2 citations · 4 across the 6 of their papers we have counts for
8 papers
LLM-Enhanced Multi-Agent Reinforcement Learning for Unified Electric Vehicles-Charging Station-Grid Optimization in Public Charging Systems
Yang Zhang, Lindong Xie, Chongyu Wang +3
In the era of the Internet of Things (IoT), coordinating connected electric vehicle (EV) charging scheduling to balance EV charging satisfaction, station profitability, and smart g…
PE-TSFM: Self-Supervised Time-Series Learning for Generalizable Power Converter Health Monitoring under Unseen Conditions
Xinyuan Liao, Xinyue Zhang, Xing Wei +4
Data-driven health monitoring of power converters remains limited by poor generalization to unseen operating conditions. This work addresses this out-of-distribution (OOD) challeng…
Problem-Structure-Informed Quantum Approximate Optimization Algorithm for Large-Scale Unit Commitment with Limited Qubits
Jingxian Zhou, Ziqing Zhu, Linghua Zhu +1
As power systems expand, solving the Unit Commitment Problem (UCP) becomes increasingly challenging due to the dimensional catastrophe, and traditional methods often struggle to ba…
Bayesian Quantum Neural Network for Renewable-Rich Power Flow with Training Efficiency and Generalization Capability Improvements
Ziqing Zhu, Shuyang Zhu, Siqi Bu
This paper addresses the challenges of power flow calculation in large scale power systems with high renewable penetration, focusing on computational efficiency and generalization.…
Quantum Reinforcement Learning-Based Two-Stage Unit Commitment Framework for Enhanced Power Systems Robustness
Xiang Wei, Ziqing Zhu, Linghua Zhu +5
Unit commitment (UC) optimizes the start-up and shutdown schedules of generating units to meet load demand while minimizing costs. However, the increasing integration of renewable…
Evaluating Uncertainties in Electricity Markets via Machine Learning and Quantum Computing
Shuyang Zhu, Ziqing Zhu, Linghua Zhu +3
The analysis of decision-making process in electricity markets is crucial for understanding and resolving issues related to market manipulation and reduced social welfare. Traditio…
Techno-Economic Modeling and Safe Operational Optimization of Multi-Network Constrained Integrated Community Energy Systems
Ze Hu, Ka Wing Chan, Ziqing Zhu +3
The integrated community energy system (ICES) has emerged as a promising solution for enhancing the efficiency of the distribution system by effectively coordinating multiple energ…
Cooperative Dispatch of Microgrids Community Using Risk-Sensitive Reinforcement Learning with Monotonously Improved Performance
Ziqing Zhu, Xiang Gao, Siqi Bu +3
The integration of individual microgrids (MGs) into Microgrid Clusters (MGCs) significantly improves the reliability and flexibility of energy supply, through resource sharing and…