Resilient unit commitment against extreme cold events considering decision-dependent uncertainty-featured EV demand response

• The temperature-sensitive EV charging load model change under extreme cold events. • The decision-dependent uncertainty (DDU) in demand response (DR) from EV loads. • A resilient unit commitment model against extreme cold events considering the temperature-sensitive EV loads and the DR from EVs. • Demonstration of the proposed model on a modified IEEE 30-bus system. With the escalating frequency of extreme cold events, power systems integrating electric vehicles (EVs) will continually confront resource inadequacy challenges due to the changes of temperature-sensitive EV loads. Despite the potential of EV loads offering emergency demand response (DR) for addressing such challenges, the willingness of EVs to respond to DR and the actual response quantity are uncertain. Furthermore, the uncertainty level in EV response varies along with DR incentive decisions, which further aggravates operation challenges. This paper proposes a resilient unit commitment (UC) model for EV-integrated power systems against extreme cold events. Specifically, first, we model how the temperature-sensitive EV charging loads change under extreme cold events considering the actual driving range and air conditioning load in EVs. Then, the inter-coupling relationship between uncertainties in EV response quantity and the DR incentive decisions is modeled. To overcome the limitations of conventional modeling approaches for decision-independent uncertainty, an affine function-based tractable model reformulation is presented addressing decision-dependent uncertainty (DDU) in EV response. Subsequently, we establish the resilient UC model within a two-stage stochastic framework considering temperature-sensitive EV loads and DDU in EVs’ response behaviors. Case studies on a modified IEEE 30-bus system verify the effectiveness of the proposed UC model in cost-efficiently and reliably accommodating increased EV loads under extreme cold events.