most citedA Machine Learning Framework to Deconstruct the Primary Drivers for Electricity Market Price Events

1 citations · 2 across the 5 of their papers we have counts for

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5 papers

eess.SP20241 cited

Hy-DAT: A Tool to Address Hydropower Modeling Gaps Using Interdependency, Efficiency Curves, and Unit Dispatch Models

Dewei Wang, Bhaskar Mitra, Sameer Nekkalapu +5

As the power system continues to be flooded with intermittent resources, it becomes more important to accurately assess the role of hydro and its impact on the power grid. While hy…

eess.SY2024

Power System Resource Expansion Planning

Sohom Datta

Power System Resource Planning is the recurrent process of studying and determining what facilities and procedures should be provided to satisfy and promote appropriate future dema…

eess.SY2023

Gaps in Representations of Hydropower Generation in Steady-State and Dynamic Models

Bhaskar Mitra, Sohom Datta, Slaven Kincic +2

In the evolving power system, where new renewable resources continually displace conventional generation, conventional hydropower resources can be an important asset that helps to…

eess.SY2023

Toward Intelligent Emergency Control for Large-scale Power Systems: Convergence of Learning, Physics, Computing and Control

Qiuhua Huang, Renke Huang, Tianzhixi Yin +13

This paper has delved into the pressing need for intelligent emergency control in large-scale power systems, which are experiencing significant transformations and are operating cl…

cs.LG20231 cited

A Machine Learning Framework to Deconstruct the Primary Drivers for Electricity Market Price Events

Milan Jain, Xueqing Sun, Sohom Datta +1

Power grids are moving towards 100% renewable energy source bulk power grids, and the overall dynamics of power system operations and electricity markets are changing. The electric…