Publications, Activities, and Awards
- A Novel Model-Free Deep Reinforcement Learning Framework for Energy Management of a PV Integrated Energy Hub
- An Improved Actor-Critic Reinforcement Learning with Neural Architecture Search for the Optimal Control Strategy of a Multi-Carrier Energy System
- Deep Reinforcement Learning-Based Self-Scheduling Strategy for a CAES-PV System Using Accurate Sky Images-Based Forecasting
- Deep Spatial-Temporal 2-D CNN -BLSTM Model for Ultrashort-Term LiDAR-Assisted Wind Turbine's Power and Fatigue Load Forecasting
- Evolutionary-Based Neural Architecture Search for an Efficient CAES and PV Farm Joint Operation Strategy Using Deep Reinforcement Learning
- Hybrid Deep Learning-Based Model for Wind Speed Forecasting Based on DWPT and Bidirectional LSTM Network
- SFNAS-DDPG: A Biomass-Based Energy Hub Dynamic Scheduling Approach via Connecting Supervised Federated Neural Architecture Search and Deep Deterministic Policy Gradient