Hybrid ventilation performance assessment using fitness functions

The purpose of this paper is to provide a multicriteria approach in order to develop and to assess several architectures of controllers for hybrid ventilation. Indeed, there is nowadays a great interest in hybrid ventilation as an energy efficient strategy to achieve thermal comfort and indoor air quality. To reach those targets and manage hybrid ventilation systems, advanced control strategies based on hierarchical fuzzy controllers have been therefore developed at the LASH laboratory. In order to allow an objective evaluation of those controllers integrating comfort, indoor air quality, energy and stability criteria, two fitness functions have been defined and tested. The use of this multicriteria approach is also of special importance for the tuning process to refine the fuzzy sets and rules. The principle of developed functions consist on converting all assessment criteria to financial equivalent ones taking into account occupant productivity, discomfort cost, heating and ventilating cost and operating cycles of equipments. Such inhomogeneous terms are not very easy to asses and the main difficulty is to define equivalences between them. To do so, 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 climate have been performed using a numerical model. The relative performances of developed architectures are then studied using a sensitivity study and the selected one has been tested using an experimental test cell (HybCell) conceived to develop and to assess controllers for hybrid ventilation.