EAGER: Developing a Framework for Mitigating Environmental Externalities in the Power Sector to Maximize Regional Outcomes

1632945Sanders， kelly该项目旨在为潜在的变革性和跨学科方法奠定基础，通过动态的市场解决方案来减少电力部门对环境和社会的影响。主要研究目标有两个：(1)了解当地发电厂效率变化的基本驱动因素；(2)基于当地空气质量条件、水资源约束和预期气候压力水平的时空优先级，开发一种新的方法来制定发电厂调度的数学框架。虽然修改“一切照旧”调度协议可能会给消费者带来更高的直接成本，但本项目将分析实现空气、水和气候改善可能带来的效益，以及该战略与其他缓解战略在成本方面的比较。提出的策略旨在确定最佳的电厂群，以可靠地满足需求，同时最大限度地减少环境和社会后果。这项研究的社会影响可能是深远的，它提供了一个创新的数学框架，可以在不投资新的电力基础设施的情况下降低发电的社会和环境成本。虽然许多可持续发展投资可能会不成比例地惠及有能力支付溢价的人群，但拟议的框架提供了一个系统规模的干预，从战略上确定将从当地发电减少中获益最多的地区。所提出的地质统计框架也可以更广泛地用于为新的基础设施投资的布局和根据最大潜在利益进行新的可持续性干预的目标区域提供信息。

1632945Sanders, KellyThis project proposes to develop the foundation for a potentially transformative and interdisciplinary approach to reduce the environmental and social impacts of the electric power sector through a dynamic market-based solution. There are two major research objectives: (1) understanding the fundamental drivers of variations in local power plant efficiency, and (2) developing a new approach to formulating a mathematical framework for power plant dispatching based on the spatio-temporal prioritization of local air quality conditions, water constraints, and anticipated levels of climate stress. Although modifying the "business as usual" dispatching protocol would likely result in higher direct costs to consumers, this project will analyze the benefits that could result in achieving air, water, and climate improvements and how this strategy compares in cost to other mitigation strategies. The proposed strategy is targeted to determine the best power plant fleet to meet demand reliably, while minimizing environmental and social consequences. The societal impact of this research is potentially far-reaching, offering an innovative mathematical framework that may reduce the social and environmental costs of power generation without new power infrastructure investments. While many sustainability investments may disproportionally benefit populations that are able to pay a premium, the proposed framework offers a systems-scale intervention that strategically identifies regions that would benefit the most from reductions in local power generation. The geostatistical framework proposed can also be used more generally to inform the placement of new infrastructure investments and regions that could be targeted for new sustainability interventions based on greatest potential benefits.