A5037297917- Smart Grid Energy Management
- Optimal Power Flow Distribution
- Integrated Energy Systems Optimization
- Electric Power System Optimization
- Microgrid Control and Optimization
- Energy Load and Power Forecasting
- Power Systems and Renewable Energy
- Advanced Battery Technologies Research
- Age of Information Optimization
- Electric Vehicles and Infrastructure
- Caching and Content Delivery
- Transportation and Mobility Innovations
- Reliability and Maintenance Optimization
- Wireless Networks and Protocols
- Data Quality and Management
- Big Data Technologies and Applications
- Power System Optimization and Stability
- IoT Networks and Protocols
- HVDC Systems and Fault Protection
- Power Line Communications and Noise
- Big Data and Business Intelligence
Zhejiang University
2021-2025
Hubei University of Technology
2018
To naturally characterize the long-time sequence coupled equipment such as energy storage systems (ESS) and to enforce non-anticipativity of dispatch decisions under uncertain renewable energy, a multi-stage robust dynamic unit commitment (MRDUC) model is proposed in this paper. MRDUC transforms into programming form, which first attempt combine day-ahead optimization with intra-day dispatch. The problem solved pre-stage, simulation economic done thereafter, further refines UC decision an...
Under the carbon neutrality goals, hybrid leakage due to asymmetric emission regulation of power industry merits greater attention. This paper proposes a bi-level planning model based on flow and locational marginal prices considering grid expansion in upper transmission level Energy Hub (EH) load transfer lower distribution level. Moreover, mitigation measures are assessed modeled, following which provides solution bisection-based convergence method model. Simulation results verify impact...
This paper proposes a day-ahead and intra-day co-optimized resilience enhancement strategy for distribution systems with outages under extreme events, namely, dynamic programming formulated multi-stage hybrid stochastic-robust optimization (DSRO). The DSRO model is pioneering effort to simultaneously determine the decision corresponding policies microgrids formation, via coupling two problem value functions. It establishes framework address anticipative challenges inherent in widely-used...
To realize the potential of integrated electrical-heating systems (IEHS) for coping with uncertain renewable energy, a reserve scheduling model based on dynamic programming transformed multi-stage adaptive robust optimization (DMRO) is proposed in this paper. The DMRO enforces non-anticipativity process via temporal decomposed framework, and enhances formulation flexibility time-coupled equipment, such as energy storage (ESS). whole split into two problems under decomposition constructure,...
The current state-of-the-art approach for battery state-of-health (SOH) estimation typically employs a centralized computing framework, wherein data from local management systems (BMSs) is aggregated and trained on cloud server, due to limited resources at the BMS. However, this framework presents various challenges, including frequent communication, latency, security, degraded prediction accuracy. To address these issues, study proposes novel adaptive multipersonalized federated learning...
Abstract Cloud energy storage system (CESS) can effectively improve the utilization rate of (ESS) and reduce cost. However, there is a lack model designed for large‐scale renewable power plants (REPPs). Due to volatility intermittency generation, as well demand following scheduling plan market arbitrage, it also necessary configure ESS REPPs. if REPP builds by itself, investment relatively high. Therefore, application CESS on generation side cost increase revenue utilizing difference between...
In order to solve the optimization dispatch problem of integrated energy systems under uncertain renewable penetrating, this paper proposes a robust model electrical-heating system with temporal decomposition considering dynamic reserve domain. The proposed solves that traditional two-stage ignores non-anticipate characteristic decision, and also behaves more effectively than existing solution methods. day-ahead stage, box variable interval was equivalently transformed into interval, while...
A multi-stage robust real-time economic dispatch model (MRRTD) for power systems is proposed in this paper. The MRRTD takes the dynamic form of optimization as framework to naturally simulate operation equipment that temporally coupled, e.g., utility-level energy storage systems. For normal systems, can work directly short time slots with a rolling horizon. large-scale expands time-slot scale and generates optimal policies. With guidance, decision be swiftly made thereafter. In addition,...