Formulation of Stochastic MPC to Balance Intermittent Solar Power with Hydro Power in Microgrid

Pandey, Madhusudhan; Winkler, Dietmar; Sharma, Roshan; Lie, Bernt

doi:10.3384/ecp21185196

Cited by 1 publication

(1 citation statement)

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“…Also, L. Imsland, P. Kittilsen, and T. Schei (2010) integrated Dymola models into commercial software designed for NMPC and did a case study with an offshore oil and gas processing plant. Pandey et al (2021a) employed OMJulia (Lie et al 2019) for stochastic MPC of solar and hydropower plants described by a set of small-scale DAEs. Pandey et al (2021b) The use of engineering software such as MATLAB for Modelica models offers easy implementation for algorithm prototyping.…”

Section: Introductionmentioning

confidence: 99%

Application of the OpenModelica-Matlab Interface to Integrated Simulation and Successive Linearization Based Model Predictive Control

Alizadeh,

Sahlodin,

Palanisamy

et al. 2023

Linköping Electronic Conference Proceedings

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This paper presents the implementation of successive linearization based model predictive control (SLMPC) efforts through the interfacing of OpenModelica and Matlab using the OMMatlab tool. The dynamic system (here a chemical process) and the model predictive control (MPC) algorithm are implemented in OpenModelica and Matlab, respectively. The model linearization procedure is carried out through OMMatlab, which is highly optimized in terms of run-time by using a single executable file and adapting it at each sample time. Also, necessary theories for a continuous model discretization are discussed for both nonlinear Modelica and linearized continuous models. A procedure for constructing an Extended Kalman Filter (EKF) from a continuous Modelica model is also presented. The usability of the OpenModelica-Matlab interface for SLMPC is demonstrated by control of liquid levels in a tanks-in-series problem.

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Section: Introductionmentioning

confidence: 99%