With the development of smart grid, energy management becomes critical for reliable and
efficient operation of power systems. In this paper, we develop a chance-constrained energy …

The uncertainty associated with renewable energy sources introduces significant challenges
in optimal power flow (OPF) analysis. A variety of new approaches have been proposed that …

We propose a data-based method to solve a multi-stage stochastic optimal power flow (OPF)
problem based on limited information about forecast error distributions. The framework …

This paper investigates how the choice of stochastic approaches and distribution
assumptions impacts strategic investment decisions in energy planning problems. We …

In this paper, we propose a risk-based data-driven distributionally robust approach to
investigating the optimal power flow with dynamic line rating. The risk terms, including …

Optimization problems face random constraint violations when uncertainty arises in
constraint parameters. Effective ways of controlling such violations include risk constraints …

Recent research on optimal power flow (OPF) in networks with renewable power involves
optimizing both first and second stage variables that adjust the decision once the uncertainty …

This is the second part of a two-part paper on data-based distributionally robust stochastic
optimal power flow. The general problem formulation and methodology have been …

As more renewables are integrated into the power system, capacity expansion planners
need more advanced long-term decision-making tools to properly model short-term …

The day-ahead management schedules of hybrid energy hubs are intricate and usually
exposed to various uncertainties with the penetration of renewable sources and different …