The objective of the proposed research is to study the integrated management of residential and personal transportation energy consumption to improve overall performance, efficiency, and reliability. The first goal of the proposal is to develop a highly resolved residential energy eco-system computational model that captures all energy consumption of an individual household, including energy for personal transportation. This can be either in the form of fossil fuels (gasoline, diesel, or natural gas) or electricity, in the case of plug-in electric vehicles. The second goal is to develop a hierarchical dynamic energy management framework for multiple interconnected energy eco-systems considering multiple energy carriers and the incorporation of stochastic human energy use behavior. The hierarchical energy management system optimally manages vehicle-building interactions for a group of residential buildings and associated vehicles. The management approach is non-disruptive, in the sense that consumers are not required to change their behavior. Deliverables include: a highly-resolved residential and transportation energy use computational model, validated using data from local utilities and from electric vehicle databases; a hierarchical energy management policy; the demonstration of the energy management policy in simulation; and an outreach component through the Ohio Energy Project.
The outcome of this work, if successful, will have a broad impact on energy efficiency, demand response, and on integration of multiple energy carriers and coordination among them -- all necessary conditions for the development of a sustainable energy system. Moreover, introduction of energy diversity in the residential-transportation sectors may significantly contribute to national energy independence. The results of this project have value beyond the immediate application considered here, since many of the advances required to realize the proposed model and optimization framework are directly transferable to other domains. In particular, the proposed modeling approach that quantifies stochastic consumer energy use behaviors provides a novel perspective to study complex interactions between human and technological systems, while the proposed hierarchical energy management framework that achieves the optimal tradeoff between population and individual objectives represents an effective strategy to control and manage sustainable infrastructure systems involving multiple participants. Dissemination of the results of the project to (utility and automotive) industry partners will enable greater societal impact.
