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

1632945桑德斯，凯利该项目提出了一个潜在的变革和跨学科的方法，以减少电力部门通过动态的市场为基础的解决方案的环境和社会影响的基础。有两个主要的研究目标：（1）了解当地电厂效率变化的基本驱动因素，以及（2）开发一种新的方法来制定一个数学框架，根据当地空气质量条件，水资源限制和预期的气候压力水平的时空优先级的电厂调度。虽然修改“照常营业”调度协议可能会导致消费者的直接成本更高，但该项目将分析可能导致空气，水和气候改善的好处，以及该策略与其他缓解策略的成本比较。所提出的战略旨在确定最佳的发电厂车队，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，提供了一个创新的数学框架，可以在没有新的电力基础设施投资的情况下降低发电的社会和环境成本。虽然许多可持续性投资可能会使能够支付溢价的人口受益，但拟议框架提供了一种系统规模的干预措施，从战略上确定了从减少当地发电量中受益最多的地区。拟议的地质统计框架还可更广泛地用于为新基础设施投资的安排和根据最大潜在效益可采取新的可持续性干预措施的区域提供信息。

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.