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Multi-objective optimization of HVAC system with an evolutionary computation algorithm
- Kusiak, Andrew, Tang, Fan, Xu, Guanglin
- Energy 2011 v.36 no.5 pp. 2440-2449
- air, air conditioning, air quality, air temperature, algorithms, data collection, energy, heat, models
- 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.