Decision Analysis in the UK Energy Supply Chain Risk Management: Tools Development and Application

Decision Analysis in the UK Energy Supply Chain Risk Management: Tools Development and Application by Amin Vafadarnikjoo Registration number: 100166891 Thesis submitted to The University of East Anglia for the Degree of Doctor of Philosophy (PhD) August 2020 Norwich Business School “This copy of the thesis has been supplied on condition that anyone who consults it is understood to recognise that its copyright rests with the author and that use of any information derived therefrom must be in accordance with current UK Copyright Law. In addition, any quotation or extract must include full attribution.” 1 Abstract Large infrastructures like electricity supply networks are widely presumed to be crucial for the functioning of societies as they create conditions for essential economic activities. There has always been a continuing concern and complexity around risks in the field of energy security and particularly power grids within energy supply chain. Drawing on this complexity and a need for useful tools, this research contributes to developing and utilising proper decision-making tools (i.e. methods and models) to deal with the risk identification and mitigation in the UK energy supply chain as a compound networked system. This thesis is comprised of four study phases (Figure I.A.). It is aimed at developing decision-making tools for risk identification, risk interdependency analysis, risk prioritisation, and long-term risk mitigation strategy recommendations. The application of the tools has focused on the UK power supply chain. The five new tools which are introduced and applied in this thesis are: (1) Proposed Expert Selection Model (ESM) and its application under hesitant fuzzy environment (i.e. HESM), (2) Proposed Neutrosophic Revised Decision-Making Trial and Evaluation Laboratory (NR-DEMATEL) method, (3) Proposed hybrid Spanning Trees Enumeration and Best-Worst Method (STE-BWM), (4) Proposed Neutrosophic Enhanced BWM (NE- BWM), and (5) Proposed stratified model of game of chance involving risk. In this thesis, the applied decision analysis tools not only are theoretically improved but also implemented in the UK power supply chain risk management to validate their effectiveness. The utilised tools can provide helpful models and methods to illuminate and solve managerial problems by enhancing decision making and policy setting. 2 Figure I.A Phases of the research Phases I and II: In Phase I, a framework is proposed containing 12 risk dimensions, and 5 classification perspectives. The 12 risk dimensions include Climate Change (CC), Natural Disasters (ND), Environmental and Health Safety (EHS), Technical Reliability (TR), Operational Safety (OS), Disease Outbreak (DO), Political Instability (PI), Industrial Action (IA), Sabotage and Terrorism (ST), Resource Availability (RA), Market Failure (MF), and Affordability (AF). The five 3 classification perspectives are context-based, position-based, temporal, origin-based, and hybrid classification. Then, in Phase II, the NR-DEMATEL has been applied in order to analyse the 12 identified risk dimensions based on the causal interrelationships and interdependencies among them, which has been missing in the current electricity risk management practices. Additionally, a novel Hesitant Expert Selection Model (HESM) to systematically assist researchers with the expert selection process is also proposed. The proposed HESM along with scenario analysis would provide a basis for the expert selection and weight assignment process. Findings have suggested the six most significant risk dimensions are ND, CC, IA, AF, PI and ST. Phase III: Besides the interrelationships between risks, it is important to know the ranking of identified risks which motivated the development and application of the BWM, by highlighting some weaknesses in the original BWM and contributing to the theoretical development. The NE-BWM and STE-BWM are introduced to enhance the efficiency of the original BWM in dealing with uncertainty in experts’ subjective judgements. The application results have highlighted that CC and ND are two most critical risk dimensions. Phase IV: A novel generic stratified decision-making model is introduced. It is based on Concept of Stratification (CST), game theory and Shared Socio-economic Pathway (SSP) to deal with long-term risk mitigation planning for the most critical identified risks (i.e. CC, and ND). The model is applied in the region of Highland and Argyll in Scotland based on the primary data obtained from experts to prioritise flooding risk mitigation strategies which were recommended by the Scottish Environment Protection Agency (SEPA). The model takes into account both UK socio-economic situations and flooding risk impacts for the long-term decision making (5 to 20-year time frame). The findings indicate that the most important strategies which can provide long-term benefit in mitigating flooding risk impact in the area of Highland and Argyll in Scotland are flood forecasting, awareness raising, emergency plans/response, planning policies, maintenance, and self help, respectively. 4 Acknowledgements I have benefited greatly from mentors and advisors to whom I wish to express my warmest gratitude. First and foremost, I would like to express my heartfelt appreciation to my supervisors Prof. Konstantinos Chalvatzis and Dr. Tiago Botelho for their sincere guidance, positive attitude and unwavering support throughout my PhD study. I am sincerely thankful to Prof. Madjid Tavana who has been a kind and sagacious mentor to me by offering profound guidance and insights. I must give my thanks to my former supervisors Prof. Nishikant Mishra and Dr. Hangfei Guo, as well as the current and former Post-graduate research director of Norwich Business School, Dr. Pinar Guven Uslu and Prof. Min Zhang for their support. I wish to express my deepest gratitude to all incredible friends, PhD peers, and administrative and academic staff at Norwich Business School, University of East Anglia who supported me, and helped me flourish during my PhD. I truly appreciate and acknowledge the University of East Anglia Social Science Faculty that made this PhD study possible for me by awarding me the UEA Scholarship. Finally, I must take this opportunity to recognise the invaluable support, pure love and active encouragement of my mother, father and sister who have been always there for me. I am so fortunate to have them in my life. 5 Dissemination of Results Part of the results of this thesis are disseminated via presentation at conferences and publication as a journal paper in Annals of Operations Research journal. The details are as follows: Journal Article: Vafadarnikjoo, A., Tavana, M., Botelho, T., Chalvatzis, K. (2020). “A Neutrosophic Enhanced Best-Worst Method for Considering Decision-Makers’ Confidence in the Best and Worst Criteria.” Annals of Operations Research, 289(2), 391-418. https://doi.org/10.1007/s10479-020-03603-x This paper is mainly based on part of the Chapter 6 regarding the proposed method NE-BWM in Section 6.3. Other co-authors’ contributions included guidance for improvement and minor editing the text, figures and tables. Conference Presentations: 1. Vafadarnikjoo, A. (2019). “Modified Best-worst Method with Decision Maker’s Uncertain Confidence about the Best and Worst Criteria.” OR61 Annual Conference, 3rd September, University of Kent, Canterbury, UK. (Oral Presentation) 2. Vafadarnikjoo, A. (2018). “UK Energy Supply Chain Risk Identification and Evaluation.” OR60 Annual Conference, 13th September, Lancaster University, Lancaster, UK. (Oral Presentation) 6 Table of Contents Chapter 1 Introduction ........................................................................................... 18 1.1 Background .......................................................................................................... 18 1.1.1 Energy tri-lemma ................................................................................. 18 1.1.2 Energy supply chain ............................................................................ 19 1.1.3 Risks, accidents, and incidents ............................................................ 21 1.2 Aims and Objectives ............................................................................................ 22 1.2.1 Research questions .............................................................................. 23 1.2.2 Research objectives ............................................................................. 23 1.3 Thesis Structure and Summary ............................................................................ 24 Chapter 2 Literature Review .................................................................................. 28 2.1 Introduction.......................................................................................................... 28 2.2 Decision Analysis Methods in Energy Planning and Risk Management ............ 28 2.3 Energy Security ................................................................................................... 30 2.4 Energy Supply Chain Risks ................................................................................. 32 2.4.1 Climate change .................................................................................... 33 2.4.2 Natural disasters .................................................................................. 34 2.4.3 Environmental and health safety ......................................................... 35 2.4.4 Technical reliability ............................................................................

Load more