Details
| Original language | English |
|---|---|
| Pages (from-to) | 12251-12258 |
| Number of pages | 8 |
| Journal | IFAC-PapersOnLine |
| Volume | 53 |
| Issue number | 2 |
| Publication status | Published - 2020 |
| Externally published | Yes |
| Event | 21st IFAC World Congress 2020 - Berlin, Germany Duration: 12 Jul 2020 → 17 Jul 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.
Keywords
- Control of distributed systems, Control of large-scale systems, Control of power systems, Convergence analysis, Iterative learning control, Networks, Nonlinear systems
ASJC Scopus subject areas
- Engineering(all)
- Control and Systems Engineering
Sustainable Development Goals
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In: IFAC-PapersOnLine, Vol. 53, No. 2, 2020, p. 12251-12258.
Research output: Contribution to journal › Conference article › Research › peer review
}
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
UR - http://www.scopus.com/inward/record.url?scp=85082768282&partnerID=8YFLogxK
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 -