<title>Development and validation of adaptive optimal operation methodology for building HVAC systems</title>

Abstract

An innovative approach to building operation, called the adaptive optimal operation methodology (AOOM), is developed and validated in this study. The AOOM, which resides in the building energy management and control system, estimates the building and heating, ventilating, and air conditioning (HVAC) system loads and parameters and supplies the local controllers the optimal set points that minimize the energy cost while maintaining occupant comfort. The AOOM uses the recursive least square method with an adaptive forgetting factor to estimate the parameters for the building zones and HVAC systems. A genetic algorithm optimizer together with a system model is then used to generate the optimal set points, such as the supply air temperature set point as well as the set points of minimum air flow rate and zone temperature for each zone. The system model is validated through different types of experiments. System level validation experiments conducted during the heating and cooling seasons indicate that the HVAC system operated under the AOOM consumes 3 to 10.8 % less heated water energy during the heating season and 1 to 4 % less electrical energy during the cooling season when compared with a commercial operation methodology.