Distributed hierarchical control for multiple refrigeration units

Abstract

This paper presents a hierarchical distributed control strategy for multiple refrigeration units (RUs). The main target is to create a modular architecture that provides the thermal demand of the central plant in a multi-agent framework. Combined with the model predictive control method, a robust and effective framework is developed that aims to minimize the energy consumption while reducing latency times and switching of the RUs. The upper layer model predictive control is identical for all RUs, while in a lower layer a mixed-integer optimization using the decentralized Frank–Wolfe algorithm secures optimal switching of the RUs. The operational behavior can be easily and transparently adjusted in a wide range. Furthermore, availability and quick replacement of faulty units is guaranteed by the concept. A simulation example consisting of an insulated cool box on a truck demonstrates the versatility and performance of the proposed approach. • Distributed hierarchical optimization for multiple refrigeration units is presented. • Model predictive control with mixed-integer optimization is employed. • Multiple refrigeration units maximize availability for the central plant. • Transparent weighting factors enable wide variety of operating patterns.