EAGER: SAI: New Decision Paradigms by Integrating Utility Theory into Infrastructure Investments

EAGER：SAI：将效用理论融入基础设施投资的新决策范式

• 批准号: 2121730
• 负责人: Destenie Nock
• 金额: $ 30万
• 依托单位: Carnegie-Mellon University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-01 至 2024-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2121730&HistoricalAwards=false
• 关键词: EAGER; SAI; New; Decision; Paradigms

Strengthening American Infrastructure (SAI) is an NSF Program seeking to stimulate human-centered fundamental and potentially transformative research that strengthens America’s infrastructure. Effective infrastructure provides a strong foundation for socioeconomic vitality and broad quality of life improvement. Strong, reliable, and effective infrastructure spurs private-sector innovation, grows the economy, creates jobs, makes public-sector service provision more efficient, strengthens communities, promotes equal opportunity, protects the natural environment, enhances national security, and fuels American leadership. To achieve these goals requires expertise from across the science and engineering disciplines. SAI focuses on how knowledge of human reasoning and decision making, governance, and social and cultural processes enables the building and maintenance of effective infrastructure that improves lives and society and builds on advances in technology and engineering.The aim of this project is to create a new framework for energy infrastructure investment decisions in the US by integrating more “macro” system-level sustainability analysis with more “micro” distributional preferences of stakeholders to generate more realistic, multi-level decision-making models. Decisions around energy system infrastructure investments involve numerous decision-makers and constituencies, each of which has their own interpretations and priorities. Different stakeholder objectives can conflict, and even may change over time as decision-makers learn more about the implications of their chosen investment decisions. Infrastructure investments otherwise beneficial can also lead to poor distributional outcomes if marginalized groups are excluded from the benefits. This project investigates priorities and perceptions around distributions of outcomes and opportunities, examines how they may change with education, incorporates them into an energy infrastructure optimization model, and evaluates preferences for this model.This framework is created by coupling an energy system optimization model with stakeholder elicitations, allowing stakeholders to determine and update acceptable tradeoffs between the environment, cost, and distributional outcomes for energy transition investment in the US. First, distributional preferences are elicited from the future engineering workforce along with an evaluation of how education can affect these preferences. Second, these preferences are integrated into an energy micro-grid investment decision model (Maximize Energy Access Model). Third, a survey is administered to the local community to elicit community preferences and these preferences are integrated into the optimization models. Throughout this process, the differences between engineering students and community members are examined.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

加强美国基础设施（SAI）是NSF的一项计划，旨在促进以人为本的基础和潜在的变革性研究，以加强美国的基础设施。有效的基础设施为社会经济活力和广泛改善生活质量奠定了坚实的基础。强大、可靠和有效的基础设施刺激私营部门创新，促进经济增长，创造就业机会，提高公共部门服务提供的效率，加强社区建设，促进机会平等，保护自然环境，增强国家安全，并推动美国的领导地位。为了实现这些目标，需要来自科学和工程学科的专业知识。SAI专注于人类推理和决策，治理，该项目的目的是通过将更多的“宏观”系统层面的可持续性分析与更多的“微观”可持续性分析相结合，为美国的能源基础设施投资决策创建一个新的框架。利益相关者的分布偏好，以产生更现实的，多层次的决策模型。围绕能源系统基础设施投资的决策涉及众多的决策者和支持者，每个人都有自己的解释和优先事项。不同的利益相关者的目标可能会发生冲突，甚至可能随着决策者对他们所选择的投资决策的影响的了解而发生变化。如果边缘化群体被排除在利益之外，基础设施投资在其他方面是有益的，也可能导致分配结果不佳。该项目调查了围绕成果和机会分布的优先级和感知，研究了它们如何随着教育而变化，将其纳入能源基础设施优化模型，并评估该模型的偏好。该框架通过将能源系统优化模型与利益相关者启发相结合而创建，允许利益相关者确定和更新环境，成本，以及美国能源转型投资的分配结果。 首先，从未来的工程劳动力的分布偏好引出沿着教育如何影响这些偏好的评估。 其次，这些偏好被集成到一个能源微电网投资决策模型（最大化能源接入模型）。 第三，对当地社区进行调查，以得出社区偏好，并将这些偏好整合到优化模型中。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Latent demand for electricity in sub-Saharan Africa: a review

撒哈拉以南非洲地区的潜在电力需求：回顾

• DOI: 10.1088/2634-4505/ac5fb2
• 发表时间: 2022
• 期刊: Environmental Research: Infrastructure and Sustainability
• 作者: Van-Hein Sackey, Charles;Levin, Todd;Nock, Destenie
• 通讯作者: Nock, Destenie

The need for agricultural productive uses in the national electrification plan of sub-Saharan African countries—a call to action for Ethiopia

撒哈拉以南非洲国家国家电气化计划中对农业生产用途的需求——呼吁埃塞俄比亚采取行动

• DOI: 10.1088/2634-4505/ac611e
• 发表时间: 2022
• 期刊: Environmental Research: Infrastructure and Sustainability
• 作者: Van-Hein Sackey, Charles;Nock, Destenie
• 通讯作者: Nock, Destenie