybrid electric vehicles are modeled and incorporated using the probabilistic "Hong's point estimate method". A group of measures like optimal procurement of active and reactive power from available resources, optimal battery energy storage scheduling, demand response, smart transformer scheduling, and network reconfiguration are carried out to maximize the expected profit of the distribution network operator. The proposed method is validated by simulation studies on a thirty-three bus active distribution network.