Power network operators have recently faced new challenges due to an increase in the penetration of non-dispatchable renewable energy sources in power grids. Incorporating emerging flexible resources like electric vehicle parking lots (EVPLs) and demand response programs (DRPs) into power systems, could be a good solution to deal with inherent uncertainties imposed by these resources to the power grid. EVPLs can improve power system operating conditions by active and reactive power injection capabilities. The participation of consumers in DRPs can also improve energy consumption management by decreasing or shifting loads to other periods. This paper proposes a hybrid information gap decision theory (IGDT)- stochastic method to solve a transmission-constrained AC unit commitment model integrated with electric vehicle (EV), incentive-based DRP, and wind energy. The behavioural uncertainty related to EV owners is modelled using a scenario-based method. Additionally, an IGDT method is applied to manage wind energy uncertainty under a two-level optimization model. Verification of the proposed model is done under several case studies. Based on the results achieved, the proposed risk-based hybrid model allows the operator to differentiate between the risk level of existing uncertainties and apply a high-flexibility decision-making model to deal with such difficulties. Additionally, the role of the aforementioned flexible resources in the reduction of power system running costs and wind power uncertainty handling are evaluated. Numerical results confirm a 3.7% reduction in the daily operating costs as a consequence of coordinated scheduling of EVPL and DRP. Moreover, Taking advantage of reactive power injection of EVPL provides more cost saving
