A set‐theoretic model predictive control approach for transient stability in smart grid. Issue 5 (7th January 2020)

• Record Type: Journal Article
• Authors: Bagherzadeh, Maryam; Lucia, Walter
• Is Part Of: IET control theory & applications. Volume 14:Issue 5(2020)
• Page Start: 700
• Page End: 707
• Publication Date: 2020-01-07
• Subjects: optimisation -- power system transient stability -- power distribution reliability -- concave programming -- convex programming -- nonlinear programming -- power generation dispatch -- set theory -- predictive control -- power system control -- smart power grids; set‐theoretic model predictive control approach -- smart grid -- transient stability control problem -- operative scenario -- impulsive perturbation -- initial perturbation -- uncertainties -- model predictive control idea -- set‐theoretic MPC -- emergency controller -- considered scenario -- worst‐case time -- simple convex optimisation problem -- computationally affordable convex optimisation problem; Control theory -- Periodicals; Automatic control -- Periodicals; 629.8312
• DOI: 10.1049/iet-cta.2019.0689
• Languages: English
• ISSNs: 1751-8644

Abstract

Abstract : In this study, the authors deal with the transient stability control problem in smart grids. They consider an operative scenario where a physical fault or a cyber‐attack produces an impulsive perturbation in the state of the system, and a controller must be designed to robustly recover, in a finite‐time, transient stability despite initial perturbation and uncertainties. The authors propose a solution that is based on a low‐demanding model predictive control (MPC) idea that is known as set‐theoretic MPC. They show that such a controller can be used as an emergency controller to deal with the considered scenario. A peculiar capability of the proposed solution is that the worst‐case time to transient stability can be apriori established. Moreover, most of the required computations are moved into an off‐line phase leaving into the on‐line phase a simple and computationally affordable convex optimisation problem. Finally, the authors have conducted an extensive simulation campaign to testify the validity of the proposed solution experimentally and to investigate its performance when contrasted with a competitor scheme.