Suggested Citation:
Li, Xuping and Joan M. Ogden (2011) Understanding the Design and Economics of Distributed Tri-generation Systems for Home and Neighborhood Refueling—Part I: Single Family Residence Case Studies. Journal of Power Sources 196 (4), 2098 - 2108

The potential benefits of hydrogen as a transportation fuel will not be achieved until hydrogen vehicles capture a substantial market share. However, although hydrogen fuel cell vehicle (FCV) technology has been making rapid progress, the lack of a hydrogen infrastructure remains a major barrier for FCV adoption and commercialization. The high cost of building an extensive hydrogen station network and the foreseeable low utilization in the near term discourages private investment. Based on the past experience of fuel infrastructure development for motor vehicles, innovative, distributed, small-volume hydrogen refueling methods may be required to refuel FCVs in the near term. Among small-volume refueling methods, home and neighborhood tri-generation systems (systems that produce electricity and heat for buildings, as well as hydrogen for vehicles) stand out because the technology is available and has potential to alleviate consumer’s fuel availability concerns. In addition, it has features attractive to consumers such as convenience and security to refuel at home or in their neighborhood. 

The objective of this paper is to provide analytical tools for various stakeholders such as policy makers, manufacturers and consumers, to evaluate the design and the technical, economic, and environmental performances of tri-generation systems for home and neighborhood refueling. An interdisciplinary framework and an engineering/economic model is developed and applied to assess home tri-generation systems for single family residences (case studies on neighborhood systems will be provided in a later paper). Major tasks include modeling yearly system operation, exploring the optimal size of a system, estimating the cost of electricity, heat and hydrogen, and system CO2 emissions, and comparing the results to alternatives. Sensitivity analysis is conducted, and the potential impacts of uncertainties in energy prices, capital cost reduction (or increase), government incentives and environmental cost are evaluated. Policy implications of the modeling results are also explored.

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