no code implementations • 4 Oct 2019 • Qingchun Hou, Yanghao Yu, Ershun Du, Hongjie He, Ning Zhang, Chongqing Kang, Guojing Liu, Huan Zhu
A new battery life model with scrapping parameters is then derived using this criterion.
no code implementations • 30 Oct 2019 • Yuxiao Liu, Bolun Xu, Audun Botterud, Ning Zhang, Chongqing Kang
Results identify how the bounds decrease with additional power grid physical knowledge or more training data.
no code implementations • 20 Apr 2020 • Qingchun Hou, Ning Zhang, Daniel S. Kirschen, Ershun Du, Yaohua Cheng, Chongqing Kang
Data-driven techniques provide a promising way to identify security rules that can be embedded in economic dispatch model to keep power system operating states secure.
1 code implementation • 11 May 2020 • Guangchun Ruan, Dongqi Wu, Xiangtian Zheng, S. Sivaranjani, Le Xie, Haiwang Zhong, Chongqing Kang
The novel coronavirus disease (COVID-19) has rapidly spread around the globe in 2020, with the U. S. becoming the epicenter of COVID-19 cases and deaths in late March.
Computers and Society
no code implementations • 3 Sep 2021 • Guangchun Ruan, Daniel S. Kirschen, Haiwang Zhong, Qing Xia, Chongqing Kang
There is an opportunity in modern power systems to explore the demand flexibility by incentivizing consumers with dynamic prices.
1 code implementation • 10 Dec 2021 • Guangchun Ruan, Zekuan Yu, Shutong Pu, Songtao Zhou, Haiwang Zhong, Le Xie, Qing Xia, Chongqing Kang
Intervention policies against COVID-19 have caused large-scale disruptions globally, and led to a series of pattern changes in the power system operation.
no code implementations • 11 Oct 2022 • Guangchun Ruan, Jianxiao Wang, Haiwang Zhong, Qing Xia, Chongqing Kang
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 electricity markets.
no code implementations • 9 Mar 2023 • Shaohuai Liu, Jinbo Liu, Weirui Ye, Nan Yang, Guanglun Zhang, Haiwang Zhong, Chongqing Kang, Qirong Jiang, Xuri Song, Fangchun Di, Yang Gao
The well-trained scheduling agent significantly reduces renewable curtailment and load shedding, which are issues arising from traditional scheduling's reliance on inaccurate day-ahead forecasts.