A multi-dimensional sensitivity analysis approach for evaluating the robustness of renewable energy sources in European countries

被引:14
作者
Wieckowski, Jakub [1 ]
Kizielewicz, Bartlomiej [2 ]
Salabun, Wojciech [1 ,2 ]
机构
[1] West Pomeranian Univ Technol Szczecin, Fac Comp Sci & Informat Technol, Dept Artificial Intelligence & Appl Math, Res Team Intelligent Decis Support Syst, Ul Zolnierska 49, PL-71210 Szczecin, Poland
[2] Natl Inst Telecommun, Szachowa 1, PL-04894 Warsaw, Poland
关键词
Renewable energy sources; Sustainable development; Robustness analysis; Decision-making; Sensitivity analysis; Robust decisions; MULTICRITERIA DECISION-ANALYSIS; POWER-GENERATION; POLICY SCENARIOS; HEALTH-CARE; MCDM; SELECTION; ELECTRICITY; CRITERIA; PRIORITIZATION; INTEGRATION;
D O I
10.1016/j.jclepro.2024.143225
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The necessity of making reliable decisions is exceptionally important in the field of sustainable development, particularly when evaluating the management of renewable energy sources. A thorough analysis becomes imperative in complex decision problems where various factors influence outcomes. Multi-Criteria Decision Analysis (MCDA) methods have emerged as valuable tools for addressing such challenges, enabling decision- makers to navigate through conflicting criteria and make informed choices. Combined with sensitivity analysis approaches, comprehensive assessments can be achieved, ensuring the robustness of decision-making processes. To increase the reliability of the results, different aspects of input data fluctuations should be examined to provide a broader view of the stability of the results. This paper proposes a comprehensive multi-dimensional sensitivity analysis approach to assess the robustness of renewable energy source (RES) development in selected European countries. By evaluating RES management in terms of electricity and energy consumption and generation, the study addresses key components of sustainable development. It offers a holistic perspective on result reliability and stability by analyzing five sensitivity dimensions: a comparative analysis of four MCDA methods, varying criteria weights scenarios, probabilistic modifications, criteria relevance identification, and ranking stability. This approach enhances decision-making in sustainable energy development, providing valuable insights for policymakers on prioritizing sustainable technologies. The provided open-source implementation promotes transparency and accessibility in decision support systems.
引用
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页数:26
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