Scenario analysis for renewable energy investment using a hybrid framework: A case study in Saudi Arabia

• Published in: Renewable energy focus 2023-09, Vol.46, p.170-184
• Main Authors: Almulhim, Tarifa, Yousif, Mohammed Al
• Format: Article
• Language: English
• Subjects: IFS; Leontief’s input-output model; Multiple-Criteria Group Decision-Making (MCGDM); Renewable Energy Investments; VIKOR method
• ISSN: 1755-0084; 1878-0229
• DOI: 10.1016/j.ref.2023.06.006

[Display omitted] •A hybrid framework to analysis Saudi renewable energy investments is proposed.•The framework proposed based on leontief and fuzzy group decision support models.•The analysis combines expert opinions with statistical data.•A sensitivity analysis assesses to what extend this hybrid framework is robust. This study aims to analyse potential future renewable energy investment scenarios and the evaluation criteria that influence the selection of an optimal scenario. For the first time in studying the renewable energy sector, a hybrid framework is proposed to address the selection process. The proposed hybrid framework combines these multi-disciplinary approaches: considering macroeconomic assumptions, using historical information as quantitative data and eliciting judgements from decision experts as qualitative data. Moreover, it tackles uncertainty regarding the future direction of renewable energy investments by utilising Intuitionistic Fuzzy Set theory. An application of the proposed hybrid framework for a case in Saudi Arabia was conducted in three phases. The first phase applied Leontief’s input-output model and proposed three investment scenarios by 2030, namely: the ‘based scenario‘ (investment of 112 billion Saudi Riyals), an ‘alternative scenario 1’ (investment of 75 billion Saudi Riyals) and an ‘alternative scenario 2’ (investment of 25 billion Saudi Riyals). The second phase established five decision criteria that are considered when selecting an optimal investment scenario, namely: ‘Economic’, ‘Environmental’, ‘Social’, ‘Public preferences’ and ‘Risk’. The third phase applied a Fuzzy Group Decision Support model to rank the scenarios. The results indicate that the ‘based scenario‘ and the ‘alternative scenario 1’ are always the compromise investment scenarios and that ‘alternative scenario 2’ is not preferred. A sensitivity analysis was applied to validate the results.