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Intelligent decision support system framework for energy retrofits in existing homes

Posted on:2015-09-26Degree:Ph.DType:Dissertation
University:Michigan State UniversityCandidate:Duah, Daniel Yaw AddaiFull Text:PDF
GTID:1478390020951014Subject:Engineering
Abstract/Summary:
Buildings, particularly residential ones, are one of the major consumers of energy. The majority of the housing stock consists of existing homes, a large number of which are energy inefficient. Retrofitting existing homes to make them energy efficient can contribute immensely to energy savings and associated economic, environmental, and health benefits to homeowners. Despite the established benefits and opportunities of energy retrofitting of homes, its adoption has faced obstacles. The lack of information and the presentation of information in a format not easily understood and used by homeowners for decision-making were identified as major obstacles. The goal of this research is to support the implementation of home energy retrofits. This goal was supported through the identification of the determinants of home energy retrofit expert knowledge, the development of an energy retrofit expert knowledge elicitation strategy, building of consensus on energy retrofit knowledge for decision-making, and the development of an intelligent decision support system framework. Specifically, the objectives of the research were: (1) to compile the information barriers to energy retrofits decision process and adoption, (2) to analyze the energy retrofit decision process model and its potential implementation as an intelligent decision support system, (3) to investigate the process of expertise development with a focus on energy retrofit decision process, (4) to develop an expertise elicitation strategy for energy retrofit knowledge, (5) to develop an IDSS framework for energy retrofits for homes, and (6) to demonstrate the application of the IDSS framework with a pilot system. Seven deliverables were achieved through this research. First, the barriers to home energy retrofit adoption were identified. Second, the protocols followed for decision-making in this domain were appraised and determined to be suitable as a building block for the eventual development of an intelligent decision support system framework. Third, the determinants of home energy retrofit experts were developed. Fourth, a home energy retrofit expertise elicitation strategy was developed and used to elicit the expertise of 19 industry experts, identified based on the determinants of expert knowledge. Fifth, the study was able to identify and achieve consensus on relevant energy retrofit knowledge used in decision-making. Sixth, an intelligent decision support system framework that combines the energy retrofit decision process, quantitative information, and expert knowledge in order to provide suitable information to homeowners to help them with decision-making was developed. Finally, the applicability of the framework was demonstrated using a pilot tool obtained from Exsys Corvid incorporated. This research proposed an approach that enhances the packaging and delivery of energy retrofit information to homeowners in order to help with decision making. The researcher envisages that the implementation of the findings of this research will remove the information barriers to the uptake of home energy retrofits, leading to an increase in its adoption and hence, reduce energy consumption of buildings to acceptable levels. The researcher further envisages that the determinants of industry expert knowledge and its elicitation, and the IDSS framework will be accepted and incorporated into industry practices, training, development, and scholarly research.
Keywords/Search Tags:Energy, Intelligent decision support system framework, Home, Expert knowledge, Development, Existing, Elicitation
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