[HTML][HTML] Fast procedure to compute empirical and Bernstein copulas

VM Hernández-Maldonado, A Erdely… - Applied Mathematics …, 2024 - Elsevier
In this work, a novel technique for efficient computation of bivariate empirical copulas and,
by extension, non-parametrical copulas. The algorithm addresses discrete and finite …

Computationally Enhanced Approach for Chance-Constrained OPF Considering Voltage Stability

Y Wu, Z Wu, Y Xu, H Long, W Gu… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
The effective management of stochastic characteristics of renewable power generations is
vital for ensuring the stable and secure operation of power systems. This paper addresses …

Stochastic Day-Ahead Scheduling of Distributed Energy Resources: A Meta Modelling Approach

K Chauhan, J Moirangthem, S Ly… - IEEE Journal of …, 2023 - ieeexplore.ieee.org
Integration of distributed energy resources (DERs) presents several challenges for grid
operators, including managing the intermittent output of renewable energy sources …

A novel quantile Lite-PCE for probabilistic risk assessment of power system cascading outage for N-1-1 contingency analysis

S Ly, K Chauhan, GH Beng… - 2023 IEEE Power & …, 2023 - ieeexplore.ieee.org
In recent times, the severity of cascading outages leading to power system blackouts has
increased due to unexpected extreme weather conditions and cyber-attacks. In this regard, a …

Efficient Probabilistic Optimal Power Flow Assessment Using an Adaptive Stochastic Spectral Embedding Surrogate Model

X Wang, J Liu, X Wang - arXiv preprint arXiv:2401.10498, 2024 - arxiv.org
This paper presents an adaptive stochastic spectral embedding (ASSE) method to solve the
probabilistic AC optimal power flow (AC-OPF), a critical aspect of power system operation …

GraphSAGE-Based Probabilistic Optimal Power Flow in Distribution System

Y Ding, H Wu, Z Xu, H Yang - 2023 International Conference on …, 2023 - ieeexplore.ieee.org
The large-scale penetration of wind and photovoltaic (PV) power generation brings
significant uncertainties to the distribution system power flows. In this paper, a data-driven …