Development and Experimental Evaluation of Grey-Box Models for Application in Model Predictive Control of a Microscale Polygeneration System
Provides a practical modelling methodology for complex energy systems, but the results are incremental and specific to the described system.
The paper develops grey-box models for a microscale polygeneration system to enable economic model predictive control, and evaluates them against experimental data, demonstrating their suitability for optimization-based supervisory control.
With the need for optimisation based supervisory controllers for complex energy systems, comes the need for reduced order system models representing not only the non-linear characteristics of the components, but also certain unknown process dynamics like their internal control logic. We present in this paper an extensive literature study of existing methods and a rational modelling procedure based on the grey-box methodology that satisfies the necessary characteristics for models to be applied in an economic-MPC of a real-world polygeneration system at the Offenburg University of Applied Sciences. The engineering application of the models and their fitting coefficients are shared in this paper. Finally, the models are evaluated against experimental data and the efficacy of the methodology is discussed based on quantitative and qualitative arguments.