Energy characteristics of multi-chiller load distribution algorithms in a large office building

Park, Jiwon; Hwan Cha, Jae; Yoon, Yeobeom; Ho Lee, Kwang

doi:10.1016/j.enbuild.2024.114462

Energy characteristics of multi-chiller load distribution algorithms in a large office building

Journal Article · Mon Jun 24 00:00:00 EDT 2024 · Energy and Buildings

DOI:https://doi.org/10.1016/j.enbuild.2024.114462· OSTI ID:2397426

Park, Jiwon ^[1]; Hwan Cha, Jae ^[1]; ^[2]; Ho Lee, Kwang ^[1]

Korea Univ., Seoul, (Korea, Republic of)
Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)

Here, this study evaluates the energy efficiency of multi-chiller systems in large office buildings, focusing on their optimization across various climate zones as defined by ASHRAE. Using EnergyPlus for simulations, the research examines five different load distribution algorithms in multi-chiller systems that range from one to ten chillers, aiming to understand their effectiveness in 15 distinct climate zones. The primary objectives of the study include identifying the energy efficiency of multi-chiller systems in each climate zone, determining the appropriate number of chillers for each zone, and evaluating the performance of the load distribution algorithms. Based on the U.S. Department of Energy’s commercial building model, the results suggest that multi-chiller systems can significantly reduce cooling energy consumption in various climates. Among the algorithms evaluated, the Sequential Uniform Part Load Ratio (SUPLR) algorithm demonstrates notable efficiency, especially in the 4A climate zone (Baltimore), where it achieves substantial energy savings. Applying the SUPLR algorithm in a multi-chiller setup with four chillers in this zone leads to an estimated 24.5 % reduction in energy usage, equivalent to 183 MW annually. The research indicates that a range of 3 to 5 chillers is typically optimal for most climate zones. In-depth analysis in the 4A climate zone highlights the importance of minimizing operation hours at low Part Load Ratios (PLR) to ensure that chillers operate at a high Coefficient of Performance (COP). This strategy underscores the potential of well-designed multi-chiller systems to reduce cooling energy demand, particularly in climates with transitional seasons. This study provides an overview of the energy-saving potential of multi-chiller systems, applicable across a variety of climatic scenarios.

View Accepted Manuscript (DOE)

Research Organization:: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)

Sponsoring Organization:: USDOE Office of Energy Efficiency and Renewable Energy (EERE)

Grant/Contract Number:: AC05-00OR22725

OSTI ID:: 2397426

Journal Information:: Energy and Buildings, Journal Name: Energy and Buildings Vol. 318; ISSN 0378-7788

Publisher:: ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

References (25)

Chilled water temperature set-point reset based on outdoor air temperature and its cooling energy performance in an office building Lee, Young Jun; Hong, Sung Hyup; Lee, Jong Man Journal of Mechanical Science and Technology, Vol. 36, Issue 3 https://doi.org/10.1007/s12206-022-0241-4	journal	March 2022
Analysis of thermal environment and energy performance by biased economizer outdoor air temperature sensor fault Kim, Chul Ho; Lee, Sung Chan; Park, Kyung Soon Journal of Mechanical Science and Technology, Vol. 36, Issue 4 https://doi.org/10.1007/s12206-022-0342-0	journal	March 2022
On energy-efficient HVAC operation with Model Predictive Control: A multiple climate zone study Raman, Naren Srivaths; Chen, Bo; Barooah, Prabir Applied Energy, Vol. 324 https://doi.org/10.1016/j.apenergy.2022.119752	journal	October 2022
A PSO-based algorithm for optimal multiple chiller systems operation Beghi, Alessandro; Cecchinato, Luca; Cosi, Giovanni Applied Thermal Engineering, Vol. 32 https://doi.org/10.1016/j.applthermaleng.2011.08.008	journal	January 2012
Effects of scenario uncertainty on chiller sizing method Kang, Yingzi; Augenbroe, Godfried; Li, Qi Applied Thermal Engineering, Vol. 123 https://doi.org/10.1016/j.applthermaleng.2017.05.041	journal	August 2017
Benefits assessment of cool skin and ventilated cavity skin: Saving energy and mitigating heat and grid stress Park, Jiwon; Lee, Kwang Ho; Lee, Sang Hoon Building and Environment, Vol. 247 https://doi.org/10.1016/j.buildenv.2023.111027	journal	January 2024
A numerical study on the optimization method to optimize the cooling load sharing for a multi-chiller system in a shopping mall Junwei, Yan; Cheng, Chen; Dongmei, Pan Energy Procedia, Vol. 142 https://doi.org/10.1016/j.egypro.2017.12.398	journal	December 2017
Lower and upper threshold limit for artificial neural network based chilled and condenser water temperatures set-point control in a chilled water system Yeon, Sang Hun; Yoon, Yeobeom; Kang, Won Hee Energy Reports, Vol. 9 https://doi.org/10.1016/j.egyr.2023.05.263	journal	December 2023
Optimal chiller loading by genetic algorithm for reducing energy consumption Chang, Yung-Chung; Lin, Jui-Kun; Chuang, Meng-Hsuan Energy and Buildings, Vol. 37, Issue 2 https://doi.org/10.1016/j.enbuild.2004.06.002	journal	February 2005
Optimal chiller loading by evolution strategy for saving energy Chang, Yung-Chung Energy and Buildings, Vol. 39, Issue 4 https://doi.org/10.1016/j.enbuild.2005.12.009	journal	April 2007
A novel approach for optimal chiller loading using particle swarm optimization Ardakani, A. Jahanbani; Ardakani, F. Fattahi; Hosseinian, S. H. Energy and Buildings, Vol. 40, Issue 12 https://doi.org/10.1016/j.enbuild.2008.06.010	journal	January 2008
Oversizing of HVAC system: Signatures and penalties Djunaedy, Ery; van den Wymelenberg, Kevin; Acker, Brad Energy and Buildings, Vol. 43, Issue 2-3 https://doi.org/10.1016/j.enbuild.2010.10.011	journal	February 2011
Exploring HVAC system sizing under uncertainty Sun, Yuming; Gu, Li; Wu, C. F. Jeff Energy and Buildings, Vol. 81 https://doi.org/10.1016/j.enbuild.2014.06.026	journal	October 2014
Detailed analysis on part load ratio characteristics and cooling energy saving of chiller staging in an office building Seo, Byeong Mo; Lee, Kwang Ho Energy and Buildings, Vol. 119 https://doi.org/10.1016/j.enbuild.2016.03.067	journal	May 2016
Optimal chiller loading by improved invasive weed optimization algorithm for reducing energy consumption Zheng, Zhi-xin; Li, Jun-qing Energy and Buildings, Vol. 161 https://doi.org/10.1016/j.enbuild.2017.12.020	journal	February 2018
Optimal chiller loading in dual-temperature chilled water plants for energy saving Jia, Lizhi; Liu, Junjie; Wei, Shen Energy and Buildings, Vol. 252 https://doi.org/10.1016/j.enbuild.2021.111425	journal	December 2021
Optimal chiller loading including transients Arahal, Manuel R.; Satué, Manuel G.; Ortega, Manuel G. Energy and Buildings, Vol. 253 https://doi.org/10.1016/j.enbuild.2021.111527	journal	December 2021
Framework to assess climate change impact on heating and cooling energy demands in building stock: A case study of Belgium in 2050 and 2100 Elnagar, Essam; Gendebien, Samuel; Georges, Emeline Energy and Buildings, Vol. 298 https://doi.org/10.1016/j.enbuild.2023.113547	journal	November 2023
Optimal loading distribution of chillers based on an improved beluga whale optimization for reducing energy consumption Li, Ze; Gao, Jiayi; Guo, Junfei Energy and Buildings, Vol. 307 https://doi.org/10.1016/j.enbuild.2024.113942	journal	March 2024
Optimal chiller loading by improved artificial fish swarm algorithm for energy saving Zheng, Zhi-xin; Li, Jun-qing; Duan, Pei-yong Mathematics and Computers in Simulation, Vol. 155 https://doi.org/10.1016/j.matcom.2018.04.013	journal	January 2019
Energy Modeling and Chillers Sizing of HVAC System for a Hotel Building Wang, Fujen; Lin, Hungwen; Tu, Weida Procedia Engineering, Vol. 121 https://doi.org/10.1016/j.proeng.2015.09.161	journal	January 2015
Chiller Plant Sizing by Cooling Load Simulation as a Means to Avoid Oversized Plant Yik, F. W. H.; Lee, W. L.; Burnett, J. HKIE Transactions, Vol. 6, Issue 2 https://doi.org/10.1080/1023697X.1999.10667801	journal	January 1999
Optimal Load Distribution Strategy for Multiple Chiller Water Units Based on Adaptive Genetic Algorithms Jun, Zhang; Kan-yu, Zhang 2010 Second WRI Global Congress on Intelligent Systems https://doi.org/10.1109/GCIS.2010.64	conference	December 2010
Learnings Networks and Professional Development in Building Energy Management Systems Industry Soleymani, Ali; van den Brom, Paula; Ahmed, Samir Education Sciences, Vol. 13, Issue 2 https://doi.org/10.3390/educsci13020215	journal	February 2023
Design and Implementation of Smart Buildings: A Review of Current Research Trend Kim, Dongsu; Yoon, Yeobeom; Lee, Jongman Energies, Vol. 15, Issue 12 https://doi.org/10.3390/en15124278	journal	June 2022

Similar Records

Performance evaluation of conventional chiller systems

Journal Article · Thu Jun 01 00:00:00 EDT 1995 · ASHRAE Journal · OSTI ID:194239

Electric chiller buyer`s guide: Water-cooled centrifugal and screw chillers

Book · Thu Jun 01 00:00:00 EDT 1995 · OSTI ID:55529

Developing Near Optimal Control Sequences for Chiller Plants with Water-side Economizers: A Case Study in a Warm and Marine Climate

Conference · Thu May 23 00:00:00 EDT 2024 · OSTI ID:2446847

Related Subjects

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION
Chiller staging
Load distribution algorithm
Multi-chiller system
Part load ratio

Energy characteristics of multi-chiller load distribution algorithms in a large office building

Citation Formats

References (25)

Similar Records

Related Subjects