Robust Resilience Enhancement Considering EVs Emergency Response Under Endogenous and Exogenous Uncertainties

With the rapid advances in wireless communications and internet-of-thing (IoT) technologies, a mass quantity of electric vehicles (EVs) can serve as mobile energy resources based on the vehicle-to-grid (V2G) infrastructure. The emergency response of EVs has become a economically viable solution for enhancing the resilience of power distribution networks (PDNs) against extreme weather events. This paper presents a robust resilience enhancement approach for the PDN by fully exploiting the EVs aggregation as mobile emergency resources. Particularly, the influence of financial incentives (offered by grid operators) on the spatio-temporal distribution of EV fleets (i.e., a higher incentive may attract more EVs to support the on-emergency power supply) are considered and analytically modeled. To capture the endogenous uncertainty of EVs' distribution associated with the incentive offering strategy, a decision-dependent uncertainty (DDU) set is developed. Also, the faults of distribution feeders under severe N - k contingencies are modeled as conventional exogenous uncertainties. A complex robust optimization problem with a mixture of endogenous and exogenous uncertainty models is developed, and efficiently solved through the customized parametric column-and-constraint generation (C&CG) algorithm. Numerical results on a 33-bus test distribution system validates the resilience benefits and economical feasibility of the proposed method. The significance of DDU modeling for network resilience enhancement is demonstrated and highlighted.