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.
Intervention policies against COVID-19 have caused large-scale disruptions globally, and led to a series of pattern changes in the power system operation.
There is an opportunity in modern power systems to explore the demand flexibility by incentivizing consumers with dynamic prices.
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
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.
Results identify how the bounds decrease with additional power grid physical knowledge or more training data.
A new battery life model with scrapping parameters is then derived using this criterion.