Work

Application of stochastic model predictive control for building energy systems using latent force models

Year: 2025

Type: article

Abstract: The model-based control of building energy systems (BES) is a hard task, since the system identification is very labor-intensive. This results in inexact models, which are subject to parameter uncertainties. Additionally, disturbances like solar radiation have a great impact on the system dynamics. In this paper we used stochastic model predictive control (SMPC) to account for parameter and disturbance uncertainties. The disturbances are modeled as time-dependent Gaussian Processes (GP), which are known as Latent-Force Models (LFM). The proposed approach is evaluated for two different BES using experimentally obtained data. The results show that the LFM-SMPC results in the lowest discomfort with a reasonable higher energy consumption compared to a constant disturbance prediction.

Source: at - Automatisierungstechnik

DOI: 10.1515/auto-2024-0160

Authors: Thore Wietzke, Daniel Landgraf, Knut Graichen

Institution: Friedrich-Alexander-Universität Erlangen-Nürnberg

Language: English

Topic: Building Energy and Comfort Optimization

Subfield: Building and Construction

Field: Engineering

Domain: Physical Sciences

SDG: Affordable and clean energy

Open Access status: hybrid

Estimated APC paid: $2,712