Development of a Risk-Based Investment Decision Framework for the Identification of Low-Carbon Pathways for Energy and Water Cogeneration Portfolios
The economic viability of cogeneration expansion planning, including low-carbon technologies, is becoming challenging due to the inherent volatility of global market conditions. Current approaches do not consider relevant risk factors that impact the outcomes of scenario analyses for cogeneration expansion planning, thereby leading to biased decision-making. This research aims to develop a risk-based investment decision framework using techno-economic analysis, real options analysis and cogeneration portfolio optimisation to evaluate economic low-carbon pathways. The research aims to enhance the existing techno-economic methodologies to aid in identifying resilient technology portfolios for deploying integrated energy and water cogeneration systems. The proposed methodological framework in this research is broadly divided into: (a) model development for real and hypothetical configurations of integrated resource systems based on renewable energy that is envisaged to be an improvement over the existing (or baseline high CO2 emissions) conditions; (b) identification and modelling of risk factors and scenarios that induce financial risks for all the portfolios and expansion options considered; and (c) economic and emissions assessment of scenarios and portfolio optimisation.
This framework was applied to several case studies involving Qatar's energy and water cogeneration sector. Based on the outcomes of this research, applying the proposed framework is expected to allow energy planners and policymakers to achieve environmental targets with lower financial risks. Moreover, the framework is flexible enough to incorporate information specific to any locale and it enables tailored investment decisions, including investment flexibility based on the prevalent economic conditions to meet the demand and the emissions target policies.
History
Language
- English
Publication Year
- 2024
License statement
© The author. The author has granted HBKU and Qatar Foundation a non-exclusive, worldwide, perpetual, irrevocable, royalty-free license to reproduce, display and distribute the manuscript in whole or in part in any form to be posted in digital or print format and made available to the public at no charge. Unless otherwise specified in the copyright statement or the metadata, all rights are reserved by the copyright holder. For permission to reuse content, please contact the author.Institution affiliated with
- Hamad Bin Khalifa University
- College of Science and Engineering - HBKU
Geographic coverage
QatarDegree Date
- 2024
Degree Type
- Doctorate