Fuju Zhou^*, Li Li, Tengfei Jia, Yongchang Yin, Aixiang Shi, Shengrong Xu

Energy Engineering, Vol.121, No.6, pp. 1697-1711, 2024, DOI:10.32604/ee.2024.047680

Abstract When a line failure occurs in a power grid, a load transfer is implemented to reconfigure the network by changing the states of tie-switches and load demands. Computation speed is one of the major performance indicators in power grid load transfer, as a fast load transfer model can greatly reduce the economic loss of post-fault power grids. In this study, a reinforcement learning method is developed based on a deep deterministic policy gradient. The tedious training process of the reinforcement learning model can be conducted offline, so the model shows satisfactory performance in real-time operation, More >

Ramanjaneyulu Kolla^*, Vinayagasundaram Ganesh, Rajendran Sakthivel, Arumugam Kumar Boobalasenthilraj

Computer Systems Science and Engineering, Vol.45, No.3, pp. 3115-3134, 2023, DOI:10.32604/csse.2023.033077

Abstract The braking quality is considered the main execution of the adaptive control framework that impacts the vehicle safety and rides solace astoundingly notably the stopping distance. This research work aims to create a pattern and design of an electromechanically adjusted lever that multiplies the applied braking force depending on the inputs given by the sensors to reduce the stopping distance of the vehicle. It is carried out using two main parts of the two-wheeler vehicle: the first part deals with the detection of load acting on the vehicle and identifying the required braking force to… More >