Power systems optimization under uncertainty: A review of methods and applications
Electric power systems and the companies and customers that interact with them are
experiencing increasing levels of uncertainty due to factors such as renewable energy …
experiencing increasing levels of uncertainty due to factors such as renewable energy …
The citylearn challenge 2022: Overview, results, and lessons learned
The shift to renewable power sources and building electrification to decarbonize existing
and emerging building stock present unique challenges for the power grid. Building loads …
and emerging building stock present unique challenges for the power grid. Building loads …
Unsupervised optimal power flow using graph neural networks
Optimal power flow is a critical optimization problem that allocates power to the generators
in order to satisfy the demand at a minimum cost. This is a non-convex problem shown to be …
in order to satisfy the demand at a minimum cost. This is a non-convex problem shown to be …
Self-supervised learning for large-scale preventive security constrained DC optimal power flow
S Park, P Van Hentenryck - IEEE Transactions on Power …, 2024 - ieeexplore.ieee.org
Security-Constrained Optimal Power Flow (SCOPF) plays a crucial role in power grid
stability but becomes increasingly complex as systems grow. This paper introduces Primal …
stability but becomes increasingly complex as systems grow. This paper introduces Primal …
Two efficient logarithmic formulations to solve nonconvex economic dispatch
H Sharifzadeh - Electric Power Systems Research, 2024 - Elsevier
To solve economic dispatch (ED) with nonconvex nonlinear generation cost functions, this
paper adopts a global optimization technique where piecewise linear approximation (PLA) …
paper adopts a global optimization technique where piecewise linear approximation (PLA) …
[HTML][HTML] Multi-level optimization strategies for large-scale nonlinear process systems
LT Biegler - Computers & Chemical Engineering, 2024 - Elsevier
With growing needs to develop and improve climate-friendly processes, optimization
strategies are essential at all levels of decision-making in chemical and energy processes …
strategies are essential at all levels of decision-making in chemical and energy processes …
Optimization with Neural Network Feasibility Surrogates: Formulations and Application to Security-Constrained Optimal Power Flow
In many areas of constrained optimization, representing all possible constraints that give rise
to an accurate feasible region can be difficult and computationally prohibitive for online use …
to an accurate feasible region can be difficult and computationally prohibitive for online use …
[HTML][HTML] Constraint-driven deep learning for nk security constrained optimal power flow
The transition to green energy is reshaping the energy landscape, marked by increased
integration of renewables, distributed resources, and the electrification of other energy …
integration of renewables, distributed resources, and the electrification of other energy …
Considerations and design goals for unbalanced optimal power flow benchmarks
Distribution network constrained mathematical optimization is key technology to enable
advanced distribution network management. In recent years, a growing amount of articles on …
advanced distribution network management. In recent years, a growing amount of articles on …
Large-Scale Grid Optimization: the Workhorse of Future Grid Computations
Abstract Purpose of Review The computation methods for modeling, controlling, and
optimizing the transforming grid are evolving rapidly. We review and systemize knowledge …
optimizing the transforming grid are evolving rapidly. We review and systemize knowledge …