research
∙
10/11/2022
Improving Sample Efficiency of Deep Learning Models in Electricity Market
The superior performance of deep learning relies heavily on a large coll...
share
research
∙
09/03/2021
Estimating Demand Flexibility Using Siamese LSTM Neural Networks
There is an opportunity in modern power systems to explore the demand fl...
research
∙
06/01/2021
Topology and Admittance Estimation: Precision Limits and Algorithms
Distribution grid topology and admittance information are essential for ...
research
∙
05/11/2020
A Cross-Domain Approach to Analyzing the Short-Run Impact of COVID-19 on the U.S. Electricity Sector
The novel coronavirus disease (COVID-19) has rapidly spread around the g...
research
∙
05/11/2020
Tracking and Analyzing the Short-Run Impact of COVID-19 on the U.S. Electricity Sector
The novel coronavirus disease (COVID-19) has rapidly spread around the g...
research
∙
04/20/2020
Sparse Oblique Decision Tree for Power System Security Rules Extraction and Embedding
Increasing the penetration of variable generation has a substantial effe...
research
∙
10/30/2019
Bounding Data-driven Model Errors in Power Grid Analysis
Data-driven models analyze power grids under incomplete physical informa...
research
∙
09/25/2019
Probabilistic duck curve in high PV penetration power system: Concept, modeling, and empirical analysis in China
The high penetration of photovoltaic (PV) is reshaping the electricity n...
research
∙
03/18/2018
Combining Probabilistic Load Forecasts
Probabilistic load forecasts provide comprehensive information about fut...
research
∙
02/09/2018