Abstract Purpose of Review The computation methods for modeling, controlling, and
optimizing the transforming grid are evolving rapidly. We review and systemize knowledge …

Security-constrained optimal power flow (SCOPF) aims to achieve an economical operation
while considering the security issues during contingencies. Data-driven security assessment …

Successful machine learning involves a complete pipeline of data, model, and downstream
applications. Instead of treating them separately, there has been a prominent increase of …

The optimal power flow methods for AC-DC systems containing VSC-HVDC generally only
consider the economy during normal operation, overlooking the distribution of line …

Electrical power scheduling typically occurs in two stages: day-ahead (DA) planning and
real-time (RT) balancing. In DA scheduling, generation and reserve capacities are set for the …

Climate change is one of the most pressing issues of our time, requiring the rapid
mobilization of many tools and approaches from across society. Machine learning has been …

This paper presents a comprehensive stochastic optimization model that seamlessly
integrates aggregate electric vehicle (EV) charging demand response with power grid …