Work

Developing a Predictive Control System for Optimal Chiller Operation

Year: 2025

Type: conference-paper

Abstract: In a world where decarbonisation is an urgent priority, the building sector plays a pivotal role in mitigating carbon emissions. To meet this challenge, it is necessary to adapt HVAC systems and develop advanced controllers, of which Model Predictive Control (MPC) stands out. This work focuses on the development of an MPC designed to optimise the operation of a refrigeration plant. To achieve an accurate controller, detailed models of the main components of the system, such as the chiller and the thermal energy storage tank, have been integrated into a simplified, control-oriented plant model. Various options have been analysed to eliminate the need for binary variables and conditional structures in the model. The developed MPC belongs to the field of nonlinear programming and aims to minimise consumption or cost and to guarantee demand coverage. The controller has been tested on a digital twin of the plant, and calculations have been performed to determine the energy and cost savings achieved.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.17288350

Authors: Bizkarra Belategi, Martin, Herrero López, Saioa, López Pérez, Susana, González-Pino, Iker, Perez-Iribarren, Estibaliz

Institutions: Tekniker, University of the Basque Country

Language: English

Topic: Building Energy and Comfort Optimization

Subfield: Building and Construction

Field: Engineering

Domain: Physical Sciences

SDGs: Climate action, Affordable and clean energy, Industry, innovation and infrastructure

Open Access status: green

Funder: European Commission