PV-grid performance under dynamic weather conditions

Paasch, Kasper M.; Cornaro, Cristina; Pierro, Marco

doi:10.1109/icdcm45535.2019.9232691

Cited by 4 publications

(1 citation statement)

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“…Also in this level, there must be no trading with the power exchange, so there must be enough energy in the battery to bridge extreme cases (grid downtimes, weather fluctuations [12]). Stochastic disturbance variables are mainly the renewable energy yield and production adjustments.…”

Section: B Secondary Controlmentioning

confidence: 99%

Three-Layer Hierarchical Model Predictive Control Concept for Industrial DC Microgrids

Knochelmann

Mannel

Schappler

2021

IECON 2021 – 47th Annual Conference of the IEEE Industrial Electronics Society

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This paper presents an extension of the dual-layer model predictive control (MPC) for industrial DC microgrids. This structure allows an easier integration of stochastic methods on all levels. Moreover, in the new three-layer MPC, energy storages are proposed for each level. As a proof of concept, a control is presented for the new layer, the primary control level in microgrids. The MPC as a central control strategy, has the disadvantage that a new model has to be created for new bus participants. By a simply expandable state space model and a parameterization with data sheet values, this disadvantage can be refuted. Further, for the application on a programmable logic controller (PLC), a simpler and faster MPC with an equal control performance, is presented.

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Section: B Secondary Controlmentioning

confidence: 99%