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Toward economic NMPC for multistage AC optimal power flow
Author(s) -
Faulwasser Timm,
Engelmann Alexander
Publication year - 2019
Publication title -
optimal control applications and methods
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.458
H-Index - 44
eISSN - 1099-1514
pISSN - 0143-2087
DOI - 10.1002/oca.2487
Subject(s) - model predictive control , control theory (sociology) , economic dispatch , electric power system , mathematical optimization , power flow , computer science , generator (circuit theory) , power (physics) , nonlinear system , stability (learning theory) , blueprint , nonlinear model , control (management) , engineering , mathematics , mechanical engineering , physics , quantum mechanics , artificial intelligence , machine learning
Summary Recently, there has been a considerable progress on the analysis of stability and performance properties of so‐called economic nonlinear model predictive control ( nmpc ) schemes, ie, schemes employing stage costs that are not directly related to distance measures of precomputed setpoints. At the same time, with respect to the energy transition, the use of nmpc schemes is proposed and investigated in a plethora of papers in different contexts. For example, receding‐horizon approaches to generator dispatch problems, which is also known as multistage optimal power flow ( opf ) in power systems, naturally lead to economic nmpc schemes based on nonconvex discrete‐time optimal control problems ( ocp ). This paper investigates the transfer of analysis results available for general economic nmpc schemes to receding‐horizon multistage opf . We propose a blueprint formulation of multistage opf including ac power flow equations. Based on this formulation, we present results on the dissipativity and recursive feasibility properties of the underlying ocp . Finally, we draw upon simulations using a 5‐bus system and a 118‐bus system to illustrate our findings.