Iterative learning control in prosumer-based microgrids with hierarchical control

Strenge, Lia; Jing, Xiaohan; Boersma, Ruth; Schultz, Pamela N.; Hellmann, Frank; Kurths, Jürgen; Raisch, Jörg; Seel, Thomas

doi:10.1016/j.ifacol.2020.12.1145

Cited by 3 publications

(2 citation statements)

References 28 publications

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“…However, in autonomous microgrids, without the resources necessary to implement a market-based solution, the ILC itself is a viable way of choosing dispatch. We leave a detailed discussion of the design, as well as a proof of linearised asymptotic stability in the iteration domain of the ILC in such a scenario to a companion paper 50 .…”

Section: B Energy Managementmentioning

confidence: 99%

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A multiplex, multi-timescale model approach for economic and frequency control in power grids

Strenge

Schultz

Kurths

et al. 2020

Chaos: An Interdisciplinary Journal of Nonlinear Science

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Power systems are subject to fundamental changes due to the increasing infeed of decentralised renewable energy sources and storage. The decentralised nature of the new actors in the system requires new concepts for structuring the power grid, and achieving a wide range of control tasks ranging from seconds to days. Here we introduce a multiplex dynamical network model covering all control timescales. Crucially, we combine a decentralised, self-organised lowlevel control and a smart grid layer of devices that can aggregate information from remote sources. The safety-critical task of frequency control is performed by the former, the economic objective of demand matching dispatch by the latter. Having both aspects present in the same model allows us to study the interaction between the layers. Remarkably, we find that adding communication in the form of aggregation does not improve the performance in the cases considered. Instead, the self-organised state of the system already contains the information required to learn the demand structure in the entire grid. The model introduced here is highly flexible, and can accommodate a wide range of scenarios relevant to future power grids. We expect that it is especially useful in the context of low-energy microgrids with distributed generation.Highly decentralised power grids, possibly in the context of prosumer systems, require new concepts for their stable operation. We expect that both self-organised systems as well as intelligent devices with communication capability that can aggregate information from remote sources will play a central role. Here we introduce a multiplex network model that combines both aspects, and use it in a basic scenario and uncover surprising interactions between the layers.

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Section: B Energy Managementmentioning

confidence: 99%

“…We consider the former a sensible stand-in for other methods that try to achieve an economically optimal situation. The design and performance of the ILC itself as a method for microgrids is treated in a companion paper 50 .…”

Section: A Lower Layermentioning

confidence: 99%

A multiplex, multi-timescale model approach for economic and frequency control in power grids

Strenge

Schultz

Kurths

et al. 2020

Chaos: An Interdisciplinary Journal of Nonlinear Science

Self Cite

View full text Add to dashboard Cite

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D-Type Iterative Learning Control for Open Container Motion System With Sloshing Constraints

Li¹,

Hou

Yong³

2021

IEEE Access

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In this paper, the iterative learning control (ILC) problem is investigated for the motion system of an open container with sloshing constraints in industrial fluid packaging. Initially, a broader class of second-order in space and first-order in time linear time-invariant singular distributed parameter system is decomposed by analyzing the motion system of an open container with sloshing constraints. Meanwhile, to eliminate the influence of singular terms on the system, a closed-loop D-type ILC algorithm is designed, and the corresponding convergence conditions are manifested. Then the convergence of the control algorithm is proved strictly. The resulting tracking error of systems can converge to any small tracking accuracy. Finally, a numerical example is given to verify the convergence and effectiveness of the closed-loop D-type ILC algorithm.

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Iterative learning control in prosumer-based DC microgrids

Vorropoulou

Strenge

Hellmann

2021

2021 IEEE Fourth International Conference on DC Microgrids (ICDCM)

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Iterative learning control in prosumer-based microgrids with hierarchical control

Cited by 3 publications

References 28 publications

A multiplex, multi-timescale model approach for economic and frequency control in power grids

A multiplex, multi-timescale model approach for economic and frequency control in power grids

D-Type Iterative Learning Control for Open Container Motion System With Sloshing Constraints

Iterative learning control in prosumer-based DC microgrids

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