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Operating Temperature Optimization for a 5th Generation District Heating and Cooling Network Using Model Predictive Control
Conference proceeding   Peer reviewed

Operating Temperature Optimization for a 5th Generation District Heating and Cooling Network Using Model Predictive Control

Yuhang Zhang, Mingzhe Liu, Zheng O'Neill, Jin Wen and ASHRAE
ASHRAE transactions, v 131, pp 546-555
01 Jan 2025

Abstract

Construction & Building Technology Engineering Engineering, Mechanical Science & Technology Technology
A 5th generation district heating and cooling (5GDHC) network is a promising advancement in district energy systems (DES), offering substantial potential to reduce building energy consumption and carbon emissions. However, optimal control strategies for these systems have been relatively underexplored. To narrow this gap, in this paper, a model predictive control (MPC)-based temperature operating optimization framework for 5GDHC networks is proposed. With the aim of minimizing the total system energy consumption, the temperature bounds used in the free-floating temperature control strategy are optimized by a model predictive controller using the differential evolution algorithm. The model utilized for MPC is the actual virtual testbed developed using Modelica, based on a use case with three substations and one balancing unit in Denver, CO. Three typical weeks representing summer, shoulder, and winter seasons are investigated to assess the effectiveness of the proposed optimal control method. The results demonstrate that compared with the baseline setting featuring constant upper and lower bounds, the optimized approach achieves significant energy savings: 10.07% during the summer week and 6.23% during the shoulder season week. However, no notable energy savings are observed during the winter week. These findings underscore the importance of optimizing temperature control to leverage temperature-varying renewable thermal sources within 5GDHC systems, thereby enhancing overall system energy performance.

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UN Sustainable Development Goals (SDGs)

This publication has contributed to the advancement of the following goals:

#7 Affordable and Clean Energy

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Collaboration types
Domestic collaboration
Web of Science research areas
Construction & Building Technology
Engineering, Mechanical
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