Large-scale energy cost optimization and performance analysis for dedicated outdoor air system: simulation results from ASHRAE RP-1865

• Published in: HVAC&R research Vol. 30; no. 10; pp. 1217 - 1235
• Main Authors: Choi, Youngsik, Lu, Xing, Feng, Fan, O'Neill, Zheng
• Format: Journal Article
• Language: English
• Published: Philadelphia Taylor & Francis 25-11-2024; Taylor & Francis Ltd
• Subjects: Air temperature; Buildings; Built environment; Climate models; Configurations; Control systems; Dehumidification; Energy; Energy costs; Genetic algorithms; Green buildings; HVAC; HVAC equipment; Optimal control; Optimization; Performance evaluation; Research projects; Sequences; Temperature control; Ventilation
• ISSN: 2374-4731; 2374-474X
• DOI: 10.1080/23744731.2024.2394358

This is the first journal article from the ASHRAE research project RP 1865, "Optimizing Supply Air Temperature Control for Dedicated Outdoor Air Systems," focusing on the large-scale energy performance evaluation of the optimal control of dedicated outdoor air systems (DOAS). DOAS is a type of air handling system that is installed in buildings to ensure proper ventilation for the built environment. It is acknowledged that DOAS with proper operation strategies can provide sufficient ventilation and dehumidification while achieving energy efficiency. In this regard, there have been efforts to develop advanced control sequences (e.g., optimal control) for DOAS. Still, limited studies have demonstrated the effectiveness of such DOAS controls on a larger scale under varying climate zones with different DOAS configurations. To fill the research gap, this study aims to quantify the energy-saving potentials of applying an optimal supply air temperature (SAT) control strategy for DOAS considering diverse configurations of HVAC systems in various climate conditions across the United States. For this study, we first developed a total of 180 EnergyPlus models accommodating different types of buildings (i.e., detailed medium-sized office and primary school) and HVAC systems (i.e., DOAS types, DOAS sizes, and terminal units) under varying ASHRAE climate zones (i.e., 2A, 3B, 4A, 4C, 6A, and 6B). Next, genetic algorithm (GA)-based optimizations were conducted to determine the optimal DOAS SAT control that would minimize the energy cost of the entire HVAC system operation. Our study of comparing the optimal control to a typical rule-based control (i.e., outdoor air temperature-based reset control) revealed approximately 4-34% of energy cost saving potential by optimizing the DOAS SAT control sequence.