This study presents a comprehensive survey on the reliability evaluation of the electrical
network system. The impacts of integration of new and renewable energy sources (electric …

Penetrations of renewable energy sources, particularly solar energy, are increasing globally
to reduce carbon emissions. Due to the intermittency of solar power, battery energy storage …

Power systems employ measures of reliability indices to indicate the effectiveness a power
system to perform its basic function of supplying electrical energy to its consumers. The …

Increasing the penetration of wind energy in power networks is one of the ways to reduce
industrial carbon footprint. However, the intermittency of wind speed inhibits the widespread …

Battery energy storage systems (BESS), demand response (DR) and the dynamic thermal
rating (DTR) system have increasingly played important roles in power grids worldwide. In …

This paper proposes a machine learning-based approach in conjunction with Monte Carlo
simulation (MCS) to improve the computation efficiency of composite power system reliability …

This paper presents a transmission line failure model that is enhanced with the dynamic
thermal rating (DTR) system. The failure model consists of two parts. The first part is the …

This paper proposes a new approach to evaluate loss of load indices in composite
generation and transmission systems. The main idea is to combine a Cross-Entropy (CE) …

This paper presents a new approach for reliability evaluation of composite power systems by
combining Monte Carlo simulation and multi label k-nearest neighbor (MLKNN) algorithm …

Supervised machine learning using neural networks is applied to denoising images
rendered by MC path tracing. Specialization of neural networks may be achieved by using a …