Data-driven MPC of descriptor systems: A case study for power networks

被引：6

作者：

Schmitz, Philipp ^{[1
]}

Engelmann, Alexander ^{[2
]}

Faulwasser, Timm ^{[2
]}

Worthmann, Karl ^{[1
]}

机构：

[1] Tech Univ Ilmenau, Inst Math, Optimizat Based Control, Ilmenau, Germany

[2] TU Dortmund Univ, Inst Energy Syst Energy Efficiency & Energy Econ, Dortmund, Germany

来源：

IFAC PAPERSONLINE | 2022年 / 55卷 / 30期

关键词：

Data-driven control; descriptor systems; MPC; Willems' fundamental lemma; optimal control; power-swing equations; power systems; AUTOMATIC-GENERATION CONTROL; FREQUENCY CONTROL; STABILITY; MODEL; MICROGRIDS;

D O I：

10.1016/j.ifacol.2022.11.079

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Recently, data-driven predictive control of linear systems has received wide-spread research attention. It hinges on the fundamental lemma by Willems et al. In a previous paper, we have shown how this framework can be applied to predictive control of linear time-invariant descriptor systems. In the present paper, we present a case study wherein we apply data-driven predictive control to a discrete-time descriptor model obtained by discretization of the power-swing equations for a nine-bus system. Our results show the efficacy of the proposed control scheme and they underpin the prospect of the data-driven framework for control of descriptor systems. Copyright (C) 2022 The Authors.

引用

页码：359 / 364

页数：6

共 50 条

[21] Data-Driven Incident Detection in Power Distribution Systems
Aguiar, Nayara
Gupta, Vijay
Trevizan, Rodrigo D.
Chalamala, Babu R.
Byrne, Raymond H.
2021 IEEE POWER & ENERGY SOCIETY GENERAL MEETING (PESGM), 2021,
[22] Linear MPC based on data-driven Artificial Neural Networks for large-scale nonlinear distributed parameter systems
Xie, Weiguo
Bonis, Ioannis
Theodoropoulos, Constantinos
22 EUROPEAN SYMPOSIUM ON COMPUTER AIDED PROCESS ENGINEERING, 2012, 30 : 1212 - 1216
[23] A Data-Driven Approach to Interactive Visualization of Power Systems
Zhu, Jun
Zhuang, Eric
Ivanov, Chavdar
Yao, Ziwen
IEEE TRANSACTIONS ON POWER SYSTEMS, 2011, 26 (04) : 2539 - 2546
[24] Stability in data-driven MPC: an inherent robustness perspective
Berberich, Julian
Koehler, Johannes
Mueller, Matthias A.
Allgower, Frank
2022 IEEE 61ST CONFERENCE ON DECISION AND CONTROL (CDC), 2022, : 1105 - 1110
[25] Offline Uncertainty Sampling in Data-driven Stochastic MPC
Teutsch, Johannes
Kerz, Sebastian
Brudigam, Tim
Wollherr, Dirk
Leibold, Marion
IFAC PAPERSONLINE, 2023, 56 (02): : 650 - 656
[26] Data-Driven MPC Scheme for Inertial Platform with Uncertain Systems Against External Vibrations
Zhao, Junhu
Yang, Qifan
Li, Huiping
ELECTRONICS, 2024, 13 (24):
[27] A Data-driven Performance Assessment Approach for MPC Systems under Multiple Operating Conditions
Xu, Yanting
Li, Ning
Li, Shaoyuan
2014 13TH INTERNATIONAL CONFERENCE ON CONTROL AUTOMATION ROBOTICS & VISION (ICARCV), 2014, : 919 - 924
[28] Distributed Data-Driven Power Iteration for Strongly Connected Networks
Gusrialdi, Azwirman
Qu, Zhihua
2021 EUROPEAN CONTROL CONFERENCE (ECC), 2021, : 87 - 92
[29] Data-driven flexibility prediction in low voltage power networks
Leiva, Javier
Aguado, Jose A.
Paredes, Angel
Arboleya, Pablo
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2020, 123
[30] Data-driven budget reductions: a case study
Novak, Denise D.
Paulos, Afeworki
Clair, Gloriana St.
BOTTOM LINE, 2011, 24 (01): : 24 - 34

← 1 2 3 4 5 →