Kristinsdottir, A (2012) Risks and decision making in development of new power plant projects. PhD thesis, Massachusetts Institute of Technology, USA.
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.
| Item Type: | Thesis (Doctoral) |
|---|---|
| Thesis advisor: | Moavenzadeh, F |
| Uncontrolled Keywords: | failure; decision making; investment; project risk analysis; data mining; risk analysis; developer; stakeholder |
| Index terms: | performance indicator, investment strategy, system dynamics, decision-making, risk analysis, energy technology, data mining, risk-informed, power plant, project risk analysis, dissertation, investment decision |
| Subjects: | economic analysis, innovation and technology management, research dissemination and communication, environmental hazards, financial risk, data science, computing systems, infrastructure and transport systems, decision analysis, performance management |
| Topics: | Quality Management, Engineering Principles, Risk Management, Sustainability, Digital Applications, Cost Management, Business Strategy, Research Practice |
| Descriptive scope: | 4 PCTA |
N.B. Descriptive scope is a count of how many of the five facets of empirical research are indicated by the words used in title, abstract and keywords. It is not intended as a judgement on the research; merely a count of the kind of word we would expect to indicate Phenomenon, Concepts, Theoretical framing, Empirical techniques, Analytical techniques. If all five are present, then a code of “5 PCTEA” will indicate this. If you feel the coding for this record is questionable, we welcome discussion around the terms we matched or the way we categorized them. The facet you would expect may not be coded, or a facet may be coded inappropriately. This can also bear on a larger question, of which facets should be treated as defining in construction management research. Please get in touch, and we will look at it. More details here