Conic optimization has recently emerged as a powerful tool for designing tractable and
guaranteed algorithms for power system operation. On the one hand, tractability is crucial …

Many real-life optimization problems frequently contain one or more constraints or objectives
for which there are no explicit formulae. If however data on feasible and/or infeasible states …

We develop DeepOPF as a Deep Neural Network (DNN) approach for solving security-
constrained direct current optimal power flow (SC-DCOPF) problems, which are critical for …

To cope with increasing uncertainty from renewable generation and flexible load, grid
operators need to solve alternative current optimal power flow (AC-OPF) problems more …

Solving power flow (PF) equations is the basis of power flow analysis, which is important in
determining the best operation of existing systems, performing security analysis, etc …

The data-driven method with strong approximation capabilities and high computational
efficiency provides a promising tool for optimal power flow (OPF) calculation with stochastic …

We establish a broad methodological foundation for mixed-integer optimization with learned
constraints. We propose an end-to-end pipeline for data-driven decision making in which …

This paper presents an adaptive group search optimization (AGSO) algorithm for solving
optimal power flow (OPF) problem. In this study, different aspects of the OPF problem are …

The interconnection and coupling of integrated energy systems (IES) including electricity
system, natural gas system and district heating system become increasingly tight. It brings …

The security-constrained optimal power flow (SCOPF) is fundamental in power systems and
connects the automatic primary response (APR) of synchronized generators with the short …