In this contribution, a model predictive control algorithm is developed, which allows an increase of the solar operating hours of a solar cooling system without a negative impact on the auxiliary electricity demand, e.g., for heat rejection in a dry cooler. An improved method of the characteristic equations for single-effect
absorption chillers is used in combination with a simple dry-cooler model to describe the part load behavior of both components. The aim of the control strategy is to find a cut-in and a cut-off condition for the solar heat operation (SHO) of an absorption chiller cooling assembly (i.e., including all the supply pumps and the dry cooler) under the constraint that the specific electricity demand during SHO is lower than the electricity demand of a reference cooling technology (e.g., a compression chiller cooling assembly). Especially for the cut-in condition, the model predictive control algorithm calculates a minimum driving temperature, which has to be reached by the solar collector and storage in order to cover the cooling load with a low cooling water temperature but restricted auxiliary electricity demand. Measurements at a solar cooling system for an IT center were used for the testing and a first evaluation of the control algorithm.
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