Machine learning assisted optimal power flow (OPF) aims to reduce the computational complexity of these non-linear and non-convex constrained optimization problems by consigning expensive (online) offline training. The majority work in this area typically employs fully connected neural networks (FCNN). However, recently convolutional (CNN) graph (GNN) have also been investigated, effort exploit...

The rapid uptake of natural gas-fired units in energy systems poses significant challenges coordinating the electricity and gas systems. Besides, uncertainty caused by integrated renewable such as wind power raises more requirements on robustness operation for system (IEGS). To address these challenges, this paper investigates distributed adjustable robust optimal flow (OPGF) model IEGS. Using ...

Optimal power flow (OPF) problems are mathematical programs to determine how distribute over networks subject and operational constraints. In this article, we treat an OPF problem as operator that maps user demand generated power, allow the parameters take values in some admissible set. We formalize theoretic approach, define characterize restricted parameter sets under which mapping has a sing...

Managing uncertainty and variability in power injections has become a major concern for system operators due to increasing levels of fluctuating renewable energy connected the grid. This work addresses this via joint chance-constrained formulation DC optimal flow (OPF) problem, which satisfies all constraints jointly with pre-determined probability. The few existing approaches solving OPF probl...

This paper examines the storage application and its optimal placement for the social cost and transmission congestion relief of wind integration. Probability density functions (PDFs) are used to characterize the uncertainties of wind speed and load. A probabilistic optimal power flow (POPF) is developed using two-point estimation which incorporates the storage system either as a variable load o...

This paper proposes a quasi-optimal power flow (OPF) algorithm for flexible DC traction systems (TPSs). Near-optimal OPF solutions can be solved with high computational efficiency by quasi-OPF. Unlike conventional algorithms, quasi-OPF does not utilize mathematical optimization algorithms but adopts new methodology. First, we adopt modeling method and successfully reveal the physical meaning of...