57 citations · 71 across the 7 of their papers we have counts for
7 papers
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…
Carbon Monitor-Power: near-real-time monitoring of global power generation on hourly to daily scales
Biqing Zhu, Xuanren Song, Zhu Deng +13
We constructed a frequently updated, near-real-time global power generation dataset: Carbon Monitor-Power since January, 2016 at national levels with near-global coverage and hourl…
Short-Term Electricity Price Forecasting based on Graph Convolution Network and Attention Mechanism
Yuyun Yang, Zhenfei Tan, Haitao Yang +2
In electricity markets, locational marginal price (LMP) forecasting is particularly important for market participants in making reasonable bidding strategies, managing potential tr…
Quantitative Assessment of U.S. Bulk Power Systems and Market Operations during COVID-19
Guangchun Ruan, Jiahan Wu, Haiwang Zhong +2
Starting in early 2020, the novel coronavirus disease (COVID-19) severely affected the U.S., causing substantial changes in the operations of bulk power systems and electricity mar…
De-carbonization of global energy use during the COVID-19 pandemic
Zhu Liu, Biqing Zhu, Philippe Ciais +15
The COVID-19 pandemic has disrupted human activities, leading to unprecedented decreases in both global energy demand and GHG emissions. Yet a little known that there is also a low…