Decision making under coupled multi-timescale uncertainty: Advanced electric power systems planning
Decision making under coupled multi-timescale uncertainty: Advanced electric power systems planning
批准号:
1128147
负责人:
Mort Webster
金额:
$33.0万
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2011
资助国家:
美国
项目状态:
已结题
起止时间:
2011-08-15 至 2014-07-31
中文摘要
这项研究的目的是开发改进的电力系统规划工具。这项研究的方法是结合每小时和每年的时间尺度进行分析,以便在发电技术的长期投资规划中考虑到发电机如何运行的限制。随着可再生能源、储能和响应性需求的增加,这些限制尤为重要。该项目将应用近似动态规划和传统的整数优化技术来探索两个时间尺度下的不确定性决策。将利用运营和投资子问题的结构来开发优化整个系统的有效方法,考虑需求、可再生发电、燃料价格和可能的环境法规的不确定性。本项目将通过开发新的算法和数据结构设计,开发在不确定条件下优化大型工程系统的新方法。它还将推进多时间尺度决策模型的最新技术,其中较小的时间尺度计算成本很高。这项工作将显著改善结合可再生能源和其他先进技术的先进电力系统的规划,以满足环境和能源要求,并将确定具有更低成本和更大弹性的系统设计。开发的方法将可供正在设计下一代电力系统的电力公司、独立系统运营商以及各种政府和非政府机构使用。该项目还将向本科生和研究生,包括妇女和代表性不足的少数民族,提供业务研究和电力系统建模方面的教育和培训。
英文摘要
The objective of this research is to develop improved tools for planning for electric power systems. The approach of this research is to combine analysis at hourly and annual timescales so that constraints on how electricity generators operate are accounted for in long-term investment planning for generation technologies. Such constraints are particularly important with increasing use of renewables, storage, and responsive demand. The project will apply approximate dynamic programming and traditional integer optimization techniques to explore decisions under uncertainty in both time scales. The structure of the operations and investment sub-problems will be exploited to develop efficient methods for optimizing the full system, accounting for uncertainty in demand, renewable generation, fuel prices, and possible environmental regulations.Intellectual MeritThis project will develop new methods for optimizing large engineering systems under uncertainty by developing new algorithms and data structure designs. It will also advance the state-of-the art for multi-timescale decision models where the smaller timescale is computationally expensive. Broader ImpactsThis work will significantly improve planning for advanced electric power systems that combine renewables and other advanced technologies to meet environmental and energy requirements, and will identify system designs with lower costs and greater resiliency. The methods developed will be usable by power companies, independent system operators, and variety of governmental and non-governmental agencies that are in the process of designing the next-generation power system. This project will also provide education and training to undergraduate and graduate students, including women and underrepresented minorities, in operations research and power systems modeling.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
Efficient and Scalable Methods for Multi-Stage Transmission Expansion under Uncertainty
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批准号:1710974
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项目类别:Standard Grant
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资助金额:$31.47万
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财政年份:2017
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负责人:Mort Webster
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依托单位:
Collaborative Research: DRU: An Improved Model of Endogenous Technical Change Considering Uncertain R&D Returns and Uncertain Climate Response
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批准号:0825915
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项目类别:Standard Grant
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资助金额:$44.21万
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财政年份:2008
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负责人:Mort Webster
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依托单位:
国内基金
海外基金
Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis
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批准号:--
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项目类别:合作创新研究团队
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资助金额:--
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批准年份:2024
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负责人:姚韬
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依托单位:
补偿性还是非补偿性规则:探析风险决策的行为与神经机制
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批准号:31170976
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项目类别:面上项目
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资助金额:64.0万元
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批准年份:2011
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负责人:李纾
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依托单位: