29 citations · 34 across the 14 of their papers we have counts for
14 papers
Bidding and Dispatch Strategies with Flexibility Quantification and Pricing for Electric Vehicle Aggregator in Joint Energy-Regulation Market
Manqi Xu, Ye Guo, Hongbin Sun
Managing and unlocking the flexibility hidden in electric vehicles (EVs) has emerged as a critical yet challenging task towards low-carbon power and energy systems. This paper focu…
Energy Internet: A Standardization-Based Blueprint Design
Ye Guo, Hanyang Lin, Hongbin Sun
The decarbonization of power and energy systems faces a bottleneck: The enormous number of user-side resources cannot be properly managed and operated by centralized system operato…
Residual Deep Reinforcement Learning for Inverter-based Volt-Var Control
Qiong Liu, Ye Guo, Lirong Deng +3
A residual deep reinforcement learning (RDRL) approach is proposed by integrating DRL with model-based optimization for inverter-based volt-var control in active distribution netwo…
Dynamic Operating Envelopes Embedded Peer-to-Peer-to-Grid Energy Trading
Zhisen Jiang, Ye Guo, Hongbin Sun +1
A novel decentralized peer-to-peer-to-grid (P2P2G) trading mechanism considering distribution network integrity is proposed. In order to direct prosumers' peer-to-peer (P2P) tradin…
An Adaptive Approach for Probabilistic Wind Power Forecasting Based on Meta-Learning
Zichao Meng, Ye Guo, Hongbin Sun
This paper studies an adaptive approach for probabilistic wind power forecasting (WPF) including offline and online learning procedures. In the offline learning stage, a base forec…
Multi-Interval Rolling-Window Joint Dispatch and Pricing of Energy and Reserve under Uncertainty
Jiantao Shi, Ye Guo, Wenchuan Wu +1
In this paper, the intra-day multi-interval rolling-window joint dispatch and pricing of energy and reserve is studied under increasing volatile and uncertain renewable generations…
Encoding Carbon Emission Flow in Energy Management: A Compact Constraint Learning Approach
Linwei Sang, Yinliang Xu, Hongbin Sun
Decarbonizing the energy supply is essential and urgent to mitigate the increasingly visible climate change. Its basis is identifying emission responsibility during power allocatio…
Conservative Sparse Neural Network Embedded Frequency-Constrained Unit Commitment With Distributed Energy Resources
Linwei Sang, Yinliang Xu, Zhongkai Yi +3
The increasing penetration of distributed energy resources (DERs) will decrease the rotational inertia of the power system and further degrade the system frequency stability. To ad…
On Degeneracy Issues in Multi-parametric Programming and Critical Region Exploration based Distributed Optimization in Smart Grid Operations
Haitian Liu, Ye Guo, Hao Liu
Improving renewable energy resource utilization efficiency is crucial to reducing carbon emissions, and multi-parametric programming has provided a systematic perspective in conduc…
Appendix for Nonparametric Multivariate Probability Density Forecast in Smart Grids With Deep Learning
Zichao Meng, Ye Guo, Wenjun Tang +1
This paper proposes a nonparametric multivariate density forecast model based on deep learning. It not only offers the whole marginal distribution of each random variable in foreca…
Reducing Action Space: Reference-Model-Assisted Deep Reinforcement Learning for Inverter-based Volt-Var Control
Qiong Liu, Ye Guo, Lirong Deng +3
Reference-model-assisted deep reinforcement learning (DRL) for inverter-based Volt-Var Control (IB-VVC) in active distribution networks is proposed. We investigate that a large act…
Smart Meters Integration in Distribution System State Estimation with Collaborative Filtering and Deep Gaussian Process
Yifei Xu, Ye Guo, Wenjun Tang +3
The problem of state estimations for electric distribution system is considered. A collaborative filtering approach is proposed in this paper to integrate the slow time-scale smart…
Reducing Learning Difficulties: One-Step Two-Critic Deep Reinforcement Learning for Inverter-based Volt-Var Control
Qiong Liu, Ye Guo, Lirong Deng +4
A one-step two-critic deep reinforcement learning (OSTC-DRL) approach for inverter-based volt-var control (IB-VVC) in active distribution networks is proposed in this paper. Firstl…
A Scenario-oriented Approach for Energy-Reserve Joint Procurement and Pricing
Jiantao Shi, Ye Guo, Lang Tong +2
We propose a scenario-oriented approach for energy-reserve joint procurement and pricing for electricity market. In this model, without the empirical reserve requirements, reserve…