In this paper, we outline a framework and the algorithms that will enable a home controller to accomplish occupancy-moderated multi-zone, multi-inhabitant space-conditioning under a demand-driven pricing scheme for electricity. We investigated the effects that influencing factors such as the number of zones and inhabitants, randomness of occupancy patterns and thermal mass of the residence can have on the efficacy of occupancy-moderated zonal space-conditioning (OZS) under different scenarios. Simulations driven by real data and highly realistic proxy data reveal that OZS can achieve improvements averaging 23% over the case without under certain settings. Our investigations also revealed that a house with heavier thermal mass stands to gain as much as 15% from OZS with pre-conditioning than a lighter one. We further offer a few pointers on reducing the cost of space-conditioning using OZS under a demand-driven pricing scheme to the average homeowner based on our findings. (C) 2013 Elsevier B.V. All rights reserved.