Research Article A Comfort-Aware Energy Efficient HVAC System Based on the Subspace Identification Method O. Tsakiridis, 1 D. Sklavounos, 2 E. Zervas, 1 and J. Stonham 2 1 Department of Electronics, TEI of Athens, Egaleo, 12210 Athens, Greece 2 Department of Engineering and Design, Brunel University, Kingston Lane, Middlesex UB8 3PH, UK Correspondence should be addressed to O. Tsakiridis; odytsak@teiath.gr Received 12 October 2015; Revised 12 January 2016; Accepted 8 February 2016 Academic Editor: Aleksander Zidansek Copyright © 2016 O. Tsakiridis et al. Tis is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. A proactive heating method is presented aiming at reducing the energy consumption in a HVAC system while maintaining the thermal comfort of the occupants. Te proposed technique fuses time predictions for the zones’ temperatures, based on a deterministic subspace identifcation method, and zones’ occupancy predictions, based on a mobility model, in a decision scheme that is capable of regulating the balance between the total energy consumed and the total discomfort cost. Simulation results for various occupation-mobility models demonstrate the efciency of the proposed technique. 1. Introduction As the control and limitation of the energy consumption remain a feld with an exceptional technological and eco- nomical interest, areas that have been considered as high energy consumers comprise very challenging research issues. According to the US Energy Information Administration from 2013 through 2040 the electricity consumption in the commercial and residential sectors will be increasing by 0.5% and 0.8% per year [1]. It is well established and widely accepted through research studies that the main energy consumers in the commercial and residential buildings are the Heat Ventilation and Air Conditioning (HVAC) systems, as well as the lighting systems. Buildings contributed a 41% (or 40 quadrillion btu) to the total US energy consumption in 2014. On an average, about 43% of the energy consumption in a commercial and resi- dential building is due to HVAC systems [2]. Terefore, due to the high rate of energy consumption, the necessity of the demand-driven control in the HVAC systems has become inevitable. In modern buildings several sophisticated systems have been applied aiming at providing this type of control in the HVAC systems. Te state-of-the-art technology of the HVAC control considers the occupancy of the zones a very important parameter, playing a key role in methods aiming at reducing energy consumption. Te detection and prediction of the zones’ occupancy are a very challenging research feld and several techniques have been proposed based on historic statistical data as well as on probabilistic models. Another equally important factor taken into account in advanced HVAC control systems is the thermal comfort of the occupants. Te objective of modern HVAC control sys- tems is to reduce energy consumption without compromising the comfort of the occupants. Wireless sensor networks, equipped with temperature, humidity, and occupancy detec- tion sensor nodes, are nowadays the basic platform to build automated HVAC control systems. A number of methods aiming to maintain the thermal comfort while saving energy have been proposed. Some of them are described in Section 2. Towards this direction, a novel technique is proposed in this paper, which aims at balancing the comfort and energy costs in a multizone system. Te decisions on heating the zones or not may be taken either centrally or in a distributed manner by wireless sensor nodes scattered in the multizone system. In any case temperature and zone occupancy information must be exchanged between a node, responsible for a zone, and its neighboring nodes. Te decision process itself relies on two kinds of predictions: (a) temperature-time predictions for Hindawi Publishing Corporation Journal of Energy Volume 2016, Article ID 5074846, 13 pages http://dx.doi.org/10.1155/2016/5074846