Model-Based Optimal Feedback Control for Microgrids with Multi-Level Iterations

Robert Scholz (), Armin Nurkanovic (), Amer Mesanovic, Jürgen Gutekunst, Andreas Potschka, Hans Georg Bock and Ekaterina Kostina
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Robert Scholz: Heidelberg University
Armin Nurkanovic: Siemens AG
Amer Mesanovic: Siemens AG
Jürgen Gutekunst: Siemens AG
Andreas Potschka: Heidelberg University
Hans Georg Bock: Heidelberg University
Ekaterina Kostina: Heidelberg University

A chapter in Operations Research Proceedings 2019, 2020, pp 73-79 from Springer

Abstract: Abstract Conventional strategies for microgrid control are based on low level controllers in the individual components. They do not reflect the nonlinear behavior of a coupled system, which can lead to instabilities of the whole system. Nonlinear model predictive control (NMPC) can overcome this problem but the standard methods are too slow to guarantee sufficiently fast feedback rates. We apply Multi-Level Iterations to reduce the computational expenses to make NMPC real-time feasible for the efficient feedback control of microgrids.

Keywords: Nonlinear model predictive control; Optimal control; Power engineering; Microgrid (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:spr:oprchp:978-3-030-48439-2_9

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DOI: 10.1007/978-3-030-48439-2_9

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