Approximate dynamic programming-based control of a building cooling system with thermal storage

The paper addresses the energy management of a building cooling system comprising a chiller plant with two chillers, a thermal storage unit, and a cooling load representing a building. Uncertainty affects the system since the cooling load depends on the building occupancy. The goal is to minimize the energy consumption of the cooling system, while preserving comfort in the building. This is achieved by optimally distributing the cooling load demand among the chillers and the thermal storage unit, and modulating the building temperature set-point to some (limited) extent. The problem can be decomposed into a static optimization problem, and a dynamic programming problem, which is solved based on the abstraction to a Markov chain of the stochastic hybrid system modeling the cooling system.