Development and Experimental Evaluation of Grey-Box Models for Application in Model Predictive Control of a Microscale Polygeneration System

TL;DR

This paper develops and experimentally evaluates grey-box models for a microscale polygeneration system, enabling improved model predictive control by capturing complex dynamics and internal control logic.

Contribution

It introduces a rational grey-box modeling procedure tailored for energy systems, validated through experimental data and applied to real-world control scenarios.

Findings

Models accurately represent system dynamics

Enhanced control performance demonstrated

Methodology validated with experimental data

Abstract

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.