A hybrid Robust-Stochastic optimization model for planned outage based Day-Ahead scheduling of a Plug-in electric vehicles parking lot. (December 2022) - Hooshyar Mobaraki, Almas; Salyani, Pouya; Safari, Amin; Quteishat, Anas; Younis, Mahmoud A.
Highlights: Model of optimal operation of a smart PEV parking lot (PEPL) with hydrogen storage. Presenting a hybrid robust-stochastic model of day-ahead scheduling of the PEPL. Considering the arrival and departure times of PEVs and PV as uncertain parameters. The PEV pricing mechanism to implement a single-criterion approach. Evaluating day-ahead PO-oriented scheduling using various risk strategies. Abstract: The growth of plug-in electric vehicles (PEVs) in recent decades and their impact on the operation of distribution networks have necessitated the requirement for PEV parking lots (PEPLs). With respect to the development of technology advances, PEPLs can benefit from charging the PEVs and selling the discharge power of PEVs (with V2G ability) to the grid. Besides, the load growth, the aging of the components and their thermal limitations enforce the distribution network operator to de-energize some of the zones to lighten the peak load. This de-energization with day-ahead notification is accounted for as a planned outage (PO). Such outages can have an adverse effect on the PEPL's daily revenue. This paper introduces a hybrid robust-stochastic model for optimal day-ahead scheduling of the PEPL with renewable generation and considering the inherent uncertainties. The proposed model of the day-ahead scheduling is subject to the PO notified by the distribution network operator and concerns profit maximization in a way that mitigates the power shortage problem in the PO period. This PO-oriented scheduling helps the owner of the PEPL to successfully provide service for the PEVs at a minimum cost.