全球敏感性分析,以提高能源系统优化建模的透明度和严谨性
William Usher1, Trevor Barnes2, Nandi Moksnes1
1Energy Technology, KTH Royal Institute of Technology, Stockholm, Sweden.
全球敏感性分析 (GSA) 为能源系统优化模型 (ESOMs) 提供了实际指导. 这种方法有效地识别了关键参数,提高了长期能源规划的透明度和可靠性.
科学领域:
- 能源系统分析 能源系统分析
- 计算建模 计算建模
- 不确定性定量化 不确定性定量化
背景情况:
- 能源系统优化模型 (ESOM) 对国家和地区的长期能源规划至关重要.
- 尽管已被认可的重要性,但关于将不确定性纳入ESOM的实际指导,如全球敏感性分析 (GSA),是有限的.
- 现有的文献显示了GSA的良好应用,但缺乏全面的实施策略.
研究的目的:
- 为在ESOM中进行GSA提供全面指导方针,从而降低采用障碍.
- 提供关于GSA在能源系统建模中的必要性和应用的教学见解.
- 在开源能源建模系统 (OSeMOSYS) 框架内使用莫里斯方法来演示GSA的实际实施.
主要方法:
- 在ESOM中制定GSA实施指导方针.
- 使用莫里斯方法用于GSA,这是一个计算效率高的技术.
- 将GSA应用于简单的示例模型和使用OSeMOSYS的现实能源系统模型.
主要成果:
- 在简单和复杂的ESOM中,GSA成功地确定了有影响力和无影响力的参数.
- 分析表明,使用开源工具,GSA可以很容易地应用于ESOM.
- 调查结果与最佳实践研究一致,强调包括所有参数,避免过度关注技术成本等特定参数.
结论:
- 执行GSA显著有利于能源系统优化场景的设计和稳定性.
- 解释GSA结果提高了能源系统建模研究的透明度和科学严谨性.
- 在能源系统规划中,GSA是理解参数影响和管理不确定性的重要工具.
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