Assessing performance and controlling operating conditions of a solar driven absorption chiller using simplified numerical models

In cooling buildings, the use of solar energy can save around 50% of primary energy. Many studies have demonstrated the interest of such systems. However, developing and improving reliability of new components, design, control, and implementation remain a major concern. The performances of solar cooling systems are greatly influenced by climatic conditions. Indeed they affect both the driving energy of the chiller and the heat rejection. It is important to mention that internal loads and control strategy also have an impact on energy performances. Therefore, assessing the energy performance during the design phase is a key point in evaluating the economic interest of an installation. Moreover, once the commissioning of the installation is accomplished, there is a need to follow through and ensure its performance, since a large number of malfunctions can affect the quality of the system. Actual performances can be very different from those calculated in the design phase.With this aim, the present article deals with the development of an absorption chiller model used in an existing solar cooling system. This installation includes a single effect absorption chiller with a nominal chilling capacity of 30 kW (EAW LB30 chiller functioning with water and lithium bromide), and it cools four classrooms of a University building in Reunion Island which is situated under a tropical climate. This pilot plant is very good monitored and can thus be used to develop and validate the absorption chiller model. The present paper first recalls the absorption principle and presents the pilot plant, the metrology, and the control strategy. Secondly, the experimental results are analysed and the steady state chiller model and also the identification method are developed. Thereafter, the simplex method is used to determine the design parameters of the machine. Finally, the simulation results are presented. The good agreement between the prediction and the experimental results allows the use of the model not only to design an installation but also to follow and control its performances.