A Stability-constrained Optimization Framework for Lur'e Systems with Applications in Power Grids
Qifeng Li, Qiushi Wang, and Konstantin Turitsyn

TL;DR
This paper introduces a stability-constrained optimization framework for Lur'e systems, particularly applied to power grids, enabling efficient and scalable transient stability-constrained optimal power flow solutions.
Contribution
It proposes a novel approach to incorporate stability certificates into optimization for large-scale Lur'e systems without discretizing differential equations.
Findings
Successfully applied to IEEE 118-Bus system
Provides a scalable TSCOPF framework
Ensures stability with reduced computational complexity
Abstract
For many nonlinear control systems, the chosen equilibrium determines both the steady-state efficiency and the dynamic performance. This paper addresses the issue of obtaining an optimal equilibrium in terms of some steady-state operation criteria for a Lur'e-type system and such an equilibrium can also guarantee a sufficiently large stability region in the dynamic domain such that the system can tolerate some given disturbance. For this purpose, a set of computationally tractable algebraic constraints, which can properly represent the stability certificate under the optimization framework, are proposed. The existing methods formulate the dynamic performance under the optimization framework by discretizing the differential-algebraic equations, which are computationally intractable for large-scale Lur'e systems like power grids. Dissimilarly, the introduced approach first constructs the…
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Taxonomy
TopicsPower System Optimization and Stability · Optimal Power Flow Distribution · Numerical methods for differential equations
