Search Results for author: Guangchun Ruan

Found 9 papers, 3 papers with code

Low-Carbon Economic Dispatch of Bulk Power Systems Using Nash Bargaining Game

no code implementations30 Jan 2023 Xuyang Li, Guangchun Ruan, Haiwang Zhong

Because the Nash bargaining solution satisfies Pareto effectiveness, we analyze the computational complexity of Pareto frontiers with parametric linear programming and interpret the inefficiency of the method.

Transmission Congestion Management with Generalized Generation Shift Distribution Factors

no code implementations24 Dec 2022 Shutong Pu, Guangchun Ruan, Xinfei Yan, Haiwang Zhong

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.

Management

Improving Sample Efficiency of Deep Learning Models in Electricity Market

no code implementations11 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.

Data Augmentation

Evaluation of Look-ahead Economic Dispatch Using Reinforcement Learning

no code implementations21 Sep 2022 Zekuan Yu, Guangchun Ruan, Xinyue Wang, Guanglun Zhang, Yiliu He, Haiwang Zhong

In this paper, we propose an evaluation approach to analyze the performance of RL agents in a look-ahead economic dispatch scheme.

reinforcement-learning reinforcement Learning

Open-Access Data and Toolbox for Tracking COVID-19 Impact on Power Systems

1 code implementation10 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.

Estimating Demand Flexibility Using Siamese LSTM Neural Networks

no code implementations3 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.

Short-Term Electricity Price Forecasting based on Graph Convolution Network and Attention Mechanism

no code implementations26 Jul 2021 Yuyun Yang, Zhenfei Tan, Haitao Yang, Guangchun Ruan, Haiwang Zhong

In electricity markets, locational marginal price (LMP) forecasting is particularly important for market participants in making reasonable bidding strategies, managing potential trading risks, and supporting efficient system planning and operation.

Review of Learning-Assisted Power System Optimization

1 code implementation1 Jul 2020 Guangchun Ruan, Haiwang Zhong, Guanglun Zhang, Yiliu He, Xuan Wang, Tianjiao Pu

With dramatic breakthroughs in recent years, machine learning is showing great potential to upgrade the toolbox for power system optimization.

Systems and Control Systems and Control Optimization and Control

Tracking and Analyzing the Short-Run Impact of COVID-19 on the U.S. Electricity Sector

1 code implementation11 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

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