Aiming at the problem of source-load uncertainty caused by the increasing penetration of renewable energy and the large-scale integration of electric vehicles (EVs) into modern power system, a robust optimal operation scheduling algorithm for regional integrated energy systems (RIESs) with such uncertain situations is urgently needed. Based on this background, aiming at the problem of the irregular charging demand of EV, this paper first proposes an EV charging demand model based on the trip chain theory. Secondly, a multi-RIES optimization operation model including a shared energy storage station (SESS) and integrated demand response (IDR) is established. Aiming at the uncertainty problem of renewable energy, this paper transforms this kind of problem into a dynamic robust optimization with time-varying parameters and proposes an improved robust optimization over time (ROOT) algorithm based on the scenario method and establishes an optimal scheduling mode with the minimum daily operation cost of a multi-regional integrated energy system. Finally, the proposed uncertainty analysis method is verified by an example of multi-RIES. The simulation results show that in the case of the improved ROOT proposed in this paper to solve the robust solution of renewable energy, compared with the traditional charging load demand that regards the EVs as a whole, the EV charging load demand based on the trip chain can reduce the cost of EV charging by 3.5% and the operating cost of the multi-RIES by 11.7%. With the increasing number of EVs, the choice of the starting point of the future EV trip chain is more variable, and the choice of charging methods is more abundant. Therefore, modeling the charging demand of EVs under more complex trip chains is the work that needs to be studied in the future.

In bilateral teleoperation systems, achieving fast position synchronization while maintaining high-communication efficiency represents an essential control objective. This article proposes a simplified control scheme with a finite-time proportional damping (FTP+d) injection method and an event-driven communication mechanism to address the challenge of position synchronization in time-delayed telerobotic systems. The system takes into account the asymmetric time-varying delays and external forces. First, a novel event-triggered strategy based on noninteger power is designed. With a designed error-velocity mixed variable, a new FTP+d controller is developed by employing a continuous nonsmooth function, a damping term, an adaptive term, and noninteger power. With the Lyapunov–Krasovskii (LK) method and the finite-time stability theory, the boundedness of the telerobot’s state is established, and the finite-time synchronization performance is analytically guaranteed. Furthermore, the relationships between controller parameters, time-varying delays, and system stability are also analyzed based on linear matrix inequality (LMI). Finally, both simulation and experimental investigations are conducted to evaluate the efficacy and performance of the proposed control approach.