Multi-objective optimization of HVAC system with an evolutionary computation algorithm

• Published in: Energy (Oxford) Vol. 36; no. 5; pp. 2440 - 2449
• Main Authors: Kusiak, Andrew, Tang, Fan, Xu, Guanglin
• Format: Journal Article
• Language: English
• Published: Kidlington Elsevier Ltd 01-05-2011; Elsevier
• Subjects: air; air conditioning; Air conditioning. Ventilation; air quality; air temperature; Algorithms; Applied sciences; Control systems; data collection; Data-driven models; Energy; Energy conservation; Energy savings; Energy use; Energy. Thermal use of fuels; Evolutionary algorithms; Evolutionary computation algorithm; Exact sciences and technology; heat; Heating, air conditioning and ventilation; HVAC system optimization; Mathematical analysis; Mathematical models; Optimization; HVAC system optimization; Data-driven models; Evolutionary computation algorithm; Energy savings; Air conditioning; Energy consumption; Ventilation; Data mining; Evolutionary algorithm; Optimization method
• ISSN: 0360-5442
• DOI: 10.1016/j.energy.2011.01.030

A data-mining approach for the optimization of a HVAC (heating, ventilation, and air conditioning) system is presented. A predictive model of the HVAC system is derived by data-mining algorithms, using a dataset collected from an experiment conducted at a research facility. To minimize the energy while maintaining the corresponding IAQ (indoor air quality) within a user-defined range, a multi-objective optimization model is developed. The solutions of this model are set points of the control system derived with an evolutionary computation algorithm. The controllable input variables — supply air temperature and supply air duct static pressure set points — are generated to reduce the energy use. The results produced by the evolutionary computation algorithm show that the control strategy saves energy by optimizing operations of an HVAC system.
► A data-mining approach for the optimization of a heating, ventilation, and air conditioning (HVAC) system is presented. ► The data used in the project has been collected from an experiment conducted at an energy research facility. ► The approach presented in the paper leads to accomplishing significant energy savings without compromising the indoor air quality. ► The energy savings are accomplished by computing set points for the supply air temperature and the supply air duct static pressure.