2026-09-20T09:56:56Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/782332026-06-16T18:17:18Zcom_1721.1_7582com_1721.1_7581col_1721.1_131022
Fred Moavenzadeh.
Kristinsdottir, Asbjorg
Massachusetts Institute of Technology. Dept. of Civil and Environmental Engineering.
Massachusetts Institute of Technology. Department of Civil and Environmental Engineering
2013-03-28T18:24:10Z
2013-03-28T18:24:10Z
2012
2012
http://hdl.handle.net/1721.1/78233
829236396
Thesis (Ph. D. in the field of Construction Engineering and Management)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 2012.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 204-209).
Power plant development projects are typically capital intensive and subject to a complex network of interconnected risks that impact development's performance. Failure to develop a power plant to meet performance constraints can come at great cost to the developer and other stakeholders involved. In order to develop an investment strategy plan based on their risk appetite, and manage risks effectively, developers must be able to identify and analyze project opportunity risks. This dissertation is motivated by the need to study the nature and impact of risks on a power plant development project, and to demonstrate how proper management of those risks can help mitigate these impacts. The purpose is to feed that information into developer's investment strategy to be able to understand whether or not to participate in particular power plant development projects, and how to participate. First phase of the dissertation is an analysis of power plant investment decisions and development process, followed by identification of risks across all stages of development. Through data mining of performance indicators of around 300 power plant development projects worldwide, clusters of geographical locations, energy technologies, and developer types are highlighted. This helps us understand which projects developers should consider for evaluation given performance trends of geographic locations, and energy technologies. Our research then introduces a novel approach to power plant project risk analysis. We combine a System Dynamics model of the power plant development process with an Analytical Network Process model that enables identification of key relationships among risks and their impact on the development process. The models are used to construct project risk profiles. These three models work together to show how developers can make risk informed decision when selecting amongst power plant project opportunities, how they should best prepare projects to mitigate negative impacts of risks involved, and how they should react to changes in managing development performance over a project's lifetime.
by Ásbjörg Kristinsdóttir.
Ph.D. in Construction Engineering and Management
245 p.
eng
Massachusetts Institute of Technology
M.I.T. theses are protected by
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http://dspace.mit.edu/handle/1721.1/7582
Civil and Environmental Engineering.
Risks and decision making in development of new power plant projects
Thesis
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<Abstract>Power plant development projects are typically capital intensive and subject to a complex network of interconnected risks that impact development's performance. Failure to develop a power plant to meet performance constraints can come at great cost to the developer and other stakeholders involved. In order to develop an investment strategy plan based on their risk appetite, and manage risks effectively, developers must be able to identify and analyze project opportunity risks. This dissertation is motivated by the need to study the nature and impact of risks on a power plant development project, and to demonstrate how proper management of those risks can help mitigate these impacts. The purpose is to feed that information into developer's investment strategy to be able to understand whether or not to participate in particular power plant development projects, and how to participate. First phase of the dissertation is an analysis of power plant investment decisions and development process, followed by identification of risks across all stages of development. Through data mining of performance indicators of around 300 power plant development projects worldwide, clusters of geographical locations, energy technologies, and developer types are highlighted. This helps us understand which projects developers should consider for evaluation given performance trends of geographic locations, and energy technologies. Our research then introduces a novel approach to power plant project risk analysis. We combine a System Dynamics model of the power plant development process with an Analytical Network Process model that enables identification of key relationships among risks and their impact on the development process. The models are used to construct project risk profiles. These three models work together to show how developers can make risk informed decision when selecting amongst power plant project opportunities, how they should best prepare projects to mitigate negative impacts of risks involved, and how they should react to changes in managing development performance over a project's lifetime.</Abstract>
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