Systemsteuerung unter Verwendung eines Algorithmischen Rahmens zur Lösung Linearer und Nichtlinearer Optimierungsprobleme

Details

Veröffentlichungs-Nr.

EP4625211

Aktenzeichen

EP24167667

Anmeldetag

28. März 2024

Veröffentlichung

1. Oktober 2025

Rechtsraum

EP

IPC

G06F17/11H02J3/00

Abstract

Traditional algorithms for solving constrained optimization problems are complicated to implement, difficult to interpret, and require significant computational resources. Disclosed embodiments convert constrained optimization problems into parametric optimization problems, in which at least a subset of the constraints are converted into parametric quadratic penalty (PQP) terms that each depends on a translational parameter. The parametric optimization problem may be used for optimization in a power system (e.g., for optimal power flow, economic dispatch, etc.). When solving the parametric optimization problem, the translational parameters are updated to ensure convergence. The parametric optimization problem can be solved with reduced computational expense, using only a linear equation solver to solve a sequence of primal variables only, thereby reducing computational complexity and expense. In addition, the disclosed embodiments provide a means to incorporate constraints into machine-learning algorithms. The disclosed algorithmic framework also provides interpretability and insights for analysis.

Anmelder

Firma

Hitachi Energy Ltd

Land

🇨🇭 Schweiz

Fachgebiete