A New HVAC Control System for Improving Perception of Indoor Ambiences

Abstract

Thermal comfort plays a vital role in any working environment. However, it is a very ambiguous term and a concept that is difficult to represent on modern computers. It is best defined as a condition of the mind which expresses satisfaction with the thermal environment, and therefore, it is dependent on the individual’s physiology and psychology. Most often the set point and working periods of the Heating Ventilating and Air Conditioning system (HVAC) can be adjusted to suit the indoor conditions expected within a building. Despite this, as each building presents its own constructional characteristics and habits of its occupants, most common control systems do not factor in these variations. Consequently, the thermal comfort conditions are beyond the range of optimal behaviour, and further, of energy consumption. To solve this problem several researchers have investigated the relationships between room conditions and thermal comfort. Normally, statistical approaches were employed, while recently, fuzzy and neural approaches have been proposed. In this context, most control systems present an adequate accuracy in controlling indoor ambiences but, as mentioned earlier, this is insufficient. Therefore, a new algorithm is needed for this control system, which must necessarily consider the real construction characteristics of the indoor ambience as well as the occupants’ habits. The comfort equation obtained by (Fanger, 1970) is observed to be too complicated to be solved using manual procedures, and more simplified models are needed as described in the following sections. In this chapter a new methodology to control Heating Ventilating and Air Conditioning systems (HVAC) is discussed. This new methodology allows us to define the actual indoor ambiences, obtain an adequate model for each particular room, and employ this information to minimize the percentage of dissatisfaction, and simultaneously, reduce the energy consumption. Identical results can be obtained using expensive sampling apparatuses like thermal comfort modules and general HVAC control systems. Despite this, our new procedure, University of A Coruna patent P200801036, is based on the fact that simple models, adapted for each particular indoor ambience, will permit us to sample the principal related variables with low-cost sampling methods, such as data loggers. Finally, in this chapter the different ambiences where it can be employed will be dealt with. 15