Probabilistic power management of a grid-connected microgrid considering electric vehicles, demand response, smart transformers, and soft open points

Abstract

The uncertainty of renewable energy generation and additional EV charging load requirements pose challenges to power system operation. The present work proposes a novel probabilistic energy management strategy comprising a coordinated Volt/Var and active power management strategies to minimize the cost of operation, improve the voltage profile, and enhance the voltage stability of the microgrid. The proposed active power management strategy comprises an implementation of an optimal incentive-based demand response strategy, economic scheduling of dispatchable generation sources, and optimal dispatch of battery energy storage system. The optimal Volt/Var strategy comprises a coordinated operation of soft open points, network reconfiguration, and the use of smart transformers. Stochastic modeling of renewable generation uncertainties, load demand, plug-in hybrid electric vehicle charging load demand, and grid energy price are carried out using the “Hong’s 2m point estimate method”. The proposed approach is validated by simulation studies on a thirty-node grid-connected microgrid system. The proposed coordinated energy management strategy can reduce the daily expected cost by ∼19.36% and the daily expected network loss by ∼60.29%. The voltage profile and the voltage stability are also significantly improved.