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It has been well acknowledged that buildings account for a large proportionof the world's energy consumption. However, the energy use of buildings,especially the heating, ventilation and air-conditioning (HVAC), is far frombeing efficient. There still exists a dramatic potential to save energy throughimproving building energy efficiency. Therefore, this paper studies the controlof HVAC system for multi-zone buildings with the objective to reduce energyconsumption cost while satisfying thermal comfort. In particular, the thermalcouplings due to the heat transfer between the adjacent zones are incorporatedin the optimization. Considering that a centralized method is generallycomputationally prohibitive for large buildings, an efficient decentralizedapproach is developed, based on the Accelerated Distributed AugmentedLagrangian (ADAL) method [1]. To evaluate the performance of the proposedmethod, we first compare it with a centralized method, in which the optimalsolution of a small-scale problem can be obtained. We find that thisdecentralized approach can almost approach the optimal solution of the problem.Further, this decentralized approach is compared with the DistributedToken-Based Scheduling Strategy (DTBSS) [2]. The numeric results reveal thatwhen the number of zones is relatively small (less than 20), the twodecentralized methods can achieve a comparable performance regarding the costof the HVAC system. However, with an increase of the number of zones in thebuilding, the proposed decentralized approach demonstrates better performancewith a considerable reduction of the total cost. Moreover, the decentralizedapproach proposed in this paper demonstrate better scalability with lessaverage computation required.

HVAC Energy Cost Optimization for a Multi-zone Building via a Decentralized Approach