Development and Assessment of Hybrid Ventilation Control Strategies using a Multicriteria Approach

The purpose of this paper is to provide a multicriteria approach in order to develop and assess several control methods for hybrid ventilation. This is important because there is currently a great interest in hybrid ventilation as an energy efficient strategy for achieving thermal comfort and good indoor air quality. To reach those targets and manage hybrid ventilation systems, advanced control strategies, based on hierarchical fuzzy controllers, have been developed at the LASH laboratory. In order to permit an objective evaluation of these controllers, in relation to the integration of comfort, indoor air quality, energy and stability criteria, two fitness functions have been defined and tested. The principle of the developed functions consists of converting all assessment criteria to financial equivalents. This takes into account occupant productivity, discomfort cost, heating and ventilating cost, and operating cycles of equipment. Such inhomogeneous terms are not very easy to assess and the main difficulty is to define equivalences between them. To achieve this, both static and adaptive approaches of thermal comfort have been taken into account. PMV, adaptive comfort temperature and CO2 concentrations have been used to evaluate the comfort criteria. First, several simulations under winter and summer conditions were performed using a numerical model. The relative performances of developed architectures were then studied using a sensitivity study. Finally the optimum method was tested using an experimental test cell (HybCell) which was conceived to develop and assess controllers for hybrid ventilation. The results show that mutlticriteria control architecture was able to manage heating and ventilation to provide optimal thermal comfort and indoor air quality at the lowest possible cost.