825 citations · 1.2k across the 22 of their papers we have counts for
9 papers · 1 filter
A Projection-Based Approach for Distributed Energy Resources Aggregation
Yiran Wang, Haiwang Zhong, Guangchun Ruan
Aggregating distributed energy resources (DERs) is of great significance to improve the overall operational efficiency of smart grid. The aggregation model needs to consider variou…
Life cycle economic viability analysis of battery storage in electricity market
Yinguo Yang, Yiling Ye, Zhuoxiao Cheng +4
Battery storage is essential to enhance the flexibility and reliability of electric power systems by providing auxiliary services and load shifting. Storage owners typically gains…
Look-Ahead AC Optimal Power Flow: A Model-Informed Reinforcement Learning Approach
Xinyue Wang, Haiwang Zhong, Guanglun Zhang +3
With the increasing proportion of renewable energy in the generation side, it becomes more difficult to accurately predict the power generation and adapt to the large deviations be…
Low-Carbon Economic Dispatch of Bulk Power Systems Using Nash Bargaining Game
Xuyang Li, Guangchun Ruan, Haiwang Zhong
Decarbonization of power systems plays a crucial role in achieving carbon neutral goals across the globe, but there exists a sharp contradiction between the emission reduction and…
Transmission Congestion Management with Generalized Generation Shift Distribution Factors
Shutong Pu, Guangchun Ruan, Xinfei Yan +1
A major concern in modern power systems is that the popularity and fluctuating characteristics of renewable energy may cause more and more transmission congestion events. Tradition…
Improving Sample Efficiency of Deep Learning Models in Electricity Market
Guangchun Ruan, Jianxiao Wang, Haiwang Zhong +2
The superior performance of deep learning relies heavily on a large collection of sample data, but the data insufficiency problem turns out to be relatively common in global electr…
Evaluation of Look-ahead Economic Dispatch Using Reinforcement Learning
Zekuan Yu, Guangchun Ruan, Xinyue Wang +3
Modern power systems are experiencing a variety of challenges driven by renewable energy, which calls for developing novel dispatch methods such as reinforcement learning (RL). Eva…
Open-Access Data and Toolbox for Tracking COVID-19 Impact on Power Systems
Guangchun Ruan, Zekuan Yu, Shutong Pu +5
Intervention policies against COVID-19 have caused large-scale disruptions globally, and led to a series of pattern changes in the power system operation. Analyzing these pandemic-…
Review of Learning-Assisted Power System Optimization
Guangchun Ruan, Haiwang Zhong, Guanglun Zhang +3
With dramatic breakthroughs in recent years, machine learning is showing great potential to upgrade the toolbox for power system optimization. Understanding the strength and limita…