Electricity generation using distributed renewable energy systems is becoming increasingly
common due to the significant increase in energy demand and the high operation of …

This article proposes a hybrid policy-based reinforcement learning (HPRL) adaptive energy
management to realize the optimal operation for the island group energy system with energy …

This paper provides a thorough examination of various techniques for sharing active power
between multiple dispatchable generation sources distributed within an interconnected …

With the increasing penetration of renewable energy and flexible loads in smart grids, a
more complicated power system with high uncertainty is gradually formed, which brings …

Strategic bidding which aims to optimally harvest the price difference in the wholesale
electricity market can efficiently allocate VPPs' aggregated resources to provide large …

The development of low-carbon power systems has not only elevated the investment costs
of power enterprises, but also generated a vast amount of electricity data. The electricity data …

As a significant paradigm change in reinforcement learning, federated learning (FL) has
emerged to address the efficiency bottlenecks and privacy concerns of centralized training …

In order to improve the tracking failure caused by small-target pedestrians and partially
blocked pedestrians in dense crowds in complex environments, a pedestrian target …

Multihop data routing over a large-scale Internet of Things (IoT) network results in energy
imbalance and poor data throughput performance. In addition, data transmission using a …

This work addresses the loop closure detection issue by matching the local pose graphs for
semantic visual SLAM. We propose a deep feature matching-based keyframe retrieval …