Zoning and occupancy-moderation for residential space-conditioning under demand-driven electricity pricing

Abstract

Occupancy-moderated zonal space-conditioning (OZS) refers to the partitioning of a residence into different zones and independently operating the space-conditioning equipment of each zone based on its occupancy. OZS remains largely unexplored in spite of its potential to reduce the cost of space-conditioning. Despite the excitement surrounding cloud-connected devices like mobile phones and tablet computers, the benefit of using them to aid energy management agents (EMAs) in reducing space-conditioning cost under demand-driven pricing of electricity is not well understood. We develop a novel framework and the algorithms to enable an EMA to implement OZS for multiple inhabitants under a demand-driven pricing scheme for electricity. We further investigate the effects that influencing factors can have on the effectiveness of OZS under different scenarios using Monte Carlo simulations. The simulation results demonstrate that OZS is realizable on a simple home computer and can achieve significant space-conditioning cost reductions in practice. In our studies, both the financial operating cost of space-conditioning and the cost associated with discomfort are included in a single aggregate cost function. We then expand the simulations to study the cost reduction that is achievable when using cloud-connected devices to provide remote schedule updates to an EMA. This part of the study reveals that reduction in space-conditioning cost is appreciable if a working resident remotely updates an EMA at mid-day of his return time in the evening. In addition, we establish a directly proportional relationship between the level of space-conditioning cost reduction achievable and the variance of return time. Based on the research findings, we further offer recommendations and ideas for future research on the use of OZS and remote schedule updates to different stakeholders like policy-makers and homeowners.