To study the role of energy system demand‐side regulation capacity on carbon emission reduction, we proposed a regional integrated energy system (RIES) optimal dispatch model considering carbon trading cost and dynamic demand response (DR). First, based on the framework of the RIES, the impact of DR of transferable load, reducible load, and substitutable load demand on system operation, considering the response characteristics of electrical and thermal load, was analyzed. Second, the carbon quota of the system was analyzed, and the effect of carbon emissions and carbon capture technology on system operation was considered. Finally, a low carbon optimized operation model of RIES was established with system operating cost and operating efficiency as the target, and system capacity and energy storage power as the constraints. The effectiveness of the optimized operation of the improved intelligent evolutionary algorithm nondominated sorting genetic algorithm II (NSGA‐II) was verified as a research method. The results show that the energy efficiency of the system can be improved by tuning the DR of load demand with the application of the optimal operation model, and a coordination optimization on the economic and low carbon in RIES operation can also be achieved by the improved NSGA‐II algorithm.

Since the rolling bearing fault signal captured by a vibration sensor contains a large amount of background noise, fault features cannot be accurately extracted. To address this problem, a rolling bearing fault feature extraction algorithm based on improved pelican optimization algorithm (IPOA)–variable modal decomposition (VMD) and multipoint optimal minimum entropy deconvolution adjustment (MOMEDA) methods is proposed. Firstly, the pelican optimization algorithm (POA) was improved using a reverse learning strategy for dimensional-by-dimensional lens imaging and circle mapping, and the optimization performance of IPOA was verified. Secondly, the kurtosis-square envelope Gini coefficient criterion was used to select the optimal modal components from the decomposed components of the signal, and MOMEDA was used to process the optimal modal components in order to obtain the optimal deconvolution signal. Finally, the Teager energy operator (TEO) was employed to demodulate and analyze the optimally deconvoluted signal in order to enhance the transient shock component of the original fault signal. The effectiveness of the proposed method was verified using simulated and actual signals. The results showed that the proposed method can accurately extract failure characteristics in the presence of strong background noise interference.

In order to solve the problems of Bidirectional RRT algorithm in the path planning of mobile robots, such as path zigzag, path passing through obstacles, and the distance between paths and obstacles is too close, an improved bidirectional RRT algorithm is proposed. The algorithm follows the basic framework of bidirectional RRT algorithm and adds a cubic spline method to smooth the path to solve the problem of zigzag path. Add more waypoints to the original path, and then set the judgment distance between each waypoint and obstacle according to the required distance between the path and obstacle to solve the problem that the path passes the obstacle and the path is too close to the obstacle. The simulation results show that the path generated by the algorithm is smooth, the probability of the path passing the obstacle is very low, and the distance between the path and the obstacle is suitable, which is easy to track and control the mobile robot.