Modular Model Composition for Rapid Implementations of Embedded Economic Model Predictive Control in Microgrids

Titelangaben

Kull, Tobias ; Zeilmann, Bernd ; Fischerauer, Gerhard:
Modular Model Composition for Rapid Implementations of Embedded Economic Model Predictive Control in Microgrids.
In: Applied Sciences. Bd. 11 (2021) Heft 22 . - No. 10602.
ISSN 2076-3417
DOI der Verlagsversion: https://doi.org/10.3390/app112210602

Volltext

	Format: PDF Name: applsci-11-10602.pdf Version: Veröffentlichte Version Verfügbar mit der Lizenz Creative Commons BY 4.0: Namensnennung
	Download (1MB)

Abstract

Economic model predictive control in microgrids combined with dynamic pricing of grid electricity is a promising technique to make the power system more flexible. However, to date, each individual microgrod requires major efforts for the mathematical modelling, the implementation on embedded devices, and the qualification of the control. In this work, a field suitable generalized linear microgrid model is presented. This scalable model is instantiated on field-typical hardware and in a modular way, so that a class of various microgrids can be easily controlled. This significantly reduces the modelling effort during commissioning, decreases the necessary qualification of commissioning staff, and allows for easy integration of additional microgrid devices during operation. An exemplary model, derived from an existing production facility microgrid, is instantiated and characteristics of the results are analysed.