Iterative learning control in prosumer-based microgrids with hierarchical control

Publikation: Beitrag in FachzeitschriftKonferenzaufsatz in FachzeitschriftForschungPeer-Review

Autorschaft

  • Lia Strenge
  • Xiaohan Jing
  • Ruth Boersma
  • Paul Schultz
  • Frank Hellmann
  • Jürgen Kurths
  • Jörg Raisch
  • Thomas Seel

Externe Organisationen

  • Technische Universität Berlin
  • Potsdam-Institut für Klimafolgenforschung (PIK)
Forschungs-netzwerk anzeigen

Details

OriginalspracheEnglisch
Seiten (von - bis)12251-12258
Seitenumfang8
FachzeitschriftIFAC-PapersOnLine
Jahrgang53
Ausgabenummer2
PublikationsstatusVeröffentlicht - 2020
Extern publiziertJa
Veranstaltung21st IFAC World Congress 2020 - Berlin, Deutschland
Dauer: 12 Juli 202017 Juli 2020

Abstract

Power systems are subject to fundamental changes due to the increasing infeed of renewable energy sources. Taking the accompanying decentralization of power generation into account, the concept of prosumer-based microgrids gives the opportunity to rethink structuring and operation of power systems from scratch. In a prosumer-based microgrid, each power grid node can feed energy into the grid and draw energy from the grid. The concept allows for spatial aggregation such that also an interaction between microgrids can be represented as a prosumer-based microgrid. The contribution of this work is threefold: (i) we propose a decentralized hierarchical control approach in a network including different time scales, (ii) we use iterative learning control to compensate periodic demand patterns and save lower-layer control energy and (iii) we assure asymptotic stability and monotonic convergence in the iteration domain for the linearized dynamics and validate the performance by simulating the nonlinear dynamics.

ASJC Scopus Sachgebiete

Ziele für nachhaltige Entwicklung

Zitieren

Iterative learning control in prosumer-based microgrids with hierarchical control. / Strenge, Lia; Jing, Xiaohan; Boersma, Ruth et al.
in: IFAC-PapersOnLine, Jahrgang 53, Nr. 2, 2020, S. 12251-12258.

Publikation: Beitrag in FachzeitschriftKonferenzaufsatz in FachzeitschriftForschungPeer-Review

Strenge, L, Jing, X, Boersma, R, Schultz, P, Hellmann, F, Kurths, J, Raisch, J & Seel, T 2020, 'Iterative learning control in prosumer-based microgrids with hierarchical control', IFAC-PapersOnLine, Jg. 53, Nr. 2, S. 12251-12258. https://doi.org/10.1016/j.ifacol.2020.12.1145
Strenge, L., Jing, X., Boersma, R., Schultz, P., Hellmann, F., Kurths, J., Raisch, J., & Seel, T. (2020). Iterative learning control in prosumer-based microgrids with hierarchical control. IFAC-PapersOnLine, 53(2), 12251-12258. https://doi.org/10.1016/j.ifacol.2020.12.1145
Strenge L, Jing X, Boersma R, Schultz P, Hellmann F, Kurths J et al. Iterative learning control in prosumer-based microgrids with hierarchical control. IFAC-PapersOnLine. 2020;53(2):12251-12258. doi: 10.1016/j.ifacol.2020.12.1145
Strenge, Lia ; Jing, Xiaohan ; Boersma, Ruth et al. / Iterative learning control in prosumer-based microgrids with hierarchical control. in: IFAC-PapersOnLine. 2020 ; Jahrgang 53, Nr. 2. S. 12251-12258.
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abstract = "Power systems are subject to fundamental changes due to the increasing infeed of renewable energy sources. Taking the accompanying decentralization of power generation into account, the concept of prosumer-based microgrids gives the opportunity to rethink structuring and operation of power systems from scratch. In a prosumer-based microgrid, each power grid node can feed energy into the grid and draw energy from the grid. The concept allows for spatial aggregation such that also an interaction between microgrids can be represented as a prosumer-based microgrid. The contribution of this work is threefold: (i) we propose a decentralized hierarchical control approach in a network including different time scales, (ii) we use iterative learning control to compensate periodic demand patterns and save lower-layer control energy and (iii) we assure asymptotic stability and monotonic convergence in the iteration domain for the linearized dynamics and validate the performance by simulating the nonlinear dynamics.",
keywords = "Control of distributed systems, Control of large-scale systems, Control of power systems, Convergence analysis, Iterative learning control, Networks, Nonlinear systems",
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note = "Funding Information: This work was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) - KU 837/39-1 / RA 516/13-1. L.S. thanks Chris Macnab and Philipp Schulze for the constructive discussions and Jan Meyer-Dulheuer for helping to focus.; 21st IFAC World Congress 2020 ; Conference date: 12-07-2020 Through 17-07-2020",
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Download

TY - JOUR

T1 - Iterative learning control in prosumer-based microgrids with hierarchical control

AU - Strenge, Lia

AU - Jing, Xiaohan

AU - Boersma, Ruth

AU - Schultz, Paul

AU - Hellmann, Frank

AU - Kurths, Jürgen

AU - Raisch, Jörg

AU - Seel, Thomas

N1 - Funding Information: This work was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) - KU 837/39-1 / RA 516/13-1. L.S. thanks Chris Macnab and Philipp Schulze for the constructive discussions and Jan Meyer-Dulheuer for helping to focus.

PY - 2020

Y1 - 2020

N2 - Power systems are subject to fundamental changes due to the increasing infeed of renewable energy sources. Taking the accompanying decentralization of power generation into account, the concept of prosumer-based microgrids gives the opportunity to rethink structuring and operation of power systems from scratch. In a prosumer-based microgrid, each power grid node can feed energy into the grid and draw energy from the grid. The concept allows for spatial aggregation such that also an interaction between microgrids can be represented as a prosumer-based microgrid. The contribution of this work is threefold: (i) we propose a decentralized hierarchical control approach in a network including different time scales, (ii) we use iterative learning control to compensate periodic demand patterns and save lower-layer control energy and (iii) we assure asymptotic stability and monotonic convergence in the iteration domain for the linearized dynamics and validate the performance by simulating the nonlinear dynamics.

AB - Power systems are subject to fundamental changes due to the increasing infeed of renewable energy sources. Taking the accompanying decentralization of power generation into account, the concept of prosumer-based microgrids gives the opportunity to rethink structuring and operation of power systems from scratch. In a prosumer-based microgrid, each power grid node can feed energy into the grid and draw energy from the grid. The concept allows for spatial aggregation such that also an interaction between microgrids can be represented as a prosumer-based microgrid. The contribution of this work is threefold: (i) we propose a decentralized hierarchical control approach in a network including different time scales, (ii) we use iterative learning control to compensate periodic demand patterns and save lower-layer control energy and (iii) we assure asymptotic stability and monotonic convergence in the iteration domain for the linearized dynamics and validate the performance by simulating the nonlinear dynamics.

KW - Control of distributed systems

KW - Control of large-scale systems

KW - Control of power systems

KW - Convergence analysis

KW - Iterative learning control

KW - Networks

KW - Nonlinear systems

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U2 - 10.1016/j.ifacol.2020.12.1145

DO - 10.1016/j.ifacol.2020.12.1145

M3 - Conference article

AN - SCOPUS:85082768282

VL - 53

SP - 12251

EP - 12258

JO - IFAC-PapersOnLine

JF - IFAC-PapersOnLine

SN - 2405-8963

IS - 2

T2 - 21st IFAC World Congress 2020

Y2 - 12 July 2020 through 17 July 2020

ER -

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