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在不确定性下的顺序决策,用于长期能源转型规划.
Molly A McDonald1, Christos T Maravelias1,2
1Chemical and Biological Engineering, Princeton University, 50 Olden St, Princeton, NJ 08540, USA.
iScience
|December 4, 2024
概括
这项研究引入了能源系统建模的新方法,以应对全球变暖. 通过考虑不确定性,它产生了多样化和有弹性的低碳技术途径.
科学领域:
- 能源系统分析 能源系统分析
- 气候变化缓解缓解 气候变化缓解
- 随机模型建模 随机模型建模
背景情况:
- 全球变暖推动了排放法规和低碳技术激励措施.
- 传统的能源系统模型假设确定性参数和单点规划.
- 这些假设限制了对能源转型途径的系统分析.
研究的目的:
- 为系统的能源转型路径生成和分析提出宽松的假设.
- 将不确定性纳入能源系统建模.
- 评估能源转型途径的弹性.
主要方法:
- 随机编程 (SP) 用于处理参数不确定性.
- 顺序决策与SP配对用于适应性规划.
- 基于模拟的方法来评估过渡路径质量.
主要成果:
- 通过主动和反来考虑不确定性,可以产生多样化的技术组合.
- 提出的方法产生了对不确定性有弹性的能源转型途径.
- 放松决定性假设可以增强对能源期货的分析.
结论:
- 整合不确定性管理对于稳健的能源系统规划至关重要.
- 随机编程和顺序决策为能源转型分析提供了改进的方法.
- 这些发现支持开发有弹性的低碳能源系统.
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