1 research outputs found
HVAC Energy Cost Optimization for a Multi-zone Building via a Decentralized Approach
It has been well acknowledged that buildings account for a large proportion
of the world's energy consumption. However, the energy use of buildings,
especially the heating, ventilation and air-conditioning (HVAC), is far from
being efficient. There still exists a dramatic potential to save energy through
improving building energy efficiency. Therefore, this paper studies the control
of HVAC system for multi-zone buildings with the objective to reduce energy
consumption cost while satisfying thermal comfort. In particular, the thermal
couplings due to the heat transfer between the adjacent zones are incorporated
in the optimization. Considering that a centralized method is generally
computationally prohibitive for large buildings, an efficient decentralized
approach is developed, based on the Accelerated Distributed Augmented
Lagrangian (ADAL) method [1]. To evaluate the performance of the proposed
method, we first compare it with a centralized method, in which the optimal
solution of a small-scale problem can be obtained. We find that this
decentralized approach can almost approach the optimal solution of the problem.
Further, this decentralized approach is compared with the Distributed
Token-Based Scheduling Strategy (DTBSS) [2]. The numeric results reveal that
when the number of zones is relatively small (less than 20), the two
decentralized methods can achieve a comparable performance regarding the cost
of the HVAC system. However, with an increase of the number of zones in the
building, the proposed decentralized approach demonstrates better performance
with a considerable reduction of the total cost. Moreover, the decentralized
approach proposed in this paper demonstrate better scalability with less
average computation required.Comment: 13 pages, 8 figure