Optimal resilient operation of smart distribution network in the presence of renewable energy resources and intelligent parking lots under uncertainties

Abstract

Due to climate changes, the occurrence of low-probability but high-impact disasters such as hurricanes, earthquakes, thunders and etc are increasing. So in the occurrence of these disasters, the resilient operation of smart distribution networks (SDNs) needs to be more investigated by researchers. To address this challenge, in this paper, the optimal resilient operation of the SDN in the presence of renewable energy resources (RERs) and intelligent parking lots (IPLs) is investigated. A hybrid stochastic-IGDT approach is developed to handle the uncertainties of the proposed model. So to do this, the stochastic method is used to modeling of RERs generation, electricity price, and EVs (arrival time, departure time, and initial energy) uncertainties. Also, due to the high impact of load uncertainties on the resilient operation of SDN, the information gap decision theory (IGDT) approach is applied to mitigate the uncertainties of load. In this paper, backup diesel generators (BDGs), battery energy storage systems (BESSs), and demand response programs (DRPs) are suggested to improve the resilient operation of SDN. In order to show the efficacy of the proposed model, four case studies are evaluated on a modified IEEE-33 bus test system. The numerical results indicate, in the risk-averse strategy, the SDN is robust against 7.2% increasing active load by having 10% more operation cost, and the resiliency of the system decrease 3.05% for the worst scenario. On the other side, in the risk-taker strategy, with decreasing 7.4% in active load, the operation cost decrease 10%, and the resiliency of the system increase 4.93%.