Enhancing resilience of distribution systems: Integrating mobile energy storage systems and information gap decision theory for uncertainty management

Power Distribution Systems (PDSs) have seen considerable disruption owing to events and the intrinsic uncertainty associated with renewable energy sources (RES). The fundamental purpose of this project is to identify methods to enhance the resilience of Mobile Energy Storage Systems (MESSs) against unexpected cyber and natural disasters. Information Gap Decision Theory (IGDT) is used to effectively handle the uncertainties linked with RES's outputs. It also applies the Seasonal Autoregressive Integrated Moving Average (SARIMA) model to predict important aspects that affect the output of RES. The shift to microgrid mode prioritizes the delivery of critical loads through MESSs, which are crucial amid adverse situations. A risk-averse strategy mitigates risks associated with wind turbine and photovoltaic (PV) outputs, therefore enhancing the resilience of the PDS. An optimization model utilizing Mixed-Integer Linear Programming (MILP) was formulated. The approach's efficacy in reducing uncertainties in RES has been proved by simulations conducted on the IEEE 69 bus and Dakota transport system. Assuming the most severe situation, the Uncertainty Radius (UR) for wind turbines is 0.7385, but for PVs, it is 0.8753, thereby guaranteeing the robustness of the system against power failures and disturbances.