Our paper “Global Sensitivity Analysis in Load Modeling via Low-rank Tensor” has been accepted by IEEE Transactions on Smart Grid.
[2021/12] Our new paper on power system operation, entitled "A Review of Deep Reinforcement Learning Applications in Power System Parameter Estimation", has been accepted by 2021 PowerCon.
Related
- [2021/6] Our two new papers on load modeling, entitled "Tensor-Based Parameter Reduction of Dynamic Load Models with Variable Frequency Drive", has been accepted by IEEE Transactions on Power Systems, and "A Novel Spiking Deep Neural Network based Unsupervised Learning for Non-intrusive Load Monitoring in Smart Grid" has been accepted by MPCE.
- [2020/11] Our new paper on load analysis, entitled "Real-time Energy Disaggregation at Substations with Behind-the-Meter Solar Generation", has been accepted by IEEE Transactions on Power Systems
- [2020/10] Our new paper on load modeling, entitled "Imitation and Transfer Q-learning-Based Parameter Identification for Composite Load Modeling", has been accepted by IEEE Transactions on Smart Grid
- [2020/9] The paper “Sizing battery storage for islanded microgrid systems to enhance robustness against attacks on energy sources” has been awarded as the 2019 Best Paper of Journal of Modern Power Systems and Clean Energy (MPCE)
- [2020/8] Yishen presented the work “Two-stage WECC composite load modeling: a deep reinforcement learning approach” at the panel on “Observability and controllability of power distribution system in big data era” at the IEEE PES General Meeting (invited by Dr. Yi Wang)