Housing Archetype Analysis for Home Energy-Efficient Retrofit in the Great Lakes Region

Kim, S. K. ; Mrozowski, T. ; Harrell-Seyburn, A. ; Ehrlich, N. ; Hembroff, L. ; Bieburn, B. ; Mazor, M. ; McIntyre, A. ; Mutton, C. ; Parsons, G. ; Syal, M. G. ; Wilkinson, R.

关键词: MICHIGAN;    GREAT LAKES;    TAXONOMY;    BUILDINGS MARKET CHARACTERIZATION;    COST EFFECTIVE ENERGY RETROFIT;    HOUSING ARCHETYPES;    ENERGY-EFFICIENT;    RETROFIT;    ARCHETYPES;    MICHIGAN;    MICHIGAN STATE UNIVERSITY;    FERRIS STATE UNIVERSITY;    GRAND RAPIDS;    ANN ARBOR;    HABITAT FOR HUMANITY;    KENT COUNTY;    GREAT LAKES;    AMERICAN HOUSING SURVEY;    ARCHETECTURAL STYLES;    MIDWEST;    QUEEN ANNE;    COLD CLIMATE;    TAXONOMY;    HOUSING CHARACTERISTICS;    HOUSING STOCK;    Buildings;   

DOI  :  10.2172/1158446
RP-ID  :  DOE/GO-102014-4002
PID  :  OSTI ID: 1158446
Others  :  Other: KNDJ-0-40347-02

学科分类：能源（综合）

美国|英语

来源: SciTech Connect

【 摘 要 】

This project report details activities and results of the 'Market Characterization' project undertaken by the Cost Effective Energy Retrofit (CEER) team targeted toward the DOE goal of achieving 30%-50% reduction in existing building energy use. CEER consists of members from the Dow Chemical Company, Michigan State University, Ferris State University and Habitat for Humanity Kent County. The purpose of this market characterization project was to identify housing archetypes which are dominant within Great Lakes region and therefore offer significant potential for energy-efficient retrofit research and implementation due to the substantial number of homes possessing similar characteristics. Understanding the characteristics of housing groups referred to as 'archetypes' by vintage, style, and construction characteristics can allow research teams to focus their retrofit research and develop prescriptive solutions for those structure types which are prevalent and offer high potential uptake within a region or market. Key research activities included; literature review, statistical analysis of national and regional data of the American Housing Survey (AHS) collected by the U.S. Census Bureau, analysis of Michigan specific data, development of a housing taxonomy of architectural styles, case studies of two local markets (i.e., Ann Arbor and Grand Rapids in Michigan) and development of a suggested framework (or process) for characterizing local markets. In order to gain a high level perspective, national and regional data from the U.S. Census Bureau was analyzed using cross tabulations, multiple regression models, and logistic regression to characterize the housing stock and determine dominant house types using 21 variables.